**Applications**



[19] Bestrin R, Vermeulen AG. Mathematical modeling and analysis of vapour compres

[20] García-Vallardes O, Pérez-Segarra CD, Rigola J. Numerical simulation of double-pipe condensers and evaporators. International Journal of Refrigeration. 2004;**27**:656-670 [21] Xu B, Yebi A, Onori S, Filipi Z, Liu X, Shutty J. Power maximization of a heavy duty diesel organic Rankine cycle waste heat recovery system utilizing mechanically coupled and fully electrified turbine expanders. In: Proceedings of the ASME 2016 Internal

[22] Invernizzi C, Iora P, Silva P. Bottoming micro-Rankine cycles for micro-gas turbines.

[23] Weiss HH, Boshwirth L. A simple but efficient equipment for experimental determi

[24] Feru E, Willems F, de Jager B, Steinbuch M. Modeling and control of a parallel waste heat recovery system for Euro-VI heavy-duty diesel engines. Energies, vol. 7, pp. 6571-

[25] Moran MJ, Shapiro HN. Fundamentals of Engineering Thermodynamics. 5th ed.,

[26] Mollaei Barzi Y, Assadi M, Parham K. A waste heat recovery system development and analysis using ORC for the energy efficiency improvement in aluminum electrolysis

[27] Elmqvist H, Mattsson SE. An introduction to the physical modeling language Modelica. In: Proceedings of the 9th European Simulation Symposium, ESS'97; October 19-23,

[29] Cennerilli S, Sciubba E. Application of the CAMEL process simulator to the dynamic simulation of gas turbines. Energy Conversion and Management. 2007;**48**:2792-2801 [30] Cennerilli S, Fiorini P, Sciubba E. Application of the Camel process simulator to the dynamic simulation of gas turbines. In: ECOS 2006 Proceedings; Vol. 1; 2006. pp. 355-363

[31] Traverso A. TRANSEO: A new simulation tool for transient analysis of innovative energy systems [PhD thesis]. Italy: TPG-DiMSET, University of Genova; 2004

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[28] Pfafferott T, Schmitz G. Modeling and transient simulation of CO

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6592, 2014

Chichester

, England

1997; Passau, Germany; 1997

sion system. International Report. Eindhoven, Netherlands: University of Technology;

**Chapter 7**

**Provisional chapter**

**The Development and Application of Organic Rankine**

**The Development and Application of Organic Rankine** 

The development of engine waste heat recovery (WHR) technologies attracts ever increasing interests due to the rising strict policy requirements and environmental concerns. Organic Rankine Cycle (ORC) can convert low medium grade heat into electrical or mechanical power and has been widely recognized as the most promising heat-driven technologies. A typical internal combustion engine (ICE) converts around 30% of the overall fuel energy into effective mechanical power and the rest of fuel energy is dumped through the engine exhaust system and cooling system. Integrating a well-designed ORC system to ICE can effectively improve the overall energy efficiency and reduce emissions with around 2–5 years payback period through fuel saving. This book chapter is meant to provide an overview of the technical development and application of ORC technology to recover wasted thermal energy from the ICE with a particular focus on vehicle applications. **Keywords:** internal combustion engine, vehicle application, organic Rankine cycle,

Over the last century, the internal combustion engine (ICE) as one of the main power sources has been widely adopted in the vehicle and marine propulsion systems such as automobiles, trains, trucks, boats, and ships. The increasing concerns on the environmental problems caused by burning fossil fuels promote the technology development of more efficient, more compact, and more cost-effective ICE, which can potentially improve the overall energy efficiency, reduce the emissions and generate more effective engine shaft power by burning fossil

> © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

distribution, and reproduction in any medium, provided the original work is properly cited.

DOI: 10.5772/intechopen.78401

**Cycle for Vehicle Waste Heat Recovery**

**Cycle for Vehicle Waste Heat Recovery**

Yiji Lu, Anthony Paul Roskilly and Xiaoli Yu

Yiji Lu, Anthony Paul Roskilly and Xiaoli Yu

Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.78401

engine waste heat recovery

**Abstract**

**1. Introduction**

#### **The Development and Application of Organic Rankine Cycle for Vehicle Waste Heat Recovery The Development and Application of Organic Rankine Cycle for Vehicle Waste Heat Recovery**

DOI: 10.5772/intechopen.78401

Yiji Lu, Anthony Paul Roskilly and Xiaoli Yu Yiji Lu, Anthony Paul Roskilly and Xiaoli Yu

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.78401

#### **Abstract**

The development of engine waste heat recovery (WHR) technologies attracts ever increasing interests due to the rising strict policy requirements and environmental concerns. Organic Rankine Cycle (ORC) can convert low medium grade heat into electrical or mechanical power and has been widely recognized as the most promising heat-driven technologies. A typical internal combustion engine (ICE) converts around 30% of the overall fuel energy into effective mechanical power and the rest of fuel energy is dumped through the engine exhaust system and cooling system. Integrating a well-designed ORC system to ICE can effectively improve the overall energy efficiency and reduce emissions with around 2–5 years payback period through fuel saving. This book chapter is meant to provide an overview of the technical development and application of ORC technology to recover wasted thermal energy from the ICE with a particular focus on vehicle applications.

**Keywords:** internal combustion engine, vehicle application, organic Rankine cycle, engine waste heat recovery

## **1. Introduction**

Over the last century, the internal combustion engine (ICE) as one of the main power sources has been widely adopted in the vehicle and marine propulsion systems such as automobiles, trains, trucks, boats, and ships. The increasing concerns on the environmental problems caused by burning fossil fuels promote the technology development of more efficient, more compact, and more cost-effective ICE, which can potentially improve the overall energy efficiency, reduce the emissions and generate more effective engine shaft power by burning fossil

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

fuels [1]. Moreover, the increasingly strict emission legislations are focusing on the nitrogen oxides (NOx), particulate matter (PM), carbon monoxide (CO), and hydrocarbon (HC).

the commercial ORC system for vehicle application is still not available from the market. One of the possible reasons is the concern on the substantial capital cost due to the complexity of the

The Development and Application of Organic Rankine Cycle for Vehicle Waste Heat Recovery

http://dx.doi.org/10.5772/intechopen.78401

129

The application of steam Rankine cycle for vehicle waste hear recovery has been reported by BMW in 2005 [15], who later announced the proposed system can achieve 15% improvement for engine performance [16, 17]. **Figure 1** is the schematic diagram of the BMW turbosteamer concept, who converts both engine coolant and exhaust energy into engine mechanical power. The system adopts two-stage turbine machines, which is similar as large-scale stationary

In 2008, Honda has reported the project exploring the application of steam Rankine cycle for engine exhaust heat recovery as illustrated in **Figure 2** [18]. The system adopts an axial piston swash plate type expander as the expansion machine under the controlled steam operational conditions ranging from 400 to 500°C at the pressure ranging from 7 to 9 MPa in order to optimize the Rankine cycle performance in engine transient driving conditions. The expander was directly connected to an electric generator producing electricity to recharge the battery pack. The maximum thermal efficiency of the system is 13% at 23 kW and the maximum power from the expander is 32 kW. Results are shown in 62 miles/h constant speed driving tests; the overall thermal efficiency can be improved by 3.8%. However, Honda announced the system

will not be considered for production unless higher efficiencies can be achieved [18].

**Figure 1.** Schematic diagram of BMW-Turbosteamer concept [16].

system and complicated control strategies required for vehicle application.

**1.2. Representative prototypes developed by vehicle manufactures**

power generation system.

Engine manufacturers have developed and adopted the technologies such as turbocharging, variable valve timing [2], Miller timing strategies [3], advanced injection strategies, and engine friction reduction technologies in order to improve the system thermal efficiency. However, adopting the stated technologies the ICE is still difficult to convert more than 40% of the fuel energy into effective mechanical power [4, 5]. And there is around 60–70% of fuel energy is wasted from the exhaust system and cooling system of ICE [4, 5]. Other approaches such as burning alternative fuels [6] and the development of hybrid pneumatic system [7] to recover the engine kinetic energy were also considered. Recent research attentions are focusing on the development of engine bottoming technologies such as advanced after treatment systems or engine waste heat recovery (WHR) technologies [8]. The Organic Rankine Cycle (ORC) is one of the most promising heat-driven technologies converting heat into mechanical power or electricity [9, 10]. ORC system can recover various heat sources such as biomass combustion heat, solar energy, geothermal heat, and industry wasted heat and heat from Internal Combustion Engine (ICE) [9]. Adopting ORC technology for engine waste heat recovery can effectively improve the overall system efficiency and reduce the emissions. A well-designed ORC system can potentially achieve around 2–5 years payback period through fuel saving [4, 5, 10]. However, Velez et al. [10] pointed out the market available ORC system with the power ranges of 0.2–2 MWe under the cost around 1and 4 × 103 € /kWe, and lower powers are in pre-commercial status because of the relatively long payback period using small-scale ORC system. The technical development, main research barriers, and potential solutions of the technology are summarized in this chapter, which aims to have an overview of the ORC technology and promote its applications.

#### **1.1. Emerging applications of the technology for vehicles**

The applications and extensively research interests of waste heat recovery technologies started in the 1970s during the oil crisis [11]. The first application of ORC for engine waste heat recovery was reported by Patel and Dovle in 1976 [12]. The research project conducted by Mack Trucks and the Thermo Electron Corporation was sponsored by US Department of Energy (DOE). The first prototype ORC machine was installed on a Mack 676 diesel engine to recover the exhaust waste heat. The system adopted Fluorinol-50 as the ORC working fluid and a three-stage axial flow turbine expander. The mechanical power of the expander was transferred to the power take-off device coupled with a speed reduction gearbox. They demonstrated the technical feasibility of the system and its economic interests. The optimal performance of the system could achieve a 13% increase in maximum power with around 15% reduction of fuel consumption. Follow on progress reported by Pate et al. [13] announced a 1 year test program of an ORC bottoming system coupled on a Mack diesel engine in 1979 and they declared a plan of expanding the ORC system on 10 trucks in 1981–1982. In 1983, the research group reported the testing results of the program [14], which demonstrated 12.5% improvement of the average fuel consumption on high-way vehicle fuel economy tests. However, no follow on progress for the expanding plan can be found from the literature. The ORC systems developed nowadays can achieve much higher efficiency because of the broad choice of advanced working fluids and the development of system components, such as expansion devices and heat exchangers. However, the commercial ORC system for vehicle application is still not available from the market. One of the possible reasons is the concern on the substantial capital cost due to the complexity of the system and complicated control strategies required for vehicle application.

#### **1.2. Representative prototypes developed by vehicle manufactures**

fuels [1]. Moreover, the increasingly strict emission legislations are focusing on the nitrogen oxides (NOx), particulate matter (PM), carbon monoxide (CO), and hydrocarbon (HC).

Engine manufacturers have developed and adopted the technologies such as turbocharging, variable valve timing [2], Miller timing strategies [3], advanced injection strategies, and engine friction reduction technologies in order to improve the system thermal efficiency. However, adopting the stated technologies the ICE is still difficult to convert more than 40% of the fuel energy into effective mechanical power [4, 5]. And there is around 60–70% of fuel energy is wasted from the exhaust system and cooling system of ICE [4, 5]. Other approaches such as burning alternative fuels [6] and the development of hybrid pneumatic system [7] to recover the engine kinetic energy were also considered. Recent research attentions are focusing on the development of engine bottoming technologies such as advanced after treatment systems or engine waste heat recovery (WHR) technologies [8]. The Organic Rankine Cycle (ORC) is one of the most promising heat-driven technologies converting heat into mechanical power or electricity [9, 10]. ORC system can recover various heat sources such as biomass combustion heat, solar energy, geothermal heat, and industry wasted heat and heat from Internal Combustion Engine (ICE) [9]. Adopting ORC technology for engine waste heat recovery can effectively improve the overall system efficiency and reduce the emissions. A well-designed ORC system can potentially achieve around 2–5 years payback period through fuel saving [4, 5, 10]. However, Velez et al. [10] pointed out the market available ORC system with the power ranges of 0.2–2 MWe under the cost around 1and 4 × 103 € /kWe, and lower powers are in pre-commercial status because of the relatively long payback period using small-scale ORC system. The technical development, main research barriers, and potential solutions of the technology are summarized in this chapter,

which aims to have an overview of the ORC technology and promote its applications.

The applications and extensively research interests of waste heat recovery technologies started in the 1970s during the oil crisis [11]. The first application of ORC for engine waste heat recovery was reported by Patel and Dovle in 1976 [12]. The research project conducted by Mack Trucks and the Thermo Electron Corporation was sponsored by US Department of Energy (DOE). The first prototype ORC machine was installed on a Mack 676 diesel engine to recover the exhaust waste heat. The system adopted Fluorinol-50 as the ORC working fluid and a three-stage axial flow turbine expander. The mechanical power of the expander was transferred to the power take-off device coupled with a speed reduction gearbox. They demonstrated the technical feasibility of the system and its economic interests. The optimal performance of the system could achieve a 13% increase in maximum power with around 15% reduction of fuel consumption. Follow on progress reported by Pate et al. [13] announced a 1 year test program of an ORC bottoming system coupled on a Mack diesel engine in 1979 and they declared a plan of expanding the ORC system on 10 trucks in 1981–1982. In 1983, the research group reported the testing results of the program [14], which demonstrated 12.5% improvement of the average fuel consumption on high-way vehicle fuel economy tests. However, no follow on progress for the expanding plan can be found from the literature. The ORC systems developed nowadays can achieve much higher efficiency because of the broad choice of advanced working fluids and the development of system components, such as expansion devices and heat exchangers. However,

**1.1. Emerging applications of the technology for vehicles**

128 Organic Rankine Cycle Technology for Heat Recovery

The application of steam Rankine cycle for vehicle waste hear recovery has been reported by BMW in 2005 [15], who later announced the proposed system can achieve 15% improvement for engine performance [16, 17]. **Figure 1** is the schematic diagram of the BMW turbosteamer concept, who converts both engine coolant and exhaust energy into engine mechanical power. The system adopts two-stage turbine machines, which is similar as large-scale stationary power generation system.

In 2008, Honda has reported the project exploring the application of steam Rankine cycle for engine exhaust heat recovery as illustrated in **Figure 2** [18]. The system adopts an axial piston swash plate type expander as the expansion machine under the controlled steam operational conditions ranging from 400 to 500°C at the pressure ranging from 7 to 9 MPa in order to optimize the Rankine cycle performance in engine transient driving conditions. The expander was directly connected to an electric generator producing electricity to recharge the battery pack. The maximum thermal efficiency of the system is 13% at 23 kW and the maximum power from the expander is 32 kW. Results are shown in 62 miles/h constant speed driving tests; the overall thermal efficiency can be improved by 3.8%. However, Honda announced the system will not be considered for production unless higher efficiencies can be achieved [18].

**Figure 1.** Schematic diagram of BMW-Turbosteamer concept [16].

The heat sources from the engine are usually calculated under engine steady state points from either experimental tests or simulation results. Although it is theoretically feasible and potentially worthwhile to recover the heat from charger air cooler and engine lube oil as reported in the literature [23], the practical applications of ORC system for engine waste heat recovery are mainly focusing on the exhaust energy and engine coolant energy. These two heat sources contain the majority of wasted heat energy from the engine. The maximizing utilization of these two heat sources can benefit for the overall vehicle thermal management and improve

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131

Rather than the engine used in stationary power generation system, who usually operated under fixed rotational speed for an electrical generation [24], the engine used for vehicle application operates under variable speed and torque conditions. Therefore, the full engine operational map analysis method is popularly used to evaluate the heat sources from the engine for vehicle application. For example, Zhang et al. [25] used similar analysis methods and conducted the analysis of a 105 kW light-duty diesel engine. In order to conduct the parametric performance study of engine waste heat recovery system, the following four parameters are critical to being identified: the temperature and mass flow rate of exhaust and coolant energy under variable engine operational conditions. Another alternative method to evaluate the recoverable waste heat from the engine coolant and exhaust energy was introduced by Ringler et al. [17], who pointed out that the ratio of the recoverable heat from the coolant and exhaust energy of ICE ranges from 1.5 to 0.5. The results from the reported work also supported the conclusion [26–28]. Similar analysis method to evaluate the recoverable coolant and exhaust energy from a single

cylinder engine was used and reported by Lu et al. as illustrated in **Figure 3** [30].

**Figure 3.** Recoverable coolant and exhaust energy from a single cylinder ICE [29].

the cooling circuit impact.

**Figure 2.** Layout of the Honda Rankine cycle prototype [18].

Cummins has conducted a project funded by U.S. Department of Energy to study an advanced engine waste heat recovery system using ORC technology since 2005 [19]. Cummins announced the developed ORC system can potentially improve the engine total efficiency by 5–8% [19]. The company further developed the waste heat recovery system and integrated with other advanced engine technologies aiming to boost the heavy-duty diesel engine to as high as 55% efficiency as reported in 2013 [20].

## **2. Organic Rankine cycle (OCR) for vehicle waste heat recovery (WHR)**

#### **2.1. Heat sources from ICEs**

The designed temperature difference between evaporation and condensation temperature determines the overall efficiency of a typical ORC. For on-road vehicle application, the condensation temperature is controlled by the radiator and the capability of engine radiator determines the lowest condensation temperature. Therefore, the majority studies of Waste Heat Recovery (WHR) from ICE focus on the engine exhaust energy [21], because the exhaust temperature of ICE is various from 200 to 700°C, which is much higher than the coolant temperature ranging from 80 to 100°C [4, 5]. The other two heat sources are the charge air (50–70°C) and engine oil (80–120°C) [22]. The maximum ratio of utilization the fuel energy converting into engine brake power for propulsion is about 40–45%. The rest of fuel energy is dumped through engine exhaust, wasted because of friction losses and heat transfer loses. It is, therefore, necessary to study the heat sources from ICE to design and evaluate an ORC system for engine waste heat recovery.

The heat sources from the engine are usually calculated under engine steady state points from either experimental tests or simulation results. Although it is theoretically feasible and potentially worthwhile to recover the heat from charger air cooler and engine lube oil as reported in the literature [23], the practical applications of ORC system for engine waste heat recovery are mainly focusing on the exhaust energy and engine coolant energy. These two heat sources contain the majority of wasted heat energy from the engine. The maximizing utilization of these two heat sources can benefit for the overall vehicle thermal management and improve the cooling circuit impact.

Rather than the engine used in stationary power generation system, who usually operated under fixed rotational speed for an electrical generation [24], the engine used for vehicle application operates under variable speed and torque conditions. Therefore, the full engine operational map analysis method is popularly used to evaluate the heat sources from the engine for vehicle application. For example, Zhang et al. [25] used similar analysis methods and conducted the analysis of a 105 kW light-duty diesel engine. In order to conduct the parametric performance study of engine waste heat recovery system, the following four parameters are critical to being identified: the temperature and mass flow rate of exhaust and coolant energy under variable engine operational conditions. Another alternative method to evaluate the recoverable waste heat from the engine coolant and exhaust energy was introduced by Ringler et al. [17], who pointed out that the ratio of the recoverable heat from the coolant and exhaust energy of ICE ranges from 1.5 to 0.5. The results from the reported work also supported the conclusion [26–28]. Similar analysis method to evaluate the recoverable coolant and exhaust energy from a single cylinder engine was used and reported by Lu et al. as illustrated in **Figure 3** [30].

**Figure 3.** Recoverable coolant and exhaust energy from a single cylinder ICE [29].

Cummins has conducted a project funded by U.S. Department of Energy to study an advanced engine waste heat recovery system using ORC technology since 2005 [19]. Cummins announced the developed ORC system can potentially improve the engine total efficiency by 5–8% [19]. The company further developed the waste heat recovery system and integrated with other advanced engine technologies aiming to boost the heavy-duty diesel engine to as

The designed temperature difference between evaporation and condensation temperature determines the overall efficiency of a typical ORC. For on-road vehicle application, the condensation temperature is controlled by the radiator and the capability of engine radiator determines the lowest condensation temperature. Therefore, the majority studies of Waste Heat Recovery (WHR) from ICE focus on the engine exhaust energy [21], because the exhaust temperature of ICE is various from 200 to 700°C, which is much higher than the coolant temperature ranging from 80 to 100°C [4, 5]. The other two heat sources are the charge air (50–70°C) and engine oil (80–120°C) [22]. The maximum ratio of utilization the fuel energy converting into engine brake power for propulsion is about 40–45%. The rest of fuel energy is dumped through engine exhaust, wasted because of friction losses and heat transfer loses. It is, therefore, necessary to study the heat sources from ICE to design and evaluate an ORC

**2. Organic Rankine cycle (OCR) for vehicle waste heat recovery** 

high as 55% efficiency as reported in 2013 [20].

**Figure 2.** Layout of the Honda Rankine cycle prototype [18].

130 Organic Rankine Cycle Technology for Heat Recovery

**(WHR)**

**2.1. Heat sources from ICEs**

system for engine waste heat recovery.

## **2.2. Working principle of Rankine-based power generation systems**

#### *2.2.1. Rankine cycle*

Steam Rankine cycle has been widely employed in large-scale power plants in the industry. This technology has been recognized as the most popular energy conversion systems, which mainly consists of four components, a pump, an evaporator, a turbine, and a condenser shown in **Figure 4**. The working principle of steam Rankine cycle can be described as follows. The liquid-phase water is first compressed to high-pressure state and flows into the evaporator, where the heat is provided from the heat sources to change the water from the liquid phase into the gas phase. The high-temperature and high-pressure steam then flow through an expansion machine where the power can be retrieved or converted into electricity. In the final step, the condenser rejects the heat from the expander steam and condenses the steam into the liquid phase.

Rankine cycle applies water as the working fluid, which has the advantages of high specific heat capacity, broad ranges of working conditions, non-toxic, and safe to use and environmentally friendly. However, steam Rankine system requires very high driven temperature in order to keep the steam in the gas phase at the exit of the expander. Because the exiting of liquid phase of fluid requires being prevented otherwise the blades of the turbine will be gradually damaged resulting in the reduction of lifetime and decrease of the expander efficiency [31].

in **Figure 5**. The wet fluids such as R717 have a negative slope of the vapor saturation curve. On the other hand, the dry fluids have a positive slope. The isentropic fluids have a vertical

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133

A wrong choice of working fluid could lead to a low-efficient and expensive plant of ORC system. Tchanche et al. [37] assessed the thermodynamic and environmental properties of 20 different fluids for solar Organic Rankine Cycle by comparing the system efficiency, irreversibility, flow rate, pressure ratio, toxicity, flammability, ozone depletion potential (ODP), and global warming potential (GWP). The influence of fluid properties on an ORC and a supercritical Rankine cycle with 35 different working fluids was assessed by Chen et al. [36] considering the latent heat, density, specific heat, and the effectiveness of superheating. An exergy-based study of fluid selection for geothermal generated ORC system was conducted by Heberle et al. [38]. The exergy analysis indicated in a series circuit, working fluids with high critical temperatures such as isopentane are more favorable to be used. The working fluids with low critical temperatures, such as R227ea, are favored in parallel circuits and power generation under the heat source temperature below 450 K. The author investigated a small-scale solar-powered regenerative ORC system using six different refrigerants. The first and second law analysis suggested that R600 and R600a have the best performance under the temperature ranges from 70to 120°C [31]. Wang et al. [33] report a study to compare the performance of 10 kW net power output ORC system using different working fluids for engine exhaust heat recovery. Results indicate R11, R141b, R113, and R123 manifest slightly higher thermodynamic performances than other working fluids [33]. The system performance study of a geothermal ORC system using 31 pure working fluids has been conducted by Saleh et al. [34]. The maximum thermal efficiency is 0.13 with n-butane as working fluid under 120°C heat source temperature [34]. There is no working fluid can be recognized as the best to be used in any ORC systems. The section of optimal working fluid needs to consider the system thermodynamic performance, the economics of the system, designed system parameters such as maximum and minimum

temperature and pressure conditions, environmental, and safety aspects.

slope of the vapor saturation curve such as R134a.

**Figure 5.** Three types of ORC working fluids: dry, isentropic, and wet.

#### *2.2.2. Organic Rankine cycle (OCR)*

As mentioned before, steam Rankine cycle requires very high heat source temperature. The Organic Rankine Cycles have been widely investigated since the 1880s. Instead of using water in Rankine cycle, the Organic Rankine Cycles employ organic working fluids such as refrigerants and hydrocarbons to recover the low-grade heat from biomass power plant, geothermal power and solar ponds [32]. The selection of working fluid plays a key role in ORC performance [33–36].

The working fluids used in Organic Rankine Cycle can be classified as wet, dry and isentropic types, who have different slopes of the vapor saturation curves in the *T-s* diagram as shown

**Figure 4.** Schematic diagram of steam Rankine cycle.

The Development and Application of Organic Rankine Cycle for Vehicle Waste Heat Recovery http://dx.doi.org/10.5772/intechopen.78401 133

**Figure 5.** Three types of ORC working fluids: dry, isentropic, and wet.

**2.2. Working principle of Rankine-based power generation systems**

Steam Rankine cycle has been widely employed in large-scale power plants in the industry. This technology has been recognized as the most popular energy conversion systems, which mainly consists of four components, a pump, an evaporator, a turbine, and a condenser shown in **Figure 4**. The working principle of steam Rankine cycle can be described as follows. The liquid-phase water is first compressed to high-pressure state and flows into the evaporator, where the heat is provided from the heat sources to change the water from the liquid phase into the gas phase. The high-temperature and high-pressure steam then flow through an expansion machine where the power can be retrieved or converted into electricity. In the final step, the condenser

rejects the heat from the expander steam and condenses the steam into the liquid phase.

Rankine cycle applies water as the working fluid, which has the advantages of high specific heat capacity, broad ranges of working conditions, non-toxic, and safe to use and environmentally friendly. However, steam Rankine system requires very high driven temperature in order to keep the steam in the gas phase at the exit of the expander. Because the exiting of liquid phase of fluid requires being prevented otherwise the blades of the turbine will be gradually damaged resulting in the reduction of lifetime and decrease of the expander efficiency [31].

As mentioned before, steam Rankine cycle requires very high heat source temperature. The Organic Rankine Cycles have been widely investigated since the 1880s. Instead of using water in Rankine cycle, the Organic Rankine Cycles employ organic working fluids such as refrigerants and hydrocarbons to recover the low-grade heat from biomass power plant, geothermal power and solar ponds [32]. The selection of working fluid plays a key role in ORC perfor-

The working fluids used in Organic Rankine Cycle can be classified as wet, dry and isentropic types, who have different slopes of the vapor saturation curves in the *T-s* diagram as shown

*2.2.1. Rankine cycle*

132 Organic Rankine Cycle Technology for Heat Recovery

*2.2.2. Organic Rankine cycle (OCR)*

**Figure 4.** Schematic diagram of steam Rankine cycle.

mance [33–36].

in **Figure 5**. The wet fluids such as R717 have a negative slope of the vapor saturation curve. On the other hand, the dry fluids have a positive slope. The isentropic fluids have a vertical slope of the vapor saturation curve such as R134a.

A wrong choice of working fluid could lead to a low-efficient and expensive plant of ORC system. Tchanche et al. [37] assessed the thermodynamic and environmental properties of 20 different fluids for solar Organic Rankine Cycle by comparing the system efficiency, irreversibility, flow rate, pressure ratio, toxicity, flammability, ozone depletion potential (ODP), and global warming potential (GWP). The influence of fluid properties on an ORC and a supercritical Rankine cycle with 35 different working fluids was assessed by Chen et al. [36] considering the latent heat, density, specific heat, and the effectiveness of superheating. An exergy-based study of fluid selection for geothermal generated ORC system was conducted by Heberle et al. [38]. The exergy analysis indicated in a series circuit, working fluids with high critical temperatures such as isopentane are more favorable to be used. The working fluids with low critical temperatures, such as R227ea, are favored in parallel circuits and power generation under the heat source temperature below 450 K. The author investigated a small-scale solar-powered regenerative ORC system using six different refrigerants. The first and second law analysis suggested that R600 and R600a have the best performance under the temperature ranges from 70to 120°C [31]. Wang et al. [33] report a study to compare the performance of 10 kW net power output ORC system using different working fluids for engine exhaust heat recovery. Results indicate R11, R141b, R113, and R123 manifest slightly higher thermodynamic performances than other working fluids [33]. The system performance study of a geothermal ORC system using 31 pure working fluids has been conducted by Saleh et al. [34]. The maximum thermal efficiency is 0.13 with n-butane as working fluid under 120°C heat source temperature [34]. There is no working fluid can be recognized as the best to be used in any ORC systems. The section of optimal working fluid needs to consider the system thermodynamic performance, the economics of the system, designed system parameters such as maximum and minimum temperature and pressure conditions, environmental, and safety aspects.

#### **2.3. Expander candidates**

The expansion machines can be divided into two types: turbine machine using the kinetic energy of the working fluid to drive the expander and positive displace expander producing power by changing the volume of working chamber.

was directly connected to a high-speed generator to produce electricity and results indicated the maximum cycle efficiency, the isentropic turbine efficiency, and electricity power obtained from the testing rig is 5.22%, 78.7%, and 32.7 kW, respectively [42]. Pei et al. [47, 48] carried out an experimental investigation on a 1–2 kW ORC system using a special designed and constructed radial flow turbine. The reported study achieves the isentropic efficiency of the radial flow turbine at 65–68% with the rotational speed around 20,000–40,000 using R123 as the organic working fluid in the ORC system [46, 47]. Compared with positive displacement expander, turbines are easier to be designed with relatively less required parts. A single stage turbine only requires two bearings to be mounted to the generator on the shaft. Furthermore, there is no contact seal existing in the turbines, which means no lubrication oil is necessary to be adapted to the system. The application of turbine for small-scale application is still not successful because the turbine is designed under rather low-expansion ratios and high-volume flows. The rotational speed of conventional turbines ranges from 10,000 to 100, 000 rpm because of the physical design of this type of expansion machine, which results to a limited or hard sourcing of proper generator for electricity production. One of the solutions to adapt the turbine machine directly with the generator is to use a high-speed generator, which will lead to high initial cost and increase the overall cost of electricity generation system. The other method to obtain the mechanical work from the turbine and convert it into electricity is by using gear. This method can effectively solve the high initial cost of the system but will require larger space for the turbine unit and reduce the efficiency of the turbine machine due to mechanical losses in the gear. Furthermore, the availability of small-scale turbine machine is still limited. The currently used radial flow turbines in small-scale power generation system are either from specially designed by the researcher or

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modified from a conventional turbine from an automotive turbocharger.

Different from the working principle turbine machines, positive displacement expanders use the expansion power by changing the volume inside the expansion chambers, which can also be named volumetric expanders. The most commonly used positive displacement expanders include piston type expander, screw expander, and scroll expander and vane expander. The positive displacement expanders can be classified into two types reciprocating piston expanders and rotary expanders. Screw expander, scroll expander, and vane expander are three main

The piston type of machines attracts extensive intentions since it was invented and has been widely applied in different areas to meet various requirements such as the most commonly used as an Internal Combustion Engine. In the past 30 years, piston expander has been adopted and developed as the expander into steam Rankine system integrating with the internal combustion engine to recover the exhaust energy [4]. The piston type of expander can be designed and constructed with one valve version and two valve version in order to allow the expansion process starting and ending inside the piston volume chamber. The working principle of these two types of reciprocating piston expanders is illustrated in **Figure 7**. Piston type of expansion machine requires precisely controlled methods for the intake and exhaust valves, which will result to the requirement of a complex control system although this type of expander can potentially reach very high-expansion efficiency [50]. Moreover, piston

*2.3.2. Positive displacement expanders*

types of rotary expanders.

#### *2.3.1. Turbines*

Turbines have been widely applied as the expansion machine to replace the piston type of expander in steam Rankine cycle since the nineteenth century and have been acknowledged as the optimal expander for large-scale power plants. It consumes the internal energy of vapor into kinetic energy, which results the velocity of the flow are relatively high but the pressure and forces between the supply and exhaust point are rather small [39]. The mechanical power is then been obtained from the shaft of the turbine by turning the rotor blades when the highvelocity fluid passes through the turbine. There are mainly two types of turbines: axial flow turbines and radial flow turbines [40]. The axial flow turbines are driven by the flow in the parallel direction to the shaft, while the radial flow turbines are rotated by the flow traveling through the hub to the tipoff the turbine as indicated in **Figure 6**. However, the application of turbines for small-scale power generation system has not been widely accepted as the best expansion machine, especially in the power plants lower than 100 kW. Radial flow turbines are one of the exceptions, which have been recently used for small-scale application in Organic Rankine Cycle (ORC) [42–47]. Kang reports the design and experimental investigation of an ORC using R245fa as the working fluid and radial flow turbine as the expansion machine [42]. The radial turbine

**Figure 6.** Working principle of turbine machines. (a) Axial flow turbine and (b) radial flow turbine [41].

was directly connected to a high-speed generator to produce electricity and results indicated the maximum cycle efficiency, the isentropic turbine efficiency, and electricity power obtained from the testing rig is 5.22%, 78.7%, and 32.7 kW, respectively [42]. Pei et al. [47, 48] carried out an experimental investigation on a 1–2 kW ORC system using a special designed and constructed radial flow turbine. The reported study achieves the isentropic efficiency of the radial flow turbine at 65–68% with the rotational speed around 20,000–40,000 using R123 as the organic working fluid in the ORC system [46, 47]. Compared with positive displacement expander, turbines are easier to be designed with relatively less required parts. A single stage turbine only requires two bearings to be mounted to the generator on the shaft. Furthermore, there is no contact seal existing in the turbines, which means no lubrication oil is necessary to be adapted to the system. The application of turbine for small-scale application is still not successful because the turbine is designed under rather low-expansion ratios and high-volume flows. The rotational speed of conventional turbines ranges from 10,000 to 100, 000 rpm because of the physical design of this type of expansion machine, which results to a limited or hard sourcing of proper generator for electricity production. One of the solutions to adapt the turbine machine directly with the generator is to use a high-speed generator, which will lead to high initial cost and increase the overall cost of electricity generation system. The other method to obtain the mechanical work from the turbine and convert it into electricity is by using gear. This method can effectively solve the high initial cost of the system but will require larger space for the turbine unit and reduce the efficiency of the turbine machine due to mechanical losses in the gear. Furthermore, the availability of small-scale turbine machine is still limited. The currently used radial flow turbines in small-scale power generation system are either from specially designed by the researcher or modified from a conventional turbine from an automotive turbocharger.

#### *2.3.2. Positive displacement expanders*

**Figure 6.** Working principle of turbine machines. (a) Axial flow turbine and (b) radial flow turbine [41].

The expansion machines can be divided into two types: turbine machine using the kinetic energy of the working fluid to drive the expander and positive displace expander producing

Turbines have been widely applied as the expansion machine to replace the piston type of expander in steam Rankine cycle since the nineteenth century and have been acknowledged as the optimal expander for large-scale power plants. It consumes the internal energy of vapor into kinetic energy, which results the velocity of the flow are relatively high but the pressure and forces between the supply and exhaust point are rather small [39]. The mechanical power is then been obtained from the shaft of the turbine by turning the rotor blades when the highvelocity fluid passes through the turbine. There are mainly two types of turbines: axial flow turbines and radial flow turbines [40]. The axial flow turbines are driven by the flow in the parallel direction to the shaft, while the radial flow turbines are rotated by the flow traveling through the hub to the tipoff the turbine as indicated in **Figure 6**. However, the application of turbines for small-scale power generation system has not been widely accepted as the best expansion machine, especially in the power plants lower than 100 kW. Radial flow turbines are one of the exceptions, which have been recently used for small-scale application in Organic Rankine Cycle (ORC) [42–47]. Kang reports the design and experimental investigation of an ORC using R245fa as the working fluid and radial flow turbine as the expansion machine [42]. The radial turbine

**2.3. Expander candidates**

134 Organic Rankine Cycle Technology for Heat Recovery

*2.3.1. Turbines*

power by changing the volume of working chamber.

Different from the working principle turbine machines, positive displacement expanders use the expansion power by changing the volume inside the expansion chambers, which can also be named volumetric expanders. The most commonly used positive displacement expanders include piston type expander, screw expander, and scroll expander and vane expander. The positive displacement expanders can be classified into two types reciprocating piston expanders and rotary expanders. Screw expander, scroll expander, and vane expander are three main types of rotary expanders.

The piston type of machines attracts extensive intentions since it was invented and has been widely applied in different areas to meet various requirements such as the most commonly used as an Internal Combustion Engine. In the past 30 years, piston expander has been adopted and developed as the expander into steam Rankine system integrating with the internal combustion engine to recover the exhaust energy [4]. The piston type of expander can be designed and constructed with one valve version and two valve version in order to allow the expansion process starting and ending inside the piston volume chamber. The working principle of these two types of reciprocating piston expanders is illustrated in **Figure 7**. Piston type of expansion machine requires precisely controlled methods for the intake and exhaust valves, which will result to the requirement of a complex control system although this type of expander can potentially reach very high-expansion efficiency [50]. Moreover, piston

no commercially available product under the power output lower than 10 kW from the market as reported by Ian et al. [55]. Because small size of screw expander needs extremely precise machining requirements to make the rotors and internal leakages of small size screw expander

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Scroll type of machine was first developed by a French inventor in 1905 and then the scroll machine starts to attract attention to be applied in Air condition system as a compressor to produce refrigeration since the mid of 1980s [57]. The most of the available scroll expanders from the market are modified from scroll compressor by swapping the inlet and outlet ports to change the device working mode from compressor to the expander. Scroll device is relatively simple equipment, which mainly includes two scrolls. The scroll expander has the advantages of little vibration, low-noise, a limited number of moving parts, broad availability, high-reliability and low initial cost [58, 59]. Scroll device has two scrolls and one of the scrolls is fixed on the shell, which is called situational scroll, while the other scroll orbiting eccentrically without rotating is named orbiting scroll. During the expansion process, high-pressure vapor enters and expands centrally of two scrolls pushing the orbiting scroll to start orbit as illustrated in **Figure 9**. The mechanical work can be continually obtained from the orbiting scroll through the shaft. Likewise the other positive displacement expanders, scroll expander has a fixed built-in expansion ratio. The optimal performance of scroll expander can be obtained when the specific volume ratio of the designed system equal to the built-in expansion ratio. Quoilin et al. pointed out the losses appearing when scroll type of expansion machine is working under and over expansion processes [9]. For example, 1 kW

are relatively higher than that of the large-scale device [51, 56].

**Figure 9.** Expansion process of the scroll device under different crank angles [60].

**Figure 7.** Working principle of reciprocating piston expander. (a) Single valve piston expander and (b) two valve piston expander [49].

expander requires a lot of bearings, a great number of moving parts, and balancing setting up, which results in a relatively complex and costly system.

Screw expander is composed of two meshing helical rotors a male and a female rotor, which requires at least four bearings for the two rotors as shown in **Figure 8**. This type of expansion machine has been widely applied in steam Rankine cycle plants for geothermal waste heat recovery system [52]. Lubrication oil is commonly used in the screw machine to seal the expanded working fluid inside the expansion chamber, which can effectively reduce the internal leakage losses during the expansion process. Screw expander has a relatively high rotational speed in positive displacement expanders and the rotation speed of this machine can reach as high as 6000 rpm [52]. The electricity production from screw expander, therefore, requires a specially designed high-speed generator or adding a gearbox to convert the mechanical power from the screw machine into electricity. This type of expansion devices has the advantages such as medium internal frictions, medium leakage losses, low vibration noise, wide ranges of power output, and long lifetime. The power produced from this expansion machine as reported by previous researchers ranging from 1.5 kW to 1 MW with the expansion ratio of 2–8 [53]. Leibowitz et al. developed an ORC power generation system using screw expander in a demonstration unit to cost-effectively recover the waste heat into power. Results indicated that screw expander is a good candidate expansion machine for the ORC system with the power output at 20 kW with installation cost in the range of \$1500 –\$2000/kWe [54]. However, there is

**Figure 8.** Working principle of screw expander [51].

no commercially available product under the power output lower than 10 kW from the market as reported by Ian et al. [55]. Because small size of screw expander needs extremely precise machining requirements to make the rotors and internal leakages of small size screw expander are relatively higher than that of the large-scale device [51, 56].

Scroll type of machine was first developed by a French inventor in 1905 and then the scroll machine starts to attract attention to be applied in Air condition system as a compressor to produce refrigeration since the mid of 1980s [57]. The most of the available scroll expanders from the market are modified from scroll compressor by swapping the inlet and outlet ports to change the device working mode from compressor to the expander. Scroll device is relatively simple equipment, which mainly includes two scrolls. The scroll expander has the advantages of little vibration, low-noise, a limited number of moving parts, broad availability, high-reliability and low initial cost [58, 59]. Scroll device has two scrolls and one of the scrolls is fixed on the shell, which is called situational scroll, while the other scroll orbiting eccentrically without rotating is named orbiting scroll. During the expansion process, high-pressure vapor enters and expands centrally of two scrolls pushing the orbiting scroll to start orbit as illustrated in **Figure 9**. The mechanical work can be continually obtained from the orbiting scroll through the shaft. Likewise the other positive displacement expanders, scroll expander has a fixed built-in expansion ratio. The optimal performance of scroll expander can be obtained when the specific volume ratio of the designed system equal to the built-in expansion ratio. Quoilin et al. pointed out the losses appearing when scroll type of expansion machine is working under and over expansion processes [9]. For example, 1 kW

**Figure 9.** Expansion process of the scroll device under different crank angles [60].

**Figure 8.** Working principle of screw expander [51].

expander requires a lot of bearings, a great number of moving parts, and balancing setting

**Figure 7.** Working principle of reciprocating piston expander. (a) Single valve piston expander and (b) two valve piston

Screw expander is composed of two meshing helical rotors a male and a female rotor, which requires at least four bearings for the two rotors as shown in **Figure 8**. This type of expansion machine has been widely applied in steam Rankine cycle plants for geothermal waste heat recovery system [52]. Lubrication oil is commonly used in the screw machine to seal the expanded working fluid inside the expansion chamber, which can effectively reduce the internal leakage losses during the expansion process. Screw expander has a relatively high rotational speed in positive displacement expanders and the rotation speed of this machine can reach as high as 6000 rpm [52]. The electricity production from screw expander, therefore, requires a specially designed high-speed generator or adding a gearbox to convert the mechanical power from the screw machine into electricity. This type of expansion devices has the advantages such as medium internal frictions, medium leakage losses, low vibration noise, wide ranges of power output, and long lifetime. The power produced from this expansion machine as reported by previous researchers ranging from 1.5 kW to 1 MW with the expansion ratio of 2–8 [53]. Leibowitz et al. developed an ORC power generation system using screw expander in a demonstration unit to cost-effectively recover the waste heat into power. Results indicated that screw expander is a good candidate expansion machine for the ORC system with the power output at 20 kW with installation cost in the range of \$1500 –\$2000/kWe [54]. However, there is

up, which results in a relatively complex and costly system.

expander [49].

136 Organic Rankine Cycle Technology for Heat Recovery

oil-free scroll expander was used in an ORC system to recover the exhaust gas heat from a 30 kW gas turbine as reported by June et al. [61]. The ORC system used a zeotropic mixture with 48.5% R245fa and 51.5% R365mfc as the working fluid and the experimental results indicated the overall efficiency of the ORC system was about 3.9% [61]. The scroll expander was operated in the over-expansion region, which can therefore only achieve the efficiency of 28.4% under the tested condition. The overall ORC efficiency can be much higher than 3.9% if the expansion machine has been operated within the optimal conditions [61]. A prototype of ORC system using an open-drive oil-free scroll expander with R123 as the working fluid was experimentally investigated by Lemort et al. [62]. Results indicated the maximum isentropic efficiency of the scroll expander could be as high as 68% [62]. Muhammad et al. [63] reported the experimental study of a small-scale ORC system recovering the heat from hot steam. An oil-free scroll expander was used in the system to produce electrical power. Results show the maximum electrical power from the system was 1.016 kW when the system thermal efficiency was 5.64% and the isentropic efficiency of the expander was 58.3% [63]. During the experiment, the maximum ORC thermal efficiency was achieved at 5.75% and the scroll expander achieved the maximum isentropic efficiency as high as 77.74% [63]. A hermetic type refrigerant scroll compressor with built-in volume ratio at 3.24 was modified as an expander and used in an ORC system as reported by Yang et al. [64]. The experimental results indicated the maximum shaft power was 2.64 kW when the ORC thermal efficiency was 5.92% [64]. The majority of scroll expanders available from the market are modified from scroll compressors, which are not designed to be used for expansion applications. A separate lubrication system is normally required to lubricate the contact seals of two scrolls and reduce the radial leakage. The other function of the oil is to seal the working fluid inside the expansion chambers during the expansion process to prevent and reduce the flank leakage of the scroll type machine.

**2.4. Cycle investigations**

(BSFC) can be reduced by a maximum of 5.0% [24].

**Figure 10.** Working principle of vane-type expander [56].

Due to the limited space, the demand of high-power to weight ratio for ORC system and complicated control strategies for vehicle application, the ORC systems are still under technical development and testing stages. The current commercialization status of ORC technology for engine waste heat recovery is mainly for stationary power generation applications because of their desirable stable operating profiles [11]. A representative study on ORC system recovering exhaust energy from a stationary compressed natural gas (CNG) engine was reported by Song et al. [24]. The results showed the electric efficiency of the CNG engine could be potentially improved by a maximum 6.0% and the overall engine brake specific fuel consumption

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The two primary heat sources from ICE systems are engine cooling system and exhaust gases, which almost contain 60–70% of the fuel energy. Engine coolant energy is normally recognized as a heat source that is not worth to recover because the coolant temperature is about 80–100°C. However, the coolant energy contains about 30% of the fuel energy. The effective utilization of engine coolant energy for ORC waste heat recovery of the ICE could potentially improve the overall system efficiency and reduce the pay-back period of the overall cost with a properly designed system [9, 10]. A typical single-loop ORC system recovering both engine coolant and exhaust energy can be shown in **Figure 11**. A recuperator can be used to recover unused heat at the exit of expansion machine to preheat the working. The coolant energy can either be used as preheating source or main heat source for ORC systems. Only part of the coolant energy can be recovered if it was used as preheating source. For example, a study conducted by Yu et al. [69] investigated the potential of using engine coolant energy as ORC preheating source. The simulation results indicated there is around 75% exhaust heat and 9.5% coolant energy can be recovered from a diesel engine [69]. Tian et al. [70] deeply investigated the effects of fluids and parameters of the ORC system for engine exhaust heat recovery. The performance ORC system using 20 working fluids (boiling point range from −51.6 to 32.05°C) was studied to evaluate the

Vane expanders have the advantages of simple construction, easy manufacture, low-cost, self-start under load and smooth torque production [35, 65]. The expansion process happens between the cylinder wall and the sliding vanes. When the high-pressure working fluid flows into the inlet port and fills chamber A, the spinning power from the rotor can be gathered as illustrated in **Figure 10**. The pressure differences among the chambers resulted by expansion process driver the rotor. Qiu et al. [56, 66] investigated a vane expander in a biomass fire CHP system with ORC and achieved the isentropic efficiency of 54.5% at the speed of 824 RPM (mechanical work of 1.552 kW). The electricity generated by the vane expander was 792 W, which lighted seventeen 50 W bulbs. The efficiencies of several vane expanders using different working fluids at different working temperatures and pressures were summarized by Aoun [67]. Results showed that the maximum efficiency of 80% was achieved by a vane expander using R-11 at 800 RPM. The rotational speed of vane type of expanders is relatively lower than other expansion machines with commonly from 1500 to 3000 rpm, which can be directly installed to the generator without requiring of gear box [35]. However, the average isentropic efficiency of vane expanders is with the range of 15–55%, which is not that competitive compared with other volumetric expansion machines, as reported by Muhammad et al. [53]. Moreover, this type of expander requires a lubrication system to lubricate the contact surface of the rotor and vane. The existing of lubricate oil will contaminate the working fluid and flow back to the system.

**Figure 10.** Working principle of vane-type expander [56].

#### **2.4. Cycle investigations**

oil-free scroll expander was used in an ORC system to recover the exhaust gas heat from a 30 kW gas turbine as reported by June et al. [61]. The ORC system used a zeotropic mixture with 48.5% R245fa and 51.5% R365mfc as the working fluid and the experimental results indicated the overall efficiency of the ORC system was about 3.9% [61]. The scroll expander was operated in the over-expansion region, which can therefore only achieve the efficiency of 28.4% under the tested condition. The overall ORC efficiency can be much higher than 3.9% if the expansion machine has been operated within the optimal conditions [61]. A prototype of ORC system using an open-drive oil-free scroll expander with R123 as the working fluid was experimentally investigated by Lemort et al. [62]. Results indicated the maximum isentropic efficiency of the scroll expander could be as high as 68% [62]. Muhammad et al. [63] reported the experimental study of a small-scale ORC system recovering the heat from hot steam. An oil-free scroll expander was used in the system to produce electrical power. Results show the maximum electrical power from the system was 1.016 kW when the system thermal efficiency was 5.64% and the isentropic efficiency of the expander was 58.3% [63]. During the experiment, the maximum ORC thermal efficiency was achieved at 5.75% and the scroll expander achieved the maximum isentropic efficiency as high as 77.74% [63]. A hermetic type refrigerant scroll compressor with built-in volume ratio at 3.24 was modified as an expander and used in an ORC system as reported by Yang et al. [64]. The experimental results indicated the maximum shaft power was 2.64 kW when the ORC thermal efficiency was 5.92% [64]. The majority of scroll expanders available from the market are modified from scroll compressors, which are not designed to be used for expansion applications. A separate lubrication system is normally required to lubricate the contact seals of two scrolls and reduce the radial leakage. The other function of the oil is to seal the working fluid inside the expansion chambers during the expansion process to prevent and reduce the flank leakage of the scroll type machine.

138 Organic Rankine Cycle Technology for Heat Recovery

Vane expanders have the advantages of simple construction, easy manufacture, low-cost, self-start under load and smooth torque production [35, 65]. The expansion process happens between the cylinder wall and the sliding vanes. When the high-pressure working fluid flows into the inlet port and fills chamber A, the spinning power from the rotor can be gathered as illustrated in **Figure 10**. The pressure differences among the chambers resulted by expansion process driver the rotor. Qiu et al. [56, 66] investigated a vane expander in a biomass fire CHP system with ORC and achieved the isentropic efficiency of 54.5% at the speed of 824 RPM (mechanical work of 1.552 kW). The electricity generated by the vane expander was 792 W, which lighted seventeen 50 W bulbs. The efficiencies of several vane expanders using different working fluids at different working temperatures and pressures were summarized by Aoun [67]. Results showed that the maximum efficiency of 80% was achieved by a vane expander using R-11 at 800 RPM. The rotational speed of vane type of expanders is relatively lower than other expansion machines with commonly from 1500 to 3000 rpm, which can be directly installed to the generator without requiring of gear box [35]. However, the average isentropic efficiency of vane expanders is with the range of 15–55%, which is not that competitive compared with other volumetric expansion machines, as reported by Muhammad et al. [53]. Moreover, this type of expander requires a lubrication system to lubricate the contact surface of the rotor and vane. The existing of lubricate oil will contaminate the working fluid

and flow back to the system.

Due to the limited space, the demand of high-power to weight ratio for ORC system and complicated control strategies for vehicle application, the ORC systems are still under technical development and testing stages. The current commercialization status of ORC technology for engine waste heat recovery is mainly for stationary power generation applications because of their desirable stable operating profiles [11]. A representative study on ORC system recovering exhaust energy from a stationary compressed natural gas (CNG) engine was reported by Song et al. [24]. The results showed the electric efficiency of the CNG engine could be potentially improved by a maximum 6.0% and the overall engine brake specific fuel consumption (BSFC) can be reduced by a maximum of 5.0% [24].

The two primary heat sources from ICE systems are engine cooling system and exhaust gases, which almost contain 60–70% of the fuel energy. Engine coolant energy is normally recognized as a heat source that is not worth to recover because the coolant temperature is about 80–100°C. However, the coolant energy contains about 30% of the fuel energy. The effective utilization of engine coolant energy for ORC waste heat recovery of the ICE could potentially improve the overall system efficiency and reduce the pay-back period of the overall cost with a properly designed system [9, 10]. A typical single-loop ORC system recovering both engine coolant and exhaust energy can be shown in **Figure 11**. A recuperator can be used to recover unused heat at the exit of expansion machine to preheat the working. The coolant energy can either be used as preheating source or main heat source for ORC systems. Only part of the coolant energy can be recovered if it was used as preheating source. For example, a study conducted by Yu et al. [69] investigated the potential of using engine coolant energy as ORC preheating source. The simulation results indicated there is around 75% exhaust heat and 9.5% coolant energy can be recovered from a diesel engine [69]. Tian et al. [70] deeply investigated the effects of fluids and parameters of the ORC system for engine exhaust heat recovery. The performance ORC system using 20 working fluids (boiling point range from −51.6 to 32.05°C) was studied to evaluate the

was reported by Shu et al. [74], who investigated the influence of using different working fluids. The high-temperature loop adopted water to recovery the exhaust energy and six working fluids have been selected for the low-temperature [74]. The dual-loop ORC system can achieve the maximum overall exergy efficiency as high as 55.05% using R1234yf as working fluid [74]. The dual-loop ORC requires two sets of ORC system components and advanced controlling strategies to balance the different heat sources, which will increase the capital cost

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The power output from the ORC system can be either mechanical or electrical. As introduced in the previous section, the expansion machines can be divided into two types turbine machine using the kinetic energy of the working fluid to drive the expander and positively displace expander producing power by changing the volume of working chamber. When the mechanical configuration is used, the expander shaft is connected to the engine drive belt or a gear. Alternatively, an alternator is used to convert the mechanical work from the ORC expander to electricity. The generated electricity can be used to power the vehicle battery or supply auxiliary utilities. One of the main drawbacks of the solution is the efficiency of avail-

The designed evaporation and condensation temperature determines the overall efficiency of ORC system. A higher temperature difference between evaporation and condensation can result in a higher overall ORC efficiency. The engine front radiator is therefore required to reject high-load of heat in order to maintain the low condensation temperature. The limited space for vehicle application restricts the size of engine cooling system. An electrically driven cooling fan is generally not recommended to achieve low condensation temperature because

Another main technical constraint is the dynamic/transient heat sources. In order to maintain the ORC system within the optimal operating region, the control of pump speed, and expander speed are required. Therefore, the complex control strategies are critical to being

of the system and result in high payback period.

**Figure 12.** Dual-loop ORC system (a) schematic diagram and (b) *T-s* diagram [26, 75].

able vehicle alternators, which is around 50–60% [5, 9].

it would sharply reduce the overall system performance.

**2.5. Technical barriers**

**Figure 11.** Single-loop ORC for engine coolant and exhaust recovery [68].

cycle parameters such as the overall thermal efficiency, expansion ratio, effective power output and electricity production cost [70]. R141b, R123, and R245fa were identified as the optimal working fluids. The highest thermal efficiency of these three working fluids ranges from 16.6% to 13.3% with the electricity production cost various from 0.30 to 0.35 €/kWh [70]. A simulation study of an ORC system for diesel engine exhaust heat recovery was reported by Zhao et al. [71]. Results indicated the BSFC reduction and the overall thermal efficiency of the engine integrated with ORC unit is 3.61 g/(kWh)–0.66% [71]. Shu et al. [72] recommended to use alkane-based working fluids for diesel engine exhaust heat recovery from the technical and economic point of view [72].

Another potential approach for engine coolant and exhaust recovery is using dual-loop ORC, which adopts two separately ORC systems to regenerate multi-heat sources from ICE [28, 73, 74]. The schematic system diagram and *T-s* diagram of dual loop ORC system can be found in **Figure 12**. Wang et al. [28, 73] conducted the study on a dual loop ORC to evaluate the performance of a gasoline engine and a light-duty diesel engine. The dual loop ORC system contains a high-temperature loop recovering engine exhaust heat and a low-temperature loop for coolant heat recovery. The proposed concept has the potential to comprehensively reuse all the recoverable heat from engine coolant and exhaust sources [73]. The investigations of using dual loop ORC system were also conducted on a selected gasoline engine and a diesel engine. For the selected gasoline engine, the results showed the dual loop ORC system can effectively improve the overall system efficiency by 3–6% throughout the engine operating region [73]. When the system was used on a light-duty diesel engine, the evaluation results indicated the thermal efficiency can be improved by 8% compared to that of the original engine [28]. At the engine rated power condition, the power output of the combined system can be improved by 26.63% [28]. Further study of the dual-loop ORC for engine coolant and exhaust recovery The Development and Application of Organic Rankine Cycle for Vehicle Waste Heat Recovery http://dx.doi.org/10.5772/intechopen.78401 141

**Figure 12.** Dual-loop ORC system (a) schematic diagram and (b) *T-s* diagram [26, 75].

was reported by Shu et al. [74], who investigated the influence of using different working fluids. The high-temperature loop adopted water to recovery the exhaust energy and six working fluids have been selected for the low-temperature [74]. The dual-loop ORC system can achieve the maximum overall exergy efficiency as high as 55.05% using R1234yf as working fluid [74]. The dual-loop ORC requires two sets of ORC system components and advanced controlling strategies to balance the different heat sources, which will increase the capital cost of the system and result in high payback period.

#### **2.5. Technical barriers**

cycle parameters such as the overall thermal efficiency, expansion ratio, effective power output and electricity production cost [70]. R141b, R123, and R245fa were identified as the optimal working fluids. The highest thermal efficiency of these three working fluids ranges from 16.6% to 13.3% with the electricity production cost various from 0.30 to 0.35 €/kWh [70]. A simulation study of an ORC system for diesel engine exhaust heat recovery was reported by Zhao et al. [71]. Results indicated the BSFC reduction and the overall thermal efficiency of the engine integrated with ORC unit is 3.61 g/(kWh)–0.66% [71]. Shu et al. [72] recommended to use alkane-based working fluids for diesel engine exhaust heat recovery from the technical and economic point of view [72]. Another potential approach for engine coolant and exhaust recovery is using dual-loop ORC, which adopts two separately ORC systems to regenerate multi-heat sources from ICE [28, 73, 74]. The schematic system diagram and *T-s* diagram of dual loop ORC system can be found in **Figure 12**. Wang et al. [28, 73] conducted the study on a dual loop ORC to evaluate the performance of a gasoline engine and a light-duty diesel engine. The dual loop ORC system contains a high-temperature loop recovering engine exhaust heat and a low-temperature loop for coolant heat recovery. The proposed concept has the potential to comprehensively reuse all the recoverable heat from engine coolant and exhaust sources [73]. The investigations of using dual loop ORC system were also conducted on a selected gasoline engine and a diesel engine. For the selected gasoline engine, the results showed the dual loop ORC system can effectively improve the overall system efficiency by 3–6% throughout the engine operating region [73]. When the system was used on a light-duty diesel engine, the evaluation results indicated the thermal efficiency can be improved by 8% compared to that of the original engine [28]. At the engine rated power condition, the power output of the combined system can be improved by 26.63% [28]. Further study of the dual-loop ORC for engine coolant and exhaust recovery

**Figure 11.** Single-loop ORC for engine coolant and exhaust recovery [68].

140 Organic Rankine Cycle Technology for Heat Recovery

The power output from the ORC system can be either mechanical or electrical. As introduced in the previous section, the expansion machines can be divided into two types turbine machine using the kinetic energy of the working fluid to drive the expander and positively displace expander producing power by changing the volume of working chamber. When the mechanical configuration is used, the expander shaft is connected to the engine drive belt or a gear. Alternatively, an alternator is used to convert the mechanical work from the ORC expander to electricity. The generated electricity can be used to power the vehicle battery or supply auxiliary utilities. One of the main drawbacks of the solution is the efficiency of available vehicle alternators, which is around 50–60% [5, 9].

The designed evaporation and condensation temperature determines the overall efficiency of ORC system. A higher temperature difference between evaporation and condensation can result in a higher overall ORC efficiency. The engine front radiator is therefore required to reject high-load of heat in order to maintain the low condensation temperature. The limited space for vehicle application restricts the size of engine cooling system. An electrically driven cooling fan is generally not recommended to achieve low condensation temperature because it would sharply reduce the overall system performance.

Another main technical constraint is the dynamic/transient heat sources. In order to maintain the ORC system within the optimal operating region, the control of pump speed, and expander speed are required. Therefore, the complex control strategies are critical to being developed or advanced ORC systems should be investigated. Using variable speed pump, adding control valves and integrating thermal energy storage system to manage fluctuation waste heat are some common strategies as reported by Manuel et al. [76].

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## **3. Conclusions**

Vehicle waste heat recovery technologies are currently under enormous interests for the purpose of reducing emissions and improving overall efficiency. Organic Rankine Cycle is one of the best solutions to recover engine waste heat into mechanical or electrical power. Key conclusions of this chapter can be summarized as follows.

It is critical to characterize the recoverable heat from the engine before designing the ORC system. A broad range of working fluids are available to be selected but there is no working fluid can be recognized as the best to be used in any ORC systems. A high-efficiency alternator to be coupled with ORC expander is in high-demand in order to promote the application of electrical version engine waste heat recovery system. For vehicle application, a compact system is desirable because of the limitation of space. A well-designed engine thermal management system should be considered. The transient heat source performance is the major technical obstacle to use ORC system for engine waste heat recovery and it can be expected either advanced control strategies or thermal energy storage technology should be used to solve the problem and promote the practical application of the ORC system for the vehicle.

## **Acknowledgements**

The authors would like to thank the supports from EPSRC through (EP/P001173/1)-Centre for Energy Systems Integration, (EP/K503885/1) toward the project- Study of engine waste heat technologies, from NSFC-RS Joint Project under the grant number No. 5151101443 and IE/151256. The support from Cao Guang Biao High Tech Talent Fund, Zhejiang University is also highly acknowledged.

## **Author details**

Yiji Lu1,2\*, Anthony Paul Roskilly1,2 and Xiaoli Yu1

\*Address all correspondence to: luyiji0620@gmail.com

1 Department of Energy Engineering, Zhejiang University, Hangzhou, China

2 Sir Joseph Swan Centre for Energy Research, Newcastle University, Newcastle, United Kingdom

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developed or advanced ORC systems should be investigated. Using variable speed pump, adding control valves and integrating thermal energy storage system to manage fluctuation

Vehicle waste heat recovery technologies are currently under enormous interests for the purpose of reducing emissions and improving overall efficiency. Organic Rankine Cycle is one of the best solutions to recover engine waste heat into mechanical or electrical power. Key

It is critical to characterize the recoverable heat from the engine before designing the ORC system. A broad range of working fluids are available to be selected but there is no working fluid can be recognized as the best to be used in any ORC systems. A high-efficiency alternator to be coupled with ORC expander is in high-demand in order to promote the application of electrical version engine waste heat recovery system. For vehicle application, a compact system is desirable because of the limitation of space. A well-designed engine thermal management system should be considered. The transient heat source performance is the major technical obstacle to use ORC system for engine waste heat recovery and it can be expected either advanced control strategies or thermal energy storage technology should be used to solve the problem and promote the practical application of the ORC

The authors would like to thank the supports from EPSRC through (EP/P001173/1)-Centre for Energy Systems Integration, (EP/K503885/1) toward the project- Study of engine waste heat technologies, from NSFC-RS Joint Project under the grant number No. 5151101443 and IE/151256. The support from Cao Guang Biao High Tech Talent Fund, Zhejiang University is

waste heat are some common strategies as reported by Manuel et al. [76].

conclusions of this chapter can be summarized as follows.

**3. Conclusions**

142 Organic Rankine Cycle Technology for Heat Recovery

system for the vehicle.

**Acknowledgements**

also highly acknowledged.

Yiji Lu1,2\*, Anthony Paul Roskilly1,2 and Xiaoli Yu1

\*Address all correspondence to: luyiji0620@gmail.com

1 Department of Energy Engineering, Zhejiang University, Hangzhou, China

2 Sir Joseph Swan Centre for Energy Research, Newcastle University, Newcastle,

**Author details**

United Kingdom


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**Chapter 8**

**Provisional chapter**

**Organic Rankine Cycle for Recovery of Liquefied**

**Organic Rankine Cycle for Recovery of Liquefied** 

DOI: 10.5772/intechopen.77990

Natural gas (NG) is an environment-friendly energy source. NG is of gas state in the environmental condition and it is liquefied to LNG at temperature of about −162°C for transportation and storage. Electric energy of 292–958 kWh is consumed when one ton of LNG is produced. Before being used, LNG must be regasified to NG again at the receiving site, and this process will release a great deal of energy, which is called cold energy. It's very important to recovery LNG cold energy, which is clean and of high quality. Power generation is a conventional and effective way to utilize LNG cold energy. For the low efficiency of the traditional power generation system with liquefied natural gas (LNG) cold energy utilization, by improving the heat transfer characteristic between the working fluid and LNG, this chapter has proposed a conception of multi-stage condensation Rankine cycle system. Furthermore, the performance of power generation systems will be enhanced with two aspects: improvement of system configuration and optimiza-

**Keywords:** organic Rankine cycle, LNG cold energy, two-stage condensation Rankine

Energy shortage and environmental pollution are two major themes in today's world [1]. More and more attentions are paid to Natural gas (NG) because it is clean and has high calorific value [2, 3], and it is widely consumed all over the world [4]. NG is of gas state in the environmental condition and it is liquefied to LNG at temperature of about −162°C for transportation and storage [5]. Electric energy of 292–958 kWh is consumed when one ton of LNG

> © 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

distribution, and reproduction in any medium, provided the original work is properly cited.

**Natural Gas (LNG) Cold Energy**

**Natural Gas (LNG) Cold Energy**

Additional information is available at the end of the chapter

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.77990

Junjiang Bao

Junjiang Bao

**Abstract**

tion of working fluids.

**1. Introduction**

cycle, zeotropic mixture, system configuration

#### **Organic Rankine Cycle for Recovery of Liquefied Natural Gas (LNG) Cold Energy Organic Rankine Cycle for Recovery of Liquefied Natural Gas (LNG) Cold Energy**

DOI: 10.5772/intechopen.77990

#### Junjiang Bao Junjiang Bao

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.77990

#### **Abstract**

Natural gas (NG) is an environment-friendly energy source. NG is of gas state in the environmental condition and it is liquefied to LNG at temperature of about −162°C for transportation and storage. Electric energy of 292–958 kWh is consumed when one ton of LNG is produced. Before being used, LNG must be regasified to NG again at the receiving site, and this process will release a great deal of energy, which is called cold energy. It's very important to recovery LNG cold energy, which is clean and of high quality. Power generation is a conventional and effective way to utilize LNG cold energy. For the low efficiency of the traditional power generation system with liquefied natural gas (LNG) cold energy utilization, by improving the heat transfer characteristic between the working fluid and LNG, this chapter has proposed a conception of multi-stage condensation Rankine cycle system. Furthermore, the performance of power generation systems will be enhanced with two aspects: improvement of system configuration and optimization of working fluids.

**Keywords:** organic Rankine cycle, LNG cold energy, two-stage condensation Rankine cycle, zeotropic mixture, system configuration

## **1. Introduction**

Energy shortage and environmental pollution are two major themes in today's world [1]. More and more attentions are paid to Natural gas (NG) because it is clean and has high calorific value [2, 3], and it is widely consumed all over the world [4]. NG is of gas state in the environmental condition and it is liquefied to LNG at temperature of about −162°C for transportation and storage [5]. Electric energy of 292–958 kWh is consumed when one ton of LNG

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

is produced [6]. Before being used, LNG must be regasified to NG again at the receiving site, and this process will release a great deal of energy, which is called cold energy [7]. It is very important to recovery LNG cold energy which is clean and of high quality. Usually LNG is heated by sea water or air, so that LNG cold energy is wasted and the sea near the regasification site also is affected [8]. Therefore, the recovery of the LNG cold energy a dual purpose [8].

In this chapter, the performance of power generation systems by LNG cold energy will be enhanced with two aspects: improvement of system configuration and optimization of working fluids. Firstly, the two-stage condensation Rankine cycle is introduced. Based on this, the effect of stage number of condensation process is discussed. Then, the influence of the arrangements for compression process and expansion process is studied. Regarding to the optimization of working fluids, pure working fluids are firstly compared, and then zeotropic mixtures are optimized. Finally, a simultaneous approach to optimize the component and

Organic Rankine Cycle for Recovery of Liquefied Natural Gas (LNG) Cold Energy

http://dx.doi.org/10.5772/intechopen.77990

151

As shown in **Figure 1**, the TCRC system consists of an evaporator, two turbines, two condensers, a mixer, a splitter and two feed pumps. After heated in the evaporator by sea water, working fluid is evaporated to vapor and is divided into two streams in the splitter. The two streams flow into different turbines respectively and are expanded to two different condensation pressures. These two streams transferred heat energy to LNG in two different condensers and cooled to liquid. The two streams are pressurized by two different pumps and mixed in the mixer. The converged stream enters the evaporator again and the new cycle recommences. Except for absorbing the condensation heat from working fluids in two condensers, LNG is further heated to the scheduled temperature in the reheater with sea water. T-s diagram of the TCRC system is plotted in **Figure 2**, and the labeled state points in **Figure 2** is the same as

In order to determine whether the new proposed cycle has a better performance, the novel

system is compared with the conventional methods under the same conditions.

composition of zeotropic mixture is put forward.

**2. Improvement of system configuration**

**2.1. Two-stage condensation Rankine cycle (TCRC)**

that in **Figure 1**.

**Figure 1.** Schematic diagram of the TCRC system.

One of effective ways to utilize LNG cold energy is power generation [9]. The traditional cycles include direct expansion cycle (DE), organic Rankine cycle (ORC) and combined cycle (CC) [10]. Although the simplicity for direct expansion cycle, it has limited applications with low efficiency and high operation pressure. Organic Rankine cycle and combined cycle are more popular and relatively mature. Osaka Gas Company in Japan built ORC and CC system using propane in 1979 and 1982, and the power output reached 1450 and 6000 kW, respectively [11]. Due to the importance of system parameters on the performance of power generation system, many researches are carried out. With seawater as heat source and LNG as heat sink, Kim et al. [12] found that there is an optimum condenser outlet temperature for ORC system. Heat source inlet temperature, evaporation pressure and condensation temperature are studied by Wang et al. [13] to achieve high exergy efficiency of ORC recovering LNG cold energy. With the heat integration of LNG at vaporization pressure of 70 bar, Koku et al. [14] obtained a thermal efficiency of 6% for the combined cycle with propane as working fluid.

Improvement of system structure and proper working fluid selection are two effective way to enhance the system performance. For system structure, the combinations of simple Rankine cycle in series or parallel is often considered by Zhang et al. [7] and García et al. [15] and they found that they were indeed more efficient. Cascaded Rankine cycles are also common improvement and are proved to be superior to simple Rankine cycles by Li et al. [16], Choi et al. [17], Cao et al. [18], and Wang et al. [19]. By combining the Rankine cycle and refrigeration cycle, the study of Zhang et al. [20] showed that both electricity and refrigeration can be produced simultaneously. Mosaffa et al. [21] compared four different cycles, and pointed out that different system structure is best when the objective function changes.

Selection of working fluids is also critical for the performance and economy of system except for cycle structure. By using eight kinds of working fluids, Zhang et al. [7] found n-pentane has the best system performance. A comparative study by Sung et al. [22] showed that R123 were the optimal working fluids for a dual-loop cycle with LNG cold energy as heat sink. Considering ethane, ethene, carbon dioxide, R134a, R143a and propene, Ferreira et al. [23] concluded that ethene and ethane had higher system efficiency. Zeotropic mixtures are also considered in power generation system for recovery of LNG cold energy. Ammonia-water mixture is used by Wang et al. [24], and they found there was an optimal mass fraction at which work output was largest. With R601-R23-R14 ternary mixture as the working fluid, Lee et al. [25] found that the exergy loss of ORC using mixture is lower than that of pure fluids. Kim et al. [26] selected R14-propane mixture as the working fluids for the first stage of a cascaded system and ethane-n-pentane mixture for the other two stages. Modi and Haglind [27] thought that zeotropic mixture is the development direction of working fluids with its higher thermodynamic performance.

In this chapter, the performance of power generation systems by LNG cold energy will be enhanced with two aspects: improvement of system configuration and optimization of working fluids. Firstly, the two-stage condensation Rankine cycle is introduced. Based on this, the effect of stage number of condensation process is discussed. Then, the influence of the arrangements for compression process and expansion process is studied. Regarding to the optimization of working fluids, pure working fluids are firstly compared, and then zeotropic mixtures are optimized. Finally, a simultaneous approach to optimize the component and composition of zeotropic mixture is put forward.

## **2. Improvement of system configuration**

is produced [6]. Before being used, LNG must be regasified to NG again at the receiving site, and this process will release a great deal of energy, which is called cold energy [7]. It is very important to recovery LNG cold energy which is clean and of high quality. Usually LNG is heated by sea water or air, so that LNG cold energy is wasted and the sea near the regasification site also is affected [8]. Therefore, the recovery of the LNG cold energy a dual purpose [8]. One of effective ways to utilize LNG cold energy is power generation [9]. The traditional cycles include direct expansion cycle (DE), organic Rankine cycle (ORC) and combined cycle (CC) [10]. Although the simplicity for direct expansion cycle, it has limited applications with low efficiency and high operation pressure. Organic Rankine cycle and combined cycle are more popular and relatively mature. Osaka Gas Company in Japan built ORC and CC system using propane in 1979 and 1982, and the power output reached 1450 and 6000 kW, respectively [11]. Due to the importance of system parameters on the performance of power generation system, many researches are carried out. With seawater as heat source and LNG as heat sink, Kim et al. [12] found that there is an optimum condenser outlet temperature for ORC system. Heat source inlet temperature, evaporation pressure and condensation temperature are studied by Wang et al. [13] to achieve high exergy efficiency of ORC recovering LNG cold energy. With the heat integration of LNG at vaporization pressure of 70 bar, Koku et al. [14] obtained a thermal efficiency of 6% for the combined cycle with propane as working fluid.

Improvement of system structure and proper working fluid selection are two effective way to enhance the system performance. For system structure, the combinations of simple Rankine cycle in series or parallel is often considered by Zhang et al. [7] and García et al. [15] and they found that they were indeed more efficient. Cascaded Rankine cycles are also common improvement and are proved to be superior to simple Rankine cycles by Li et al. [16], Choi et al. [17], Cao et al. [18], and Wang et al. [19]. By combining the Rankine cycle and refrigeration cycle, the study of Zhang et al. [20] showed that both electricity and refrigeration can be produced simultaneously. Mosaffa et al. [21] compared four different cycles, and pointed out

Selection of working fluids is also critical for the performance and economy of system except for cycle structure. By using eight kinds of working fluids, Zhang et al. [7] found n-pentane has the best system performance. A comparative study by Sung et al. [22] showed that R123 were the optimal working fluids for a dual-loop cycle with LNG cold energy as heat sink. Considering ethane, ethene, carbon dioxide, R134a, R143a and propene, Ferreira et al. [23] concluded that ethene and ethane had higher system efficiency. Zeotropic mixtures are also considered in power generation system for recovery of LNG cold energy. Ammonia-water mixture is used by Wang et al. [24], and they found there was an optimal mass fraction at which work output was largest. With R601-R23-R14 ternary mixture as the working fluid, Lee et al. [25] found that the exergy loss of ORC using mixture is lower than that of pure fluids. Kim et al. [26] selected R14-propane mixture as the working fluids for the first stage of a cascaded system and ethane-n-pentane mixture for the other two stages. Modi and Haglind [27] thought that zeotropic mixture is the development direction of working fluids with its

that different system structure is best when the objective function changes.

higher thermodynamic performance.

150 Organic Rankine Cycle Technology for Heat Recovery

#### **2.1. Two-stage condensation Rankine cycle (TCRC)**

As shown in **Figure 1**, the TCRC system consists of an evaporator, two turbines, two condensers, a mixer, a splitter and two feed pumps. After heated in the evaporator by sea water, working fluid is evaporated to vapor and is divided into two streams in the splitter. The two streams flow into different turbines respectively and are expanded to two different condensation pressures. These two streams transferred heat energy to LNG in two different condensers and cooled to liquid. The two streams are pressurized by two different pumps and mixed in the mixer. The converged stream enters the evaporator again and the new cycle recommences. Except for absorbing the condensation heat from working fluids in two condensers, LNG is further heated to the scheduled temperature in the reheater with sea water. T-s diagram of the TCRC system is plotted in **Figure 2**, and the labeled state points in **Figure 2** is the same as that in **Figure 1**.

In order to determine whether the new proposed cycle has a better performance, the novel system is compared with the conventional methods under the same conditions.

**Figure 1.** Schematic diagram of the TCRC system.

**Figure 2.** T-s diagram of the TCRC system.

Net power output, thermal efficiency and exergy efficiency of TCRC system is compared with the traditional cycles (DEC, ORC and CC), as shown in **Figure 3**. It should be pointed out that four systems all used propane as working fluid. From **Figure 3**, it can be found that the performance of proposed system is remarkably superior to the traditional power generation cycles. Combined cycle has the highest net power output, thermal efficiency and exergy efficiency among the traditional systems. However, compared with CC system, TCRC system has a 45.27%, 42.91% and 52.31% increase respectively, in term of net power output, thermal efficiency and exergy efficiency.

**2.2. Effects of stage number of condensation process**

**Figure 4.** Heat transfer characteristics between working fluid and LNG: (a) ORC and (b) TCRC.

stages of condensation process should be chosen?

tion expansion cycle (DC) is also considered.

expansion.

In the previous section, it has been proved that two-stage condensation process has the potential to improve the performance of power generation systems by LNG cold energy. If the number of condensation stage is increased, the performance of power generation systems should be better at the cost of greater initial investment with more equipment. How many

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**Figure 5** shows the schematic of six different cycles from single-stage to three-stage condensation Rankine cycle with or without direction expansion. To take a comparison object, direc-

**Figure 5.** Schematic of single-stage, two-stage and three-stage condensation Rankine cycles with or without direction

In order to explain the reason why TCRC system could have a better performance than the traditional cycle, the heat transfer curves between working fluid and LNG of ORC and TCRC systems are plotted in **Figure 4**. It can be seen from **Figure 4** that heat transfer irreversibility of ORC system is larger than that of TCRC system. The main reason is that compared with ORC system, the condensation process of TCRC system is two-stage, which could lower the heat transfer irreversibility of the condenser.

**Figure 3.** System performance of the four power generation methods: (a) net power output, (b) thermal efficiency, and (c) exergy efficiency.

**Figure 4.** Heat transfer characteristics between working fluid and LNG: (a) ORC and (b) TCRC.

#### **2.2. Effects of stage number of condensation process**

Net power output, thermal efficiency and exergy efficiency of TCRC system is compared with the traditional cycles (DEC, ORC and CC), as shown in **Figure 3**. It should be pointed out that four systems all used propane as working fluid. From **Figure 3**, it can be found that the performance of proposed system is remarkably superior to the traditional power generation cycles. Combined cycle has the highest net power output, thermal efficiency and exergy efficiency among the traditional systems. However, compared with CC system, TCRC system has a 45.27%, 42.91% and 52.31% increase respectively, in term of net power output, thermal

In order to explain the reason why TCRC system could have a better performance than the traditional cycle, the heat transfer curves between working fluid and LNG of ORC and TCRC systems are plotted in **Figure 4**. It can be seen from **Figure 4** that heat transfer irreversibility of ORC system is larger than that of TCRC system. The main reason is that compared with ORC system, the condensation process of TCRC system is two-stage, which could lower the heat

**Figure 3.** System performance of the four power generation methods: (a) net power output, (b) thermal efficiency, and

efficiency and exergy efficiency.

**Figure 2.** T-s diagram of the TCRC system.

152 Organic Rankine Cycle Technology for Heat Recovery

transfer irreversibility of the condenser.

(c) exergy efficiency.

In the previous section, it has been proved that two-stage condensation process has the potential to improve the performance of power generation systems by LNG cold energy. If the number of condensation stage is increased, the performance of power generation systems should be better at the cost of greater initial investment with more equipment. How many stages of condensation process should be chosen?

**Figure 5** shows the schematic of six different cycles from single-stage to three-stage condensation Rankine cycle with or without direction expansion. To take a comparison object, direction expansion cycle (DC) is also considered.

**Figure 5.** Schematic of single-stage, two-stage and three-stage condensation Rankine cycles with or without direction expansion.

Net power output of system:

$$\mathbf{W}\_{\text{net}} = \sum \mathbf{W}\_{\text{tra},l} - \sum \mathbf{W}\_{p,l} \tag{1}$$

The electricity production cost (EPC) can be expressed as:

$$EPC = \frac{3600 \text{ C}\_{\text{total}}}{W\_{\text{net}}} \tag{2}$$

The electricity prices of literatures are different, such as 0.04, 0.061, 0.1, 0.123 and 0.18\$/kWh [28]. DC and CC systems should be selected at the LNG vaporization pressure less than 30 bar if the electricity price is 0.04\$/kWh. No system is profitable at the LNG vaporization pressure of 70 bar. The CC systems are suitable at all the LNG vaporization pressure when the electricity price is 0.061\$/kWh. At the LNG vaporization pressure less than 30 bar, it should be considered DE system. Seven cycles could be profitable if electricity price is larger than 0.1\$/kWh.

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The capacity of power generation can be weight by net power output, and whether cycle is profitable could evaluated by EPC. But the maximum profitability of the system is determined by both the net power output and EPC, which be reflected by annual net income. The electricity price of 0.123 \$/kWh is taken as the referenced electricity price. It can be seen from **Figure 8** that the annual net income of the 3CC system is largest, while the least is the DC cycle. The annual net income of the Rankine cycles is lower than that of the combined cycles at the same stage number of the condensation process. When the stage number of the condensation process increases, both the annual net income of the Rankine cycle and the combined

**2.3. Influence of the arrangements for compression process and expansion process**

In the field of utilizing LNG cold energy by ORC (organic Rankine cycle), most studies focus on how to reduce the irreversible loss of the heat exchange process but pay little attention to the arrangements for compression and expansion process. The compression and expansion process, as the parts of the cycle that consumes and products energy, affect the cycle performance as well due to that their different arrangements make the efficiency of the component different. The structures of four different two-stage condensation Rankine cycles are shown in **Figure 9**. There are two types of arrangements for the pumps in the compression process.

cycle systems goes up, but their increase rates decrease.

**Figure 7.** The minimum EPC of seven systems at different LNG vapor pressures.

The annual total net income (ATNI) of the system can be defined as:

*ATNI* = 7300(*EP* − *EPC*) *Wnet* (3)

where EP is electricity price.

From **Figure 6** it can be seen that the net power output of the 3CC is the largest and the DE is the least at any LNG vaporization pressure. When stage number of condensation process increases, the net power output of Rankine cycles and combined cycles both increases. The performance of combined cycles is better than that of Rankine cycles at the same stage number of condensation process.

**Figure 7** shows the minimum EPC of seven different cycles at different LNG vaporization pressures. The EPC of the Rankine cycle is larger than that of the combined system at the same stage number of condensation process. The EPC of combined cycle is the least at the LNG vaporization pressure less than 30 bar. With the increase of the stage number of condensation process, EPC of combined cycles and Rankine cycles augments, but its increase rate decreases. When the LNG vaporization pressure increases, the difference of EPC between combined cycles and Rankine cycles at the same stage number of condensation process tends to zero.

**Figure 6.** The maximum net power output at different LNG vaporization pressures.

**Figure 7.** The minimum EPC of seven systems at different LNG vapor pressures.

Net power output of system:

154 Organic Rankine Cycle Technology for Heat Recovery

where EP is electricity price.

ber of condensation process.

The electricity production cost (EPC) can be expressed as:

The annual total net income (ATNI) of the system can be defined as:

**Figure 6.** The maximum net power output at different LNG vaporization pressures.

*EPC* <sup>=</sup> <sup>3600</sup> *<sup>C</sup>* \_\_\_\_\_\_\_*total*

*Wnet* = ∑*Wtur*,*<sup>j</sup>* − ∑*Wp*,*<sup>l</sup>* (1)

*ATNI* = 7300(*EP* − *EPC*) *Wnet* (3)

From **Figure 6** it can be seen that the net power output of the 3CC is the largest and the DE is the least at any LNG vaporization pressure. When stage number of condensation process increases, the net power output of Rankine cycles and combined cycles both increases. The performance of combined cycles is better than that of Rankine cycles at the same stage num-

**Figure 7** shows the minimum EPC of seven different cycles at different LNG vaporization pressures. The EPC of the Rankine cycle is larger than that of the combined system at the same stage number of condensation process. The EPC of combined cycle is the least at the LNG vaporization pressure less than 30 bar. With the increase of the stage number of condensation process, EPC of combined cycles and Rankine cycles augments, but its increase rate decreases. When the LNG vaporization pressure increases, the difference of EPC between combined cycles and Rankine cycles at the same stage number of condensation process tends to zero.

*Wnet*

(2)

The electricity prices of literatures are different, such as 0.04, 0.061, 0.1, 0.123 and 0.18\$/kWh [28]. DC and CC systems should be selected at the LNG vaporization pressure less than 30 bar if the electricity price is 0.04\$/kWh. No system is profitable at the LNG vaporization pressure of 70 bar. The CC systems are suitable at all the LNG vaporization pressure when the electricity price is 0.061\$/kWh. At the LNG vaporization pressure less than 30 bar, it should be considered DE system. Seven cycles could be profitable if electricity price is larger than 0.1\$/kWh.

The capacity of power generation can be weight by net power output, and whether cycle is profitable could evaluated by EPC. But the maximum profitability of the system is determined by both the net power output and EPC, which be reflected by annual net income. The electricity price of 0.123 \$/kWh is taken as the referenced electricity price. It can be seen from **Figure 8** that the annual net income of the 3CC system is largest, while the least is the DC cycle. The annual net income of the Rankine cycles is lower than that of the combined cycles at the same stage number of the condensation process. When the stage number of the condensation process increases, both the annual net income of the Rankine cycle and the combined cycle systems goes up, but their increase rates decrease.

#### **2.3. Influence of the arrangements for compression process and expansion process**

In the field of utilizing LNG cold energy by ORC (organic Rankine cycle), most studies focus on how to reduce the irreversible loss of the heat exchange process but pay little attention to the arrangements for compression and expansion process. The compression and expansion process, as the parts of the cycle that consumes and products energy, affect the cycle performance as well due to that their different arrangements make the efficiency of the component different.

The structures of four different two-stage condensation Rankine cycles are shown in **Figure 9**. There are two types of arrangements for the pumps in the compression process.

*ηturb*,*is* = Σ*<sup>n</sup>*=<sup>0</sup>

compress arrangement performs better than the parallel.

found in Ref. [29].

constant turbine efficiency.

constant efficiency.

15

where Fn is input parameter SP and Vr, and An is the regression coefficients, which could be

In order to study the arrangements of the pumps, cycle 1 is compared with cycle 3 with constant turbine efficiency and same arrangements of the turbines, as shown in **Figure 10a**. Although the condensation temperatures vary within a range, cycle 1 performs almost the same as Cycle 3, which indicating that the impact of the arrangements of the pumps on the system performance is little. The reason is that the consumed power of WF-pump 1 and WF-pump 2 is small (< 0.05 kW), which has a very little effect on the net power output.

To investigate the arrangements of the turbines, Cycle 1 is compared with Cycle 2, as shown in in **Figure 10b**. It can be seen that the net output power of Cycle 2 is always a little higher than that of Cycle 1 at different condensation temperatures, which suggests that the series

Net power output of cycle 1 is compared with cycle 2 and cycle 3 with non-constant turbine efficiency, as shown in **Figure 11**. It could be found that the impact of the arrangements for

**Figure 10.** The comparison of the net power output between (a) cycle 1 and cycle 3, (b) cycle 1 and cycle 2 under the

**Figure 11.** The comparison of the net power output between (a) cycle 1 and cycle 3, (b) cycle 1 and cycle 2 under non-

*Fn An* (4)

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Organic Rankine Cycle for Recovery of Liquefied Natural Gas (LNG) Cold Energy

**Figure 8.** The maximized annual net income of seven cycles at different LNG vapor pressures.

**Figure 9.** The configurations of four different two-stage condensation Rankine cycles.

The arrangement a shown in **Figure 9** is called parallel compression arrangement. The other arrangement b shown in **Figure 9** is called series compression arrangement. Similarly, there are also two types of arrangements for the turbines in the expansion process. The arrangement c shown in **Figure 9** is called parallel expansion arrangement. The arrangement d shown in **Figure 9** is called series expansion arrangement.

This paper takes 80% as the reference efficiency when the turbine efficiency is constant. When the turbine efficiency is non-constant, this paper adopted the turbine efficiency prediction model with the turbine size parameter (SP) and the specific volume (Vr) as the input parameters, as is shown in Eq. (4).

$$
\eta\_{turb,is} = \begin{array}{c}
\text{15} \\
\text{25}
\end{array}
\text{F}\_n\text{A}\_n\tag{4}
$$

where Fn is input parameter SP and Vr, and An is the regression coefficients, which could be found in Ref. [29].

In order to study the arrangements of the pumps, cycle 1 is compared with cycle 3 with constant turbine efficiency and same arrangements of the turbines, as shown in **Figure 10a**. Although the condensation temperatures vary within a range, cycle 1 performs almost the same as Cycle 3, which indicating that the impact of the arrangements of the pumps on the system performance is little. The reason is that the consumed power of WF-pump 1 and WF-pump 2 is small (< 0.05 kW), which has a very little effect on the net power output.

To investigate the arrangements of the turbines, Cycle 1 is compared with Cycle 2, as shown in in **Figure 10b**. It can be seen that the net output power of Cycle 2 is always a little higher than that of Cycle 1 at different condensation temperatures, which suggests that the series compress arrangement performs better than the parallel.

Net power output of cycle 1 is compared with cycle 2 and cycle 3 with non-constant turbine efficiency, as shown in **Figure 11**. It could be found that the impact of the arrangements for

**Figure 10.** The comparison of the net power output between (a) cycle 1 and cycle 3, (b) cycle 1 and cycle 2 under the constant turbine efficiency.

The arrangement a shown in **Figure 9** is called parallel compression arrangement. The other arrangement b shown in **Figure 9** is called series compression arrangement. Similarly, there are also two types of arrangements for the turbines in the expansion process. The arrangement c shown in **Figure 9** is called parallel expansion arrangement. The arrangement d shown

**Figure 8.** The maximized annual net income of seven cycles at different LNG vapor pressures.

156 Organic Rankine Cycle Technology for Heat Recovery

This paper takes 80% as the reference efficiency when the turbine efficiency is constant. When the turbine efficiency is non-constant, this paper adopted the turbine efficiency prediction model with the turbine size parameter (SP) and the specific volume (Vr) as the input param-

in **Figure 9** is called series expansion arrangement.

**Figure 9.** The configurations of four different two-stage condensation Rankine cycles.

eters, as is shown in Eq. (4).

**Figure 11.** The comparison of the net power output between (a) cycle 1 and cycle 3, (b) cycle 1 and cycle 2 under nonconstant efficiency.

pumps on the system performance is little but the influence of the arrangements for turbine is great. The series arrangement for turbines has a greater impact on the system performance than the parallel arrangement. Meanwhile, this impact for non-constant turbine efficiency is much more pronounced than that for constant turbine efficiency, with comparing **Figures 10** and **11**.

output is approximately the same as that of the critical temperature of working fluids. With the increase of the critical temperature, the net power output of the system increases roughly.

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In this section, 11 pure working fluids are combined to binary mixtures. With the net power output as the objective function, evaporation temperature, condensation temperatures, the inlet pressure of the NG turbine and the molar fraction of binary working fluids are optimized. When the net power output of the system is maximum, the optimized results of differ-

The gray dotted line in **Figure 13b** represents the trend line of net power output of 11 pure working fluids, and the black dotted line represents the trend line of maximum net power output in each column. From Figure b, it can be found that the optimal net power output for pure fluids changes from 2158.49 to 2712.41 kW. While the optimal net power output for mixtures distributes between 2894.47 and 3107.91 kW, which has an obvious increase than that for pure fluids and the variation range for mixtures is much smaller than that of pure fluids. **Figure 14** shows the maximum net power output of the two-stage condensation combined cycle when the component numbers of working fluids change from one to five. When the component number of mixed working fluid is five, it is actually quaternary mixture due to the results of optimization. As shown in **Figure 14**, with the increase of the component number of mixed working fluid, the net power output of the two-stage condensation combined cycle is increased, but the increase rate is gradually reduced. When the component numbers of the mixed working fluid are three and four, the net power output of the system is almost the

**Figure 12.** The maximum net power output and the critical temperature for different working fluids.

**3.2. Mixed working fluids**

ent binary mixtures are shown in **Figure 13**.

## **3. Optimization of working fluids**

#### **3.1. Pure working fluids**

For power generation systems using LNG cold energy, the choice of working fluid has a great influence on the performance of the system. Due to the low temperature of the LNG, it is necessary to consider several aspects when selecting working fluid. Based on the previous study, this paper selects 11 kinds of working fluids, including hydrocarbons (HCs) and hydrofluorocarbons (HFCs), and the physical properties of them are shown in **Table 1**.

The evaporation temperature, the condensation temperatures and the inlet pressure of NG turbine of the two-stage condensation combined cycle are optimized with the net power output as objective function. T The maximum net power output and the critical temperatures of the 11 different pure working fluids are shown in **Figure 12**.

It can be seen from **Figure 12** that the net power output of the two-stage condensation combined cycle is the largest when n-C5 H12 is chosen as working fluid, and the net power output of C2 F6 is the least. From the trend lines of the net power output and the critical temperature for 11 kinds of working fluids, it can be found that the variation trend of the net power


**Table 1.** Physical properties of selected pure working fluids.

output is approximately the same as that of the critical temperature of working fluids. With the increase of the critical temperature, the net power output of the system increases roughly.

#### **3.2. Mixed working fluids**

pumps on the system performance is little but the influence of the arrangements for turbine is great. The series arrangement for turbines has a greater impact on the system performance than the parallel arrangement. Meanwhile, this impact for non-constant turbine efficiency is much more pronounced than that for constant turbine efficiency, with comparing **Figures 10** and **11**.

For power generation systems using LNG cold energy, the choice of working fluid has a great influence on the performance of the system. Due to the low temperature of the LNG, it is necessary to consider several aspects when selecting working fluid. Based on the previous study, this paper selects 11 kinds of working fluids, including hydrocarbons (HCs) and hydrofluorocarbons (HFCs), and the physical properties of them are shown in **Table 1**.

The evaporation temperature, the condensation temperatures and the inlet pressure of NG turbine of the two-stage condensation combined cycle are optimized with the net power output as objective function. T The maximum net power output and the critical temperatures of

It can be seen from **Figure 12** that the net power output of the two-stage condensation com-

H<sup>6</sup> 32.17 48.72 −88.82

H<sup>6</sup> 91.06 45.55 −47.62

H<sup>8</sup> 96.74 42.51 −42.11

H<sup>8</sup> 144.94 40.09 −7.00

H<sup>10</sup> 151.98 37.96 −0.49

H<sup>12</sup> 196.55 33.70 36.06

F<sup>4</sup> 101.06 40.59 −26.07

HF5 66.02 36.18 −48.09

F6 19.88 30.48 −78.09

F8 71.87 26.40 −36.79

R23 CHF<sup>3</sup> 26.14 48.32 −82.09

 is the least. From the trend lines of the net power output and the critical temperature for 11 kinds of working fluids, it can be found that the variation trend of the net power

**(bar)**

H12 is chosen as working fluid, and the net power output

**Normal boiling point (°C)**

**3. Optimization of working fluids**

158 Organic Rankine Cycle Technology for Heat Recovery

bined cycle is the largest when n-C5

of C2 F6

R170 C2

R1270 C<sup>3</sup>

R290 C<sup>3</sup>

— i-C<sup>4</sup>

R600 n-C<sup>4</sup>

R601 n-C5

R134a C2

R125 C2

R116 C2

R218 C<sup>3</sup>

H2

**Table 1.** Physical properties of selected pure working fluids.

the 11 different pure working fluids are shown in **Figure 12**.

**Working fluids Chemical formula Critical temperature (°C) Critical pressure** 

**3.1. Pure working fluids**

In this section, 11 pure working fluids are combined to binary mixtures. With the net power output as the objective function, evaporation temperature, condensation temperatures, the inlet pressure of the NG turbine and the molar fraction of binary working fluids are optimized. When the net power output of the system is maximum, the optimized results of different binary mixtures are shown in **Figure 13**.

The gray dotted line in **Figure 13b** represents the trend line of net power output of 11 pure working fluids, and the black dotted line represents the trend line of maximum net power output in each column. From Figure b, it can be found that the optimal net power output for pure fluids changes from 2158.49 to 2712.41 kW. While the optimal net power output for mixtures distributes between 2894.47 and 3107.91 kW, which has an obvious increase than that for pure fluids and the variation range for mixtures is much smaller than that of pure fluids.

**Figure 14** shows the maximum net power output of the two-stage condensation combined cycle when the component numbers of working fluids change from one to five. When the component number of mixed working fluid is five, it is actually quaternary mixture due to the results of optimization. As shown in **Figure 14**, with the increase of the component number of mixed working fluid, the net power output of the two-stage condensation combined cycle is increased, but the increase rate is gradually reduced. When the component numbers of the mixed working fluid are three and four, the net power output of the system is almost the

**Figure 12.** The maximum net power output and the critical temperature for different working fluids.

same. With the increase of the component number of mixture, the difficulty of charging working fluids into system becomes significant. Therefore, considering the increase rate of the net power output and the difficulty of charging working fluids, the optimum component number of hydrocarbon mixtures is three for the two-stage condensation combined cycle.

**3.3. A simultaneous approach to optimize the component and composition of** 

The traditional method of determining the components and compositions of mixtures is firstly to predefine some fluids, and then, according to the number of components, these fluids are chosen and combined as the component of mixed working fluids one by one. At last, the compositions of the formed mixtures and the corresponding system parameters are optimized at the specified system structure respectively. It is difficult to optimize the components of a

**Figure 15.** Basic idea for simultaneous approach to optimize component and composition of zeotropic mixture.

**Figure 14.** The net power output of the system corresponding to the mixtures with different component numbers.

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161

**zeotropic mixture**

**Figure 13.** The maximum net power output of different pure working fluids and binary mixtures: (a) 3-D histogram and (b) 2-D diagram.

same. With the increase of the component number of mixture, the difficulty of charging working fluids into system becomes significant. Therefore, considering the increase rate of the net power output and the difficulty of charging working fluids, the optimum component number

**Figure 13.** The maximum net power output of different pure working fluids and binary mixtures: (a) 3-D histogram and

(b) 2-D diagram.

of hydrocarbon mixtures is three for the two-stage condensation combined cycle.

160 Organic Rankine Cycle Technology for Heat Recovery

**Figure 14.** The net power output of the system corresponding to the mixtures with different component numbers.

## **3.3. A simultaneous approach to optimize the component and composition of zeotropic mixture**

The traditional method of determining the components and compositions of mixtures is firstly to predefine some fluids, and then, according to the number of components, these fluids are chosen and combined as the component of mixed working fluids one by one. At last, the compositions of the formed mixtures and the corresponding system parameters are optimized at the specified system structure respectively. It is difficult to optimize the components of a

**Figure 15.** Basic idea for simultaneous approach to optimize component and composition of zeotropic mixture.

mixture, because the components of the mixed working fluids are independent of each other and discrete, and meanwhile it is difficult to describe them with mathematical variables. In order to reduce the intensity of calculation for components and compositions of zeotropic mixtures and achieve the simultaneous optimization of components and compositions for zeotropic mixtures, a selective coefficient a<sup>i</sup> is introduced, as shown in **Figure 15**. Because the components of mixture are discrete, only discrete variables can be used to describe them. Each component of mixture is expressed by a selective coefficient. The selective coefficient a<sup>i</sup> is a binary variable, and it has two values 0 or 1. When the value of selective coefficient a<sup>i</sup> is 1, the component expressed by this selective coefficient is selected. While the value of selective

coefficient a<sup>i</sup>

optimized by Σa<sup>i</sup> = 2. While the composition x<sup>i</sup>

fraction). Pure fluid pentane is best among pure fluids.

mal results are shown in **Table 2**.

**4. Conclusions**

calculation time greatly.

**Acknowledgements**

**Conflict of interest**

The author declared that there is no conflict of interest.

(No. 51606025).

ai

is 0, it means this component is not selected. The sum of the selective coefficient

Organic Rankine Cycle for Recovery of Liquefied Natural Gas (LNG) Cold Energy

of each component is the continuous variable

http://dx.doi.org/10.5772/intechopen.77990

, but the

163

x<sup>i</sup> = 1.

is used to control the number of component for mixture. For example, binary mixture can be

Net power output is selected as the objective function, and the optimization variables include the selective coefficients of components, operation parameters of system and compositions of components. For the two-stage condensation Rankine cycle shown in **Figure 1**, the main operation parameters are evaporation temperature, the first-stage condensation temperature and the second-stage condensation temperature. The range of control variables and their opti-

**Table 2** shows that the best ternary mixture is propylene/isobutane/pentane (0.492/0.319/0.189, by mole fraction), and the optimum binary mixture isobutane/pentane (0.836/0.164, by mole

This chapter has proposed a conception of multi-stage condensation Rankine cycle (TCRC) system. The performance of the power generation systems is enhanced by two aspects: improvement of system configuration and optimization of working fluids. Compared with the combined cycle, the net work output, thermal efficiency and exergy efficiency of the TCRC system are respectively increased by 45.27, 42.91 and 52.31%. The two-stage condensation Rankine cycle is more suitable from the viewpoint of economy. For the arrangements for compression process and expansion process of TCRC, the arrangements for pumps have little impact on the net output power and the series arrangement for turbines performs better than the parallel arrangement. With the increase of the critical temperature for pure fluids, the net power output of the system increases roughly. Zeotropic mixture can improve the performance, and the optimum component number of hydrocarbon mixtures is three for the two-stage condensation combined cycle. A simultaneous approach to optimize the component and composition of zeotropic mixture is put forward which can reduce the consumed

This research was financially supported by the National Natural Science Foundation of China

and its value is between 0 and 1. There are no constraint conditions for composition x<sup>i</sup>

total sum of compositions for all the selected components should be 1, i.e., Σa<sup>i</sup>


**Table 2.** The range of control variables and their optimal results in case 2.

coefficient a<sup>i</sup> is 0, it means this component is not selected. The sum of the selective coefficient ai is used to control the number of component for mixture. For example, binary mixture can be optimized by Σa<sup>i</sup> = 2. While the composition x<sup>i</sup> of each component is the continuous variable and its value is between 0 and 1. There are no constraint conditions for composition x<sup>i</sup> , but the total sum of compositions for all the selected components should be 1, i.e., Σa<sup>i</sup> x<sup>i</sup> = 1.

Net power output is selected as the objective function, and the optimization variables include the selective coefficients of components, operation parameters of system and compositions of components. For the two-stage condensation Rankine cycle shown in **Figure 1**, the main operation parameters are evaporation temperature, the first-stage condensation temperature and the second-stage condensation temperature. The range of control variables and their optimal results are shown in **Table 2**.

**Table 2** shows that the best ternary mixture is propylene/isobutane/pentane (0.492/0.319/0.189, by mole fraction), and the optimum binary mixture isobutane/pentane (0.836/0.164, by mole fraction). Pure fluid pentane is best among pure fluids.

## **4. Conclusions**

mixture, because the components of the mixed working fluids are independent of each other and discrete, and meanwhile it is difficult to describe them with mathematical variables. In order to reduce the intensity of calculation for components and compositions of zeotropic mixtures and achieve the simultaneous optimization of components and compositions for

the components of mixture are discrete, only discrete variables can be used to describe them. Each component of mixture is expressed by a selective coefficient. The selective coefficient a<sup>i</sup> is a binary variable, and it has two values 0 or 1. When the value of selective coefficient a<sup>i</sup>

the component expressed by this selective coefficient is selected. While the value of selective

**pure fluid**

Ethane selective coefficient a1 {0,1} 0 0 0 Ethylene selective coefficient a2 {0,1} 0 0 0 Propylene selective coefficient a<sup>3</sup> {0,1} 0 0 1 Propane selective coefficient a<sup>4</sup> {0,1} 0 0 0 Butane selective coefficient a5 {0,1} 0 0 0 Isobutane selective coefficient a6 {0,1} 0 1 1 Pentane selective coefficient a<sup>7</sup> {0,1} 1 1 1 R23 selective coefficient a8 {0,1} 0 0 0 R32 selective coefficient a9 {0,1} 0 0 0 R41 selective coefficient a10 {0,1} 0 0 0 R116 selective coefficient a11 {0,1} 0 0 0 Ethane mole fraction x1 [0,1] 0.441 0.485 0.598 Ethylene mole fraction x2 [0,1] 0.162 0.488 0.254 Propylene mole fraction x<sup>3</sup> [0,1] 0.399 0.527 0.492 Propane mole fraction x<sup>4</sup> [0,1] 0.211 0.410 0.852 Butane mole fraction x5 [0,1] 0.752 0.539 0.570 Isobutane mole fraction x6 [0,1] 0.825 0.836 0.319 Pentane mole fraction x<sup>7</sup> [0,1] 1 0.164 0.189 R23 mole fraction x8 [0,1] 0.622 0.734 0.494 R32 mole fraction x9 [0,1] 0.300 0.390 0.351 R41 mole fraction x10 [0,1] 0.705 0.503 0.188 R116 mole fraction x11 [0,1] 0.583 0.304 0.452 Evaporation temperature x12 (°C) [5,10] 6.3 10.0 10.0

is introduced, as shown in **Figure 15**. Because

**Optimal results of binary mixture**

[−140, −90] −100.0 −113.9 −129.7

[−80, −40] −42.9 −56.2 −71.2

is 1,

**Optimal results of ternary mixture**

zeotropic mixtures, a selective coefficient a<sup>i</sup>

162 Organic Rankine Cycle Technology for Heat Recovery

**Control variables Range Results of** 

First-stage condensation temperature

**Table 2.** The range of control variables and their optimal results in case 2.

Second-stage condensation temperature x14 (°C)

x13 (°C)

This chapter has proposed a conception of multi-stage condensation Rankine cycle (TCRC) system. The performance of the power generation systems is enhanced by two aspects: improvement of system configuration and optimization of working fluids. Compared with the combined cycle, the net work output, thermal efficiency and exergy efficiency of the TCRC system are respectively increased by 45.27, 42.91 and 52.31%. The two-stage condensation Rankine cycle is more suitable from the viewpoint of economy. For the arrangements for compression process and expansion process of TCRC, the arrangements for pumps have little impact on the net output power and the series arrangement for turbines performs better than the parallel arrangement. With the increase of the critical temperature for pure fluids, the net power output of the system increases roughly. Zeotropic mixture can improve the performance, and the optimum component number of hydrocarbon mixtures is three for the two-stage condensation combined cycle. A simultaneous approach to optimize the component and composition of zeotropic mixture is put forward which can reduce the consumed calculation time greatly.

## **Acknowledgements**

This research was financially supported by the National Natural Science Foundation of China (No. 51606025).

## **Conflict of interest**

The author declared that there is no conflict of interest.

## **Author details**

#### Junjiang Bao

Address all correspondence to: baojj@dlut.edu.cn

School of Petroleum and Chemical Engineering, Dalian University of Technology, Panjin, China

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**Chapter 9**

Provisional chapter

**Power Generation with Thermolytic Reverse**

Power Generation with Thermolytic Reverse

Deok Han Kim, Byung Ho Park, Kilsung Kwon,

Deok Han Kim, Byung Ho Park, Kilsung Kwon,

Additional information is available at the end of the chapter

compounds for novel technologies of waste heat recovery.

bicarbonate, thermolytic solution

Keywords: reverse electrodialysis (RED), closed-loop, waste heat, ammonium

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and eproduction in any medium, provided the original work is properly cited.

© 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use,

distribution, and reproduction in any medium, provided the original work is properly cited.

Additional information is available at the end of the chapter

Longnan Li and Daejoong Kim

Longnan Li and Daejoong Kim

http://dx.doi.org/10.5772/intechopen.81006

Abstract

**Electrodialysis for Low-Grade Waste Heat Recovery**

DOI: 10.5772/intechopen.81006

Closed-loop reverse electrodialysis (RED) systems that use a thermolytic solution for lowgrade waste heat recovery have attracted significant attention. They have several cost benefits, e.g., the absence of repetitive pretreatment and removal of locational constraints, when compared with open-loop RED systems using seawater and river water. This study presents a model of RED that uses ammonium bicarbonate, and this is a promising solution for closed-loop systems. The modified Planck-Henderson equation is used to calculate the ion exchange membrane potential. The calculation is based on the conductivity measurements as ionization carbonate electrochemical information has not been reported before this study. The solution resistance is experimentally determined. The experimentally obtained permselectivity is implemented into the model to predict the membrane potential more accurately. The results of the improved model are well matched with experimental results under results under various operating conditions of the RED system. In addition, in the model of this study, the net power density was characterized with the consideration of the pumping loss. The improved model predicts a maximum net power density of 0.84 W/m<sup>2</sup> with an intermembrane distance of 0.1 mm, a flow rate of 3 mL/min, and a concentration ratio of 200 as optimum conditions. The results of the study are expected to improve our understanding of the ammonium bicarbonate-RED system and contribute to modeling studies using ammonium bicarbonate or certain other

Electrodialysis for Low-Grade Waste Heat Recovery


#### **Power Generation with Thermolytic Reverse Electrodialysis for Low-Grade Waste Heat Recovery** Power Generation with Thermolytic Reverse Electrodialysis for Low-Grade Waste Heat Recovery

DOI: 10.5772/intechopen.81006

Deok Han Kim, Byung Ho Park, Kilsung Kwon, Longnan Li and Daejoong Kim Deok Han Kim, Byung Ho Park, Kilsung Kwon, Longnan Li and Daejoong Kim

Additional information is available at the end of the chapter Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/intechopen.81006

#### Abstract

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1016/j.energy.2014.09.036

166 Organic Rankine Cycle Technology for Heat Recovery

100510-1.00009-0

DOI: 10.1016/j.enconman.2017.02.032

Closed-loop reverse electrodialysis (RED) systems that use a thermolytic solution for lowgrade waste heat recovery have attracted significant attention. They have several cost benefits, e.g., the absence of repetitive pretreatment and removal of locational constraints, when compared with open-loop RED systems using seawater and river water. This study presents a model of RED that uses ammonium bicarbonate, and this is a promising solution for closed-loop systems. The modified Planck-Henderson equation is used to calculate the ion exchange membrane potential. The calculation is based on the conductivity measurements as ionization carbonate electrochemical information has not been reported before this study. The solution resistance is experimentally determined. The experimentally obtained permselectivity is implemented into the model to predict the membrane potential more accurately. The results of the improved model are well matched with experimental results under results under various operating conditions of the RED system. In addition, in the model of this study, the net power density was characterized with the consideration of the pumping loss. The improved model predicts a maximum net power density of 0.84 W/m<sup>2</sup> with an intermembrane distance of 0.1 mm, a flow rate of 3 mL/min, and a concentration ratio of 200 as optimum conditions. The results of the study are expected to improve our understanding of the ammonium bicarbonate-RED system and contribute to modeling studies using ammonium bicarbonate or certain other compounds for novel technologies of waste heat recovery.

Keywords: reverse electrodialysis (RED), closed-loop, waste heat, ammonium bicarbonate, thermolytic solution

© 2016 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and eproduction in any medium, provided the original work is properly cited. © 2018 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

## 1. Introduction

The increase in world energy consumption has led to a significant increase in the demand for fossil fuels. The increase in fossil fuel consumption causes various problems, including global warming and climate change. The Paris climate conference underscores the collective, worldwide attention on preventing bigger disasters. Several studies have focused on lessening and replacing the consumption of fossil fuels. An emerging source is waste heat, which is not only a cause of heat pollution but also a source for generating electricity in a different way [1, 2]. There are several techniques to harness waste heat, e.g., the organic Rankine cycle (ORC) and thermoelectric power. However, there are several disadvantages for the recovery of energy by using these techniques, such as environmentally harmful refrigerants, downsizing in ORC systems, low efficiency, and poor form factor in thermoelectric elements [3–9].

solution flow rate and feed solution concentration combinations [10]. They achieved a maximum power density of 0.89 W/m<sup>2</sup> with an intermembrane distance of 0.3 mm and with concentrated and diluted solutions of 2 and 0.02 M, respectively [19]. Kwon and his coworkers quantitatively tested parameters such as intermembrane distances and IEM types [20]. They obtained a power density of 0.77 W/m<sup>2</sup> with an intermembrane distance of 0.2 mm and with concentrated and diluted solutions of 1.5 and 0.01 M, respectively. Geise et al. provided deep insights into the transport phenomena of ammonium bicarbonate through IEMs [21–24]. They analyzed the relationship between the permselectivity, membrane resistance, membrane structure, and functional groups fixed on several types of IEMs and individual ion species of the

Power Generation with Thermolytic Reverse Electrodialysis for Low-Grade Waste Heat Recovery

http://dx.doi.org/10.5772/intechopen.81006

169

Since 2011, the studies have focused on RED numerical simulations. Veerman et al. developed a one-dimensional numerical model for a unit cell [25]. Tedesco et al. improved the model of Veerman with respect to the previously neglected nonideal phenomena, such as concentration polarization (CP) and temperature variation, and validated a wider concentration range [26]. Kwon and his coworkers further developed the model. They applied some updated thermodynamic properties in the model, such as dielectric constant and viscosity. CP phenomena were considered in their model through the implementation with empirical equations. This upgraded model can predict the actual physics more accurately, and it enabled the calculation of higher concentration combinations. However, the calculation with bicarbonate is yet to be improved because of its complexity. Compared to a binary electrolyte (e.g., sodium chloride), it

The key issue in this calculation is to predict the internal resistance and membrane potential in the system. Compared with NaCl, which is the conventional electrolyte for the RED process, the electrochemical information of ammonium bicarbonate requires the estimation of the membrane potential and internal resistance, including activity and transport number. The transportation properties of ammonium bicarbonate remain unclarified and unexplored by extant studies. A recent study estimated the membrane potential based on electrical conductivity measurements [27]. The solution resistance was computed in the range of concentration

In this study, we performed a numerical simulation of RED power generation. The simulation was based on ammonium bicarbonate and validated through our experimental results. The permselectivity of the IEM was assumed as in previous studies [25, 26, 28]. Moreover, we measured all the properties by an experiment to predict the RED performance more precisely. Following the model validation, the optimum operating conditions of RED systems were characterized with different settings in terms of flow rate, intermembrane distance, and con-

A thermal-driven electrochemical generator (TDEG) is illustrated in Figure 1. The TDEG consists of a RED system and a separator based on thermal energy [10]. The mixed diluted

is hard to of extensively expressing the electrochemical information.

of our interest based on the definition of molar conductivity.

centration ratio.

2. Modeling approach

ammonium bicarbonate electrolyte.

The reverse electrodialysis (RED) system combined with thermal separation components could form a closed loop that harnesses the waste heat by utilizing the salinity gradient energy (SGE) [10]. RED is a power generation technique based on SGE. RED mixes of two different salinity solutions with ion exchange membranes (IEM). It includes advantage of not emitting environmentally harmful gases. It also obtains unlimited, free fuel supply in the vicinity of places where seawater and river water meet. Conversely, the accessibility to these natural resources limits its locational options. Furthermore, the high cost of maintenance of the RD stack is a challenging problem for actual implementation. Especially, the IEMs, a core component, are still exposed to fouling problems, and the fouled IEMs should be either replaced with new ones or recovered [11, 12]. These problems of RED can be overcome by combining a RED system with a thermal separation component because of its closed-loop characteristics [13–16]. The difference of salinity solution concentrations retains the electromotive force by separating the increased solute from the diluted side and recapturing it in the concentrated solution without any fresh solution supply, and thus the process is operated as a closed-loop system. The closed-loop system mitigates the geographical limitations as a continuous supply of fresh seawater (high concentration solution) and river water (low concentration solution) is not necessary, thereby preventing the possible risks of membrane fouling as well as saving pretreatment costs.

A thermolytic solution that is easily separated at a relatively low temperature is necessary for the process. Traditionally, organic and ammonia solutions are used as thermolytic solutions in waste heat recovery systems. Organic solutions, such as R-21 and R-123, have a low boiling point; however, they do not solve in water and show low osmotic efficiency [4]. Ammonia water (ammonium hydroxide) is another widely used ORC solution; however, it is corrosive, which means the damage of the materials of RED such as membranes and spacers. An ammonium bicarbonate is a promising thermolytic solution owing to its high solubility in water, large osmotic efficiency, circulation capacity, and relatively low molecular weight [17, 18]. More importantly, ammonium bicarbonate can be recovered with moderate heat, which suggests significant energy advantages compared with the regeneration of other draw solutes. Ammonium bicarbonate has low decomposition temperature, of approximately 60�C at 1 atm, and it decomposes at 120�C. Luo et al. conducted RED experiments by using an ammonium bicarbonate solution under different inlet conditions. They set different feed solution flow rate and feed solution concentration combinations [10]. They achieved a maximum power density of 0.89 W/m<sup>2</sup> with an intermembrane distance of 0.3 mm and with concentrated and diluted solutions of 2 and 0.02 M, respectively [19]. Kwon and his coworkers quantitatively tested parameters such as intermembrane distances and IEM types [20]. They obtained a power density of 0.77 W/m<sup>2</sup> with an intermembrane distance of 0.2 mm and with concentrated and diluted solutions of 1.5 and 0.01 M, respectively. Geise et al. provided deep insights into the transport phenomena of ammonium bicarbonate through IEMs [21–24]. They analyzed the relationship between the permselectivity, membrane resistance, membrane structure, and functional groups fixed on several types of IEMs and individual ion species of the ammonium bicarbonate electrolyte.

Since 2011, the studies have focused on RED numerical simulations. Veerman et al. developed a one-dimensional numerical model for a unit cell [25]. Tedesco et al. improved the model of Veerman with respect to the previously neglected nonideal phenomena, such as concentration polarization (CP) and temperature variation, and validated a wider concentration range [26]. Kwon and his coworkers further developed the model. They applied some updated thermodynamic properties in the model, such as dielectric constant and viscosity. CP phenomena were considered in their model through the implementation with empirical equations. This upgraded model can predict the actual physics more accurately, and it enabled the calculation of higher concentration combinations. However, the calculation with bicarbonate is yet to be improved because of its complexity. Compared to a binary electrolyte (e.g., sodium chloride), it is hard to of extensively expressing the electrochemical information.

The key issue in this calculation is to predict the internal resistance and membrane potential in the system. Compared with NaCl, which is the conventional electrolyte for the RED process, the electrochemical information of ammonium bicarbonate requires the estimation of the membrane potential and internal resistance, including activity and transport number. The transportation properties of ammonium bicarbonate remain unclarified and unexplored by extant studies. A recent study estimated the membrane potential based on electrical conductivity measurements [27]. The solution resistance was computed in the range of concentration of our interest based on the definition of molar conductivity.

In this study, we performed a numerical simulation of RED power generation. The simulation was based on ammonium bicarbonate and validated through our experimental results. The permselectivity of the IEM was assumed as in previous studies [25, 26, 28]. Moreover, we measured all the properties by an experiment to predict the RED performance more precisely. Following the model validation, the optimum operating conditions of RED systems were characterized with different settings in terms of flow rate, intermembrane distance, and concentration ratio.

## 2. Modeling approach

1. Introduction

168 Organic Rankine Cycle Technology for Heat Recovery

pretreatment costs.

The increase in world energy consumption has led to a significant increase in the demand for fossil fuels. The increase in fossil fuel consumption causes various problems, including global warming and climate change. The Paris climate conference underscores the collective, worldwide attention on preventing bigger disasters. Several studies have focused on lessening and replacing the consumption of fossil fuels. An emerging source is waste heat, which is not only a cause of heat pollution but also a source for generating electricity in a different way [1, 2]. There are several techniques to harness waste heat, e.g., the organic Rankine cycle (ORC) and thermoelectric power. However, there are several disadvantages for the recovery of energy by using these techniques, such as environmentally harmful refrigerants, downsizing in ORC

The reverse electrodialysis (RED) system combined with thermal separation components could form a closed loop that harnesses the waste heat by utilizing the salinity gradient energy (SGE) [10]. RED is a power generation technique based on SGE. RED mixes of two different salinity solutions with ion exchange membranes (IEM). It includes advantage of not emitting environmentally harmful gases. It also obtains unlimited, free fuel supply in the vicinity of places where seawater and river water meet. Conversely, the accessibility to these natural resources limits its locational options. Furthermore, the high cost of maintenance of the RD stack is a challenging problem for actual implementation. Especially, the IEMs, a core component, are still exposed to fouling problems, and the fouled IEMs should be either replaced with new ones or recovered [11, 12]. These problems of RED can be overcome by combining a RED system with a thermal separation component because of its closed-loop characteristics [13–16]. The difference of salinity solution concentrations retains the electromotive force by separating the increased solute from the diluted side and recapturing it in the concentrated solution without any fresh solution supply, and thus the process is operated as a closed-loop system. The closed-loop system mitigates the geographical limitations as a continuous supply of fresh seawater (high concentration solution) and river water (low concentration solution) is not necessary, thereby preventing the possible risks of membrane fouling as well as saving

A thermolytic solution that is easily separated at a relatively low temperature is necessary for the process. Traditionally, organic and ammonia solutions are used as thermolytic solutions in waste heat recovery systems. Organic solutions, such as R-21 and R-123, have a low boiling point; however, they do not solve in water and show low osmotic efficiency [4]. Ammonia water (ammonium hydroxide) is another widely used ORC solution; however, it is corrosive, which means the damage of the materials of RED such as membranes and spacers. An ammonium bicarbonate is a promising thermolytic solution owing to its high solubility in water, large osmotic efficiency, circulation capacity, and relatively low molecular weight [17, 18]. More importantly, ammonium bicarbonate can be recovered with moderate heat, which suggests significant energy advantages compared with the regeneration of other draw solutes. Ammonium bicarbonate has low decomposition temperature, of approximately 60�C at 1 atm, and it decomposes at 120�C. Luo et al. conducted RED experiments by using an ammonium bicarbonate solution under different inlet conditions. They set different feed

systems, low efficiency, and poor form factor in thermoelectric elements [3–9].

A thermal-driven electrochemical generator (TDEG) is illustrated in Figure 1. The TDEG consists of a RED system and a separator based on thermal energy [10]. The mixed diluted

The input parameters used in the model are listed in Table 1.

present in the solution [31]:

Spacer properties

Solution properties

IEMs' properties

a

b

both sides [23].

Diffusivity of water (m<sup>2</sup>

Diffusivity of ammonium bicarbonate (m<sup>2</sup>

CEM Resistance (Ω∙cm2

AEM Resistance (Ω∙cm2

order magnitude), between 1 � <sup>10</sup>�<sup>11</sup> and 1 � <sup>10</sup>�<sup>14</sup> m2

Table 1. Input parameters used in the RED model.

bicarbonate than that of NaCl [30]. Thus, the value of 1 � <sup>10</sup>�<sup>12</sup> m2

When we consider the RED system as an electric circuit, the RED stack exhibits potential difference and internal resistance. Equation (1) shows the potential difference across an IEM between two solutions of different concentration, which is described for all ionic species

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Here, T denotes the temperature, Rg denotes the universal gas constant (8.314 J/mol�K), F denotes the Faraday constant (96485 C/mol), C denotes the concentration of solution, zi

The definition of ionic transport number for species i (ti) is the ionic flux of that species divided by the overall ionic current across the IEM membrane. The electrochemical information of ammonium bicarbonate is needed when calculating equating membrane potential. This is because the equilibrium and ionization constant of ammonium bicarbonate were not clear [27]. Given that Eq. (1) is not intuitive to determine transport number and activity of

/s) <sup>a</sup> <sup>1</sup> � <sup>10</sup>�<sup>12</sup>

) <sup>b</sup> 2 [23]

) <sup>b</sup> 12 [23]

Permselectivity (—) Experiment Thickness (m) 120 [29]

Permselectivity (—) Experiment Thickness (m) 120 [29]

From extant studies [26], the stack performance is not significantly affected by the diffusivity of NaCl for a wide range (two order magnitude). We verified the same tendency on an ammonium bicarbonate electrolyte for a wider range (three

The membrane resistance was measured through the direct current (DC) method at 0.5 M ammonium bicarbonate on

[29]

/s, because of the heavier molecular weight of ammonium

/s is considered as a reliable assumption.

/s) 1.2 � <sup>10</sup>�<sup>9</sup>

denotes the valence number of ion species i, and γ denotes the activity coefficient.

Open ratio (—) 0.56 Porosity (—) 0.74 ð1Þ

171

Figure 1. Schematic illustration of a TDEG. The figure on the left-hand side shows an RED single-cell model, and it has a flow length of L. The solution flows through the channel (thickness δ) with a flow rate of Q.

solution can be separated by applying waste heat in the separator. Then, it will be recaptured in the concentrated solution. Specifically, electricity would be generated when the high concentration and low concentration ammonium bicarbonate solutions flow through each side of the IEM. Meanwhile, ions would pass though the membrane, and the two solutions with different concentrations are mixed. Then, the flow stream would flow into a thermal separator (e.g., a distillation column). Waste heat is utilized in the thermal separator to separate the solute (NH3 and CO2) from the concentration flow stream. The solute from the thermal separator would be recaptured by the high concentration flow stream to form a renewed high concentration flow stream, which is supplied to the RED again. Thus, the renewed high and low concentration streams flow back to the RED stack. The concentration gradient between the different sides of the IEM is maintained. A unit cell pair in RED is composed of a concentrated solution channel, a diluted solution channel, a cation exchange membrane (CEM), and an anion exchange membrane (AEM). The solution concentrations are estimated along the channel with length L and width W in this study.

The present model was developed based on the following four assumptions [25]: (1) the resistance of the IEMs is held at a constant value; (2) the electrode potential of a stack is linearly proportional to the number of cells; (3) the effect of the electrodes at both ends of the stack is neglected; and (4) the inlet flow is uniformly distributed into each channel.

The input parameters used in the model are listed in Table 1.

When we consider the RED system as an electric circuit, the RED stack exhibits potential difference and internal resistance. Equation (1) shows the potential difference across an IEM between two solutions of different concentration, which is described for all ionic species present in the solution [31]:

$$V(z) = \frac{R\_g T}{F} \sum\_i \frac{t\_i}{z\_i} \ln \left( \frac{\boldsymbol{\gamma}\_i^H \boldsymbol{C}\_i^H(z)}{\boldsymbol{\gamma}\_i^L \boldsymbol{C}\_i^L(z)} \right) \tag{1}$$

Here, T denotes the temperature, Rg denotes the universal gas constant (8.314 J/mol�K), F denotes the Faraday constant (96485 C/mol), C denotes the concentration of solution, zi denotes the valence number of ion species i, and γ denotes the activity coefficient.

The definition of ionic transport number for species i (ti) is the ionic flux of that species divided by the overall ionic current across the IEM membrane. The electrochemical information of ammonium bicarbonate is needed when calculating equating membrane potential. This is because the equilibrium and ionization constant of ammonium bicarbonate were not clear [27]. Given that Eq. (1) is not intuitive to determine transport number and activity of


a From extant studies [26], the stack performance is not significantly affected by the diffusivity of NaCl for a wide range (two order magnitude). We verified the same tendency on an ammonium bicarbonate electrolyte for a wider range (three order magnitude), between 1 � <sup>10</sup>�<sup>11</sup> and 1 � <sup>10</sup>�<sup>14</sup> m2 /s, because of the heavier molecular weight of ammonium bicarbonate than that of NaCl [30]. Thus, the value of 1 � <sup>10</sup>�<sup>12</sup> m2 /s is considered as a reliable assumption. b The membrane resistance was measured through the direct current (DC) method at 0.5 M ammonium bicarbonate on both sides [23].

Table 1. Input parameters used in the RED model.

solution can be separated by applying waste heat in the separator. Then, it will be recaptured in the concentrated solution. Specifically, electricity would be generated when the high concentration and low concentration ammonium bicarbonate solutions flow through each side of the IEM. Meanwhile, ions would pass though the membrane, and the two solutions with different concentrations are mixed. Then, the flow stream would flow into a thermal separator (e.g., a distillation column). Waste heat is utilized in the thermal separator to separate the solute (NH3 and CO2) from the concentration flow stream. The solute from the thermal separator would be recaptured by the high concentration flow stream to form a renewed high concentration flow stream, which is supplied to the RED again. Thus, the renewed high and low concentration streams flow back to the RED stack. The concentration gradient between the different sides of the IEM is maintained. A unit cell pair in RED is composed of a concentrated solution channel, a diluted solution channel, a cation exchange membrane (CEM), and an anion exchange membrane (AEM). The solution concentrations are estimated along the chan-

Figure 1. Schematic illustration of a TDEG. The figure on the left-hand side shows an RED single-cell model, and it has a

flow length of L. The solution flows through the channel (thickness δ) with a flow rate of Q.

The present model was developed based on the following four assumptions [25]: (1) the resistance of the IEMs is held at a constant value; (2) the electrode potential of a stack is linearly proportional to the number of cells; (3) the effect of the electrodes at both ends of the stack is

neglected; and (4) the inlet flow is uniformly distributed into each channel.

nel with length L and width W in this study.

170 Organic Rankine Cycle Technology for Heat Recovery

ammonium bicarbonate compared with NaCl [25, 26, 30, 32], Huang et al. adopted the Planck-Henderson equation to compute the membrane potential as below [27, 31]:

$$\mathcal{V}(\mathbf{z}) \approx \frac{R\_g T}{F} \frac{\sum \frac{|\mathbf{z}\_i| u\_i}{\mathbf{z}\_i} \left[ C\_i^L(\mathbf{z}) - C\_i^H(\mathbf{z}) \right]}{\sum |\mathbf{z}\_i| u\_i \left[ C\_i^L(\mathbf{z}) - C\_i^H(\mathbf{z}) \right]} \ln \left( \frac{\sum |\mathbf{z}\_i| u\_i C\_i^H(\mathbf{z})}{\sum |\mathbf{z}\_i| u\_i C\_i^L(\mathbf{z})} \right) \tag{2}$$

In this equation, we assume that the activity of each species is proportional to the ionic mobility (ui) and the molar concentration (Ci). Here, we assume that the valence number of all electrolytes in the ammonium bicarbonate solution is dominantly monovalent (+1 or �1) which can be measured by the pH of the solution [27].

For the binary electrolyte, Eq. (2) is transformed into Eq. (3) by imposing the electrical conductivity described in Eq. (4) and the permselectivity of the IEM [33–39]:

$$V \approx \alpha\_{\rm{lEM}} \frac{R\_{\rm{g}} T}{F} \ln \left( \frac{\kappa^{H}}{\kappa^{L}} \right) \tag{3}$$

$$\kappa = F \sum |z\_i| \mu\_i C\_i \tag{4}$$

current value is divided by the projecting membrane area. The factor 1/2 is related to the pair

Figure 2. Electrical conductivity of ammonium bicarbonate solution for various concentrations. The red dashed line

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Finally, the power output and power density of the system can be calculated as Eq. (8): P zð Þ¼ I zð Þ<sup>2</sup>

Equation (10) shows the total solute transportation (flux) in the system. The total solute flux (Js) can be divided into two different parts. The first term of the right-hand side of the equation indicates the counter-ion transport through the membrane, and it is the coulombic part. The other term in the right-hand side shows the co-ion transport. The co-ion transport can be expressed by the diffusivity (DAmBi) of ammonium bicarbonate and the ion exchange mem-

Another mass transport phenomenon that happens in the system is water flux across the membrane, which is in the opposite direction owing to the osmosis [29] caused by the concen-

ð7Þ

173

ð9Þ

ð10Þ

Rload (8)

membrane area (CEM and AEM) in a cell as follows:

denotes a third order regression line and R<sup>2</sup> = 0.99.

brane thickness (h) [25]:

tration difference across the IEM;

The total internal resistance in the system is computed by the following Eq. (5):

$$R\_{\rm ohmic}(\mathbf{z}) = \frac{\mathbf{1}}{\mathcal{J}} \left( \mathbf{R}\_{\rm CEM} + \mathbf{R}\_{\rm AEM} + \frac{\delta\_H}{\Lambda\_H(\mathbf{z}) \mathbf{C}\_H(\mathbf{z})} + \frac{\delta\_L}{\Lambda\_L(\mathbf{z}) \mathbf{C}\_L(\mathbf{z})} \right) \tag{5}$$

Here, δ denotes the thickness of the channels, β denotes an open ratio of the spacer, and Λ denotes the molar conductivity of the solutions. The third and fourth terms in the right-hand side denote the resistance of the solution bodies. RCEM and RAEM denote the resistances of the IEMs measured by the direct current method under standard conditions [23, 39].

The previous Falkenhagen-Leist-Kelbg (FLK) equation describes the molar conductivity generally based on an NaCl solution, and here, we modified it for the case of ammonium bicarbonate [26, 32]. We utilized empirical values by using the definition of electrical conductivity of ammonium bicarbonate (Λ ¼ κ=C) obtained by conductivity measurements as shown in Figure 2. The Arrhenius law [40] shows that if a temperature variation exists, then a new electrical conductivity profile must be established such that the electrical conductivity increases with the increase in temperature based on the Arrhenius law [40].

The current value is calculated by Ohm's law, which is based on the system voltage and resistance, as follows:

$$I(z) = \frac{V\_{OC}(z)}{R\_{\text{int}}(z) + R\_{\text{load}}} \tag{6}$$

Here, the subscripts int and load mean the internal resistance of the cell and external resistance, respectively. The current density i is obtained by integrating I(z) along the channel. Then, the

Power Generation with Thermolytic Reverse Electrodialysis for Low-Grade Waste Heat Recovery http://dx.doi.org/10.5772/intechopen.81006 173

ammonium bicarbonate compared with NaCl [25, 26, 30, 32], Huang et al. adopted the Planck-

In this equation, we assume that the activity of each species is proportional to the ionic mobility (ui) and the molar concentration (Ci). Here, we assume that the valence number of all electrolytes in the ammonium bicarbonate solution is dominantly monovalent (+1 or �1)

For the binary electrolyte, Eq. (2) is transformed into Eq. (3) by imposing the electrical conduc-

Here, δ denotes the thickness of the channels, β denotes an open ratio of the spacer, and Λ denotes the molar conductivity of the solutions. The third and fourth terms in the right-hand side denote the resistance of the solution bodies. RCEM and RAEM denote the resistances of the

The previous Falkenhagen-Leist-Kelbg (FLK) equation describes the molar conductivity generally based on an NaCl solution, and here, we modified it for the case of ammonium bicarbonate [26, 32]. We utilized empirical values by using the definition of electrical conductivity of ammonium bicarbonate (Λ ¼ κ=C) obtained by conductivity measurements as shown in Figure 2. The Arrhenius law [40] shows that if a temperature variation exists, then a new electrical conductivity profile must be established such that the electrical conductivity

The current value is calculated by Ohm's law, which is based on the system voltage and

Here, the subscripts int and load mean the internal resistance of the cell and external resistance, respectively. The current density i is obtained by integrating I(z) along the channel. Then, the

δ<sup>H</sup> ΛHð Þz CHð Þz

þ

δL ΛLð Þz CLð Þz ð2Þ

ð3Þ

ð4Þ

(5)

ð6Þ

Henderson equation to compute the membrane potential as below [27, 31]:

which can be measured by the pH of the solution [27].

1

Rohmicð Þ¼ z

172 Organic Rankine Cycle Technology for Heat Recovery

resistance, as follows:

tivity described in Eq. (4) and the permselectivity of the IEM [33–39]:

The total internal resistance in the system is computed by the following Eq. (5):

IEMs measured by the direct current method under standard conditions [23, 39].

increases with the increase in temperature based on the Arrhenius law [40].

<sup>β</sup> RCEM <sup>þ</sup> RAEM <sup>þ</sup>

Figure 2. Electrical conductivity of ammonium bicarbonate solution for various concentrations. The red dashed line denotes a third order regression line and R<sup>2</sup> = 0.99.

current value is divided by the projecting membrane area. The factor 1/2 is related to the pair membrane area (CEM and AEM) in a cell as follows:

$$\dot{i} = \frac{\sum\_{z=0}^{L} I(z)dz}{2LW} \tag{7}$$

Finally, the power output and power density of the system can be calculated as Eq. (8):

$$\mathbf{P}(\mathbf{z}) = \mathbf{I}(\mathbf{z})^2 \mathbf{R}\_{load} \tag{8}$$

$$\sum\_{z=0}^{L} P(z)dz$$

$$p = \frac{\sum\_{z=0}^{L} P(z)dz}{2LW} \tag{9}$$

Equation (10) shows the total solute transportation (flux) in the system. The total solute flux (Js) can be divided into two different parts. The first term of the right-hand side of the equation indicates the counter-ion transport through the membrane, and it is the coulombic part. The other term in the right-hand side shows the co-ion transport. The co-ion transport can be expressed by the diffusivity (DAmBi) of ammonium bicarbonate and the ion exchange membrane thickness (h) [25]:

$$J\_s(z) = \frac{i(z)}{F} + \left(\frac{D\_{AmBi}}{h\_{CM}} + \frac{D\_{AmBi}}{h\_{AEM}}\right) \left(C\_H(z) - C\_L(z)\right) \tag{10}$$

Another mass transport phenomenon that happens in the system is water flux across the membrane, which is in the opposite direction owing to the osmosis [29] caused by the concentration difference across the IEM;

$$J\_w(z) = -\left(\frac{D\_w}{h\_{CM}} + \frac{D\_w}{h\_{AEM}}\right) \left(C\_H(z) - C\_L(z)\right) \tag{11}$$

Here, Dw denotes the water diffusivity.

The concentration profile along the flow channel is calculated by mass conservation equations for an infinitesimal control volume as follows [25]:

$$\frac{dC\_H}{dz}(z) = -\frac{W}{\mathcal{Q}\_H} J\_s(z) + C\_H(z) \frac{W}{\mathcal{Q}\_H} J\_w(z) V\_\ast \tag{12}$$

$$\frac{dC\_L}{dz}(z) = \frac{W}{Q\_L} J\_s(z) - C\_L(z) \frac{W}{Q\_L} J\_w(z) V\_w \tag{13}$$

Here, Vw denotes the water molar density.

First, the feed solution concentration and solution flow rate are assigned to the model as the input conditions. Second, the local electric variables are calculated. Finally, the next node concentration is obtained through Eqs. (12) and (13) with the solute and water transport. The backward finite difference approximation with a node size of dz = L/3000 is applied.

#### 3. Experimental approach

#### 3.1. Experimental setup for RED

In the experiment, instead of NaCl, ammonium bicarbonate (11213, Sigma-Aldrich) was used. Figure 3(a) illustrates the RED stack, which includes two electrodes combined with endplates, CEMs and AEMs, silicon gaskets, and polymer spacers. The endplates were fabricated with polymethyl methacrylate (PMMA). The electrodes combined with the endplates were fabricated by titanium and coated with iridium and ruthenium. The calibration of the membranes (CMV/ AMV, Asahi glass) was performed in a 0.6 M NH4HCO solution for more than 24 h after washed by deionized water. The RED stack consists of five cells, and the effective membrane area was 49 cm2 . The polymer spacers (PETEX 06–745/56, Sefar) were used as the channel supporter, and the vertical material exchange is precipitated in the channel to prevent forming the boundary layer. The gaskets were composed of silicone rubber sheets with a thickness of 0.3 mm. The gaskets and spacers were cut in the desired 5 M K4 Fe(CN)6 (31254, Sigma-Aldrich), 0.05 M K3Fe (CN)6 (31253, Sigma-Aldrich), 0.05 K4Fe(CN)6 (31254, Sigma-Aldrich), and 0.3 M NH4HCO3. Those experiments were carried out at the room temperature of 25 � 0.3�C.

Figure 3(b) shows the RED experimental setup. All the solutions were fed by peristaltic pumps (EMP-2000 W, EMS Tech). A four-wire mode cable was connected to the electrodes, and a source meter (2410, Keithley) was employed to measure the RED performance. We used polarization and power density curves to characterize the RED system electrochemical performance. We measured the terminal voltage over the stack by the galvanostat method with the current variation in a step-like way of 10 mA. The power density curve is determined

Figure 3. Schematic illustration of (a) the RED stack and (b) the RED experimental setup. The red and purple colors in the

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schematic indicate the cation and anion, respectively (e.g., cation or cation exchange membrane).

In previous studies related to the RED numerical model, permselectivity was assumed as either unity or a constant value. However, it was reported that the permselectivity of an IEM

according to the voltage and the current density.

3.2. Membrane potential measurement

Figure 3. Schematic illustration of (a) the RED stack and (b) the RED experimental setup. The red and purple colors in the schematic indicate the cation and anion, respectively (e.g., cation or cation exchange membrane).

current variation in a step-like way of 10 mA. The power density curve is determined according to the voltage and the current density.

#### 3.2. Membrane potential measurement

ð11Þ

ð12Þ

ð13Þ

Here, Dw denotes the water diffusivity.

174 Organic Rankine Cycle Technology for Heat Recovery

Here, Vw denotes the water molar density.

3. Experimental approach

3.1. Experimental setup for RED

49 cm2

for an infinitesimal control volume as follows [25]:

The concentration profile along the flow channel is calculated by mass conservation equations

First, the feed solution concentration and solution flow rate are assigned to the model as the input conditions. Second, the local electric variables are calculated. Finally, the next node concentration is obtained through Eqs. (12) and (13) with the solute and water transport. The

In the experiment, instead of NaCl, ammonium bicarbonate (11213, Sigma-Aldrich) was used. Figure 3(a) illustrates the RED stack, which includes two electrodes combined with endplates, CEMs and AEMs, silicon gaskets, and polymer spacers. The endplates were fabricated with polymethyl methacrylate (PMMA). The electrodes combined with the endplates were fabricated by titanium and coated with iridium and ruthenium. The calibration of the membranes (CMV/ AMV, Asahi glass) was performed in a 0.6 M NH4HCO solution for more than 24 h after washed by deionized water. The RED stack consists of five cells, and the effective membrane area was

. The polymer spacers (PETEX 06–745/56, Sefar) were used as the channel supporter, and the vertical material exchange is precipitated in the channel to prevent forming the boundary layer. The gaskets were composed of silicone rubber sheets with a thickness of 0.3 mm. The gaskets and spacers were cut in the desired 5 M K4 Fe(CN)6 (31254, Sigma-Aldrich), 0.05 M K3Fe (CN)6 (31253, Sigma-Aldrich), 0.05 K4Fe(CN)6 (31254, Sigma-Aldrich), and 0.3 M NH4HCO3.

Figure 3(b) shows the RED experimental setup. All the solutions were fed by peristaltic pumps (EMP-2000 W, EMS Tech). A four-wire mode cable was connected to the electrodes, and a source meter (2410, Keithley) was employed to measure the RED performance. We used polarization and power density curves to characterize the RED system electrochemical performance. We measured the terminal voltage over the stack by the galvanostat method with the

Those experiments were carried out at the room temperature of 25 � 0.3�C.

backward finite difference approximation with a node size of dz = L/3000 is applied.

In previous studies related to the RED numerical model, permselectivity was assumed as either unity or a constant value. However, it was reported that the permselectivity of an IEM

Figure 4. Schematic illustration of the experimental setup to determine the permselectivity of the IEM.

varies with different combinations of the concentrated and diluted solutions [22, 27, 36, 41]. Therefore, to predict the RED performance more precisely, we applied the actual permselectivity of the IEMs as follows.

The permselectivity is calculated by the following equation [39]:

$$
\alpha = \frac{\Delta V\_{\text{actual}}}{\Delta V\_{\text{theoretical}}} \tag{14}
$$

concentration of the diluted solution was kept constant at 0.01 M. The concentration of the concentrated solution changed with concentration ratios of 5, 10, 50, 100, 150, and 200. The measured membrane potentials of CMV are greater than those of AMV for most cases caused by the higher constant charge density of CMV [44–46]. Calculated by Eq. (14), the permselectivity of the CMV drops from 0.952 to 0.888. Moreover, the membrane potential of AMV also monotonously decreased from 0.959 to 0.866 with an increase in concentration ratio. This tendency can be explained by two reasons. First, the concentration difference induces osmotic dwelling, which is when strong osmotic cling occurs because of high osmotic pressure between the membrane's internal solution and the bulk solution [22, 41, 47, 48]. Next, the possibility of co-ions percolation rises to a higher degree with a higher concentration ratio gradient due to an increase of the CP phenomena, and this leads to an increase at a higher concentration difference ratio [30, 41, 43]. A new data set of the permselectivity is acquired when the operating temperature varies. For the electrical conductivity, a similar way should be followed. Because the mechanism of an interaction between ions and membranes is too complexed, the effects of the temperature on the permselectivity is partly studied based on the temperature dependence

Figure 5. Comparison of the experimental membrane potential data (circular and triangular symbols) and the solution

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We calculated the open circuit voltage (OCV) obtained at zero current by applying the actual permselectivity of the IEMs obtained from Figure 5. We compared it with the experimental data. A comparison of the OCVs between the calculation and the experiment is displayed in Figure 6. The red and black bars represent the simulated and measured values of the OCV, respectively. The flow rate was fixed at 10 mL/min for each cell. The tendency of the simulation results shows in good agreement with the tendency of the experimental results, although the simulation values are slightly higher in all cases. This is due to two main reasons: (1) the uniform flow distribution for the experimental case was not the same completely because of the flow stream variation due to the effect of flow inlet and outlet branches, leading to the

of the diffusivity of each ion [49, 50].

conductivity-based estimation by using Eq. (4).

To calculate permselectivity, a simple experiment was needed to measure the IEM potential. Figure 4 shows the method we used to measure permselectivity. Two reservoirs contain solutions with different concentration combinations. Two reference electrodes and an IEM are inserted between the reservoirs [42, 43]. Ag/AgCl is used as reference electrode, as it has a very low potential. The total area of the IEM was 0.785 cm<sup>2</sup> , and the solution contained in each reservoir was 100 mL. In order to reduce the CP effect, the solutions were circulated, and the membrane potential was measured by the Ag/AgCl electrodes after 15–30 min when the system reached a steady state [39].

#### 4. Results and discussion

#### 4.1. Application of actual permselectivity

In Figure 5, the conductivity-based estimation of the membrane potential is presented with a blue line, which is calculated by Eq. (4). Here, α is set to unity. The experimental membrane potentials across each IEM are denoted as circular and triangular symbols. For each case, the

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Figure 5. Comparison of the experimental membrane potential data (circular and triangular symbols) and the solution conductivity-based estimation by using Eq. (4).

varies with different combinations of the concentrated and diluted solutions [22, 27, 36, 41]. Therefore, to predict the RED performance more precisely, we applied the actual permselectivity

Figure 4. Schematic illustration of the experimental setup to determine the permselectivity of the IEM.

To calculate permselectivity, a simple experiment was needed to measure the IEM potential. Figure 4 shows the method we used to measure permselectivity. Two reservoirs contain solutions with different concentration combinations. Two reference electrodes and an IEM are inserted between the reservoirs [42, 43]. Ag/AgCl is used as reference electrode, as it has a very

reservoir was 100 mL. In order to reduce the CP effect, the solutions were circulated, and the membrane potential was measured by the Ag/AgCl electrodes after 15–30 min when the

In Figure 5, the conductivity-based estimation of the membrane potential is presented with a blue line, which is calculated by Eq. (4). Here, α is set to unity. The experimental membrane potentials across each IEM are denoted as circular and triangular symbols. For each case, the

ð14Þ

, and the solution contained in each

The permselectivity is calculated by the following equation [39]:

low potential. The total area of the IEM was 0.785 cm<sup>2</sup>

system reached a steady state [39].

4. Results and discussion

4.1. Application of actual permselectivity

of the IEMs as follows.

176 Organic Rankine Cycle Technology for Heat Recovery

concentration of the diluted solution was kept constant at 0.01 M. The concentration of the concentrated solution changed with concentration ratios of 5, 10, 50, 100, 150, and 200. The measured membrane potentials of CMV are greater than those of AMV for most cases caused by the higher constant charge density of CMV [44–46]. Calculated by Eq. (14), the permselectivity of the CMV drops from 0.952 to 0.888. Moreover, the membrane potential of AMV also monotonously decreased from 0.959 to 0.866 with an increase in concentration ratio. This tendency can be explained by two reasons. First, the concentration difference induces osmotic dwelling, which is when strong osmotic cling occurs because of high osmotic pressure between the membrane's internal solution and the bulk solution [22, 41, 47, 48]. Next, the possibility of co-ions percolation rises to a higher degree with a higher concentration ratio gradient due to an increase of the CP phenomena, and this leads to an increase at a higher concentration difference ratio [30, 41, 43]. A new data set of the permselectivity is acquired when the operating temperature varies. For the electrical conductivity, a similar way should be followed. Because the mechanism of an interaction between ions and membranes is too complexed, the effects of the temperature on the permselectivity is partly studied based on the temperature dependence of the diffusivity of each ion [49, 50].

We calculated the open circuit voltage (OCV) obtained at zero current by applying the actual permselectivity of the IEMs obtained from Figure 5. We compared it with the experimental data. A comparison of the OCVs between the calculation and the experiment is displayed in Figure 6. The red and black bars represent the simulated and measured values of the OCV, respectively. The flow rate was fixed at 10 mL/min for each cell. The tendency of the simulation results shows in good agreement with the tendency of the experimental results, although the simulation values are slightly higher in all cases. This is due to two main reasons: (1) the uniform flow distribution for the experimental case was not the same completely because of the flow stream variation due to the effect of flow inlet and outlet branches, leading to the

Figure 6. Comparison of the OCV obtained from the simulation and experiment.

production of additional shadow areas [32]. (2) The gaseous bubble (CO2, NH3) which is promoted under the room temperature degraded the system performance, while it was not considered in this study [17, 51].

Figure 7 shows the effect of actual permselectivity on RED performance when the concentrated and diluted solutions were fixed as 1 and 0.01 mol, respectively. Figure 7(a) and (b) show the polarization curves when applying actual permselectivity, and Figure 7(c) and (d) present the power density curves, calculated with α = 1 and the experimentally obtained value α = 0.891, respectively. The experimental result is the average of the actual permselectivity of CEM and AEM. The maximum difference of the power density between the calculated and experimental results was 0.2 W/m<sup>2</sup> . When we considered the actual permselectivity (in the experiments), however, the gap was reduced to 0.04 W/m<sup>2</sup> (0.5%). Therefore, the consideration of the actual permselectivity plays a critical role in modeling the RED process with ammonium bicarbonate.

#### 4.2. Model validation with experiments

We numerically and experimentally evaluated the power density based on the variation of concentration ratio. The evaluation results are shown in Figure 8. In the six cases evaluated, the concentrated solution varied, while the diluted solution was fixed as constant at 0.01 M. The intermembrane distance was 0.3 mm, and the feed flow rate was fixed as 10 mL/min for each cell. The dashed lines represent the simulation results, and the symbols represent the experimental results. When the concentrated solution was equal to or exceeded 1 M, then all the simulation results of the power density curve fall in the error bar area. However, the simulation results deviated from the error bars when the concentrated solution was 0.5 M or less. This phenomenon could be caused by the lower concentration of the concentrated solution which induces an increase of the membrane resistance [24, 52].

The change time of the solution in the flow channel depends on the solution feed flow rate. This results in the change of OCV difference between the concentrated and diluted solutions. The influence of the flow rate on the RED system power density and the OCV were estimated.

Figure 8. Power density curves with varying concentration ratios. The dashed lines denote the simulation results, and the

Figure 7. Polarization curves (a) and (b) and power density curves (c) and (d), with actual and ideal permselectivity of the IEM.

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symbols denote the experimental results.

Power Generation with Thermolytic Reverse Electrodialysis for Low-Grade Waste Heat Recovery http://dx.doi.org/10.5772/intechopen.81006 179

Figure 7. Polarization curves (a) and (b) and power density curves (c) and (d), with actual and ideal permselectivity of the IEM.

production of additional shadow areas [32]. (2) The gaseous bubble (CO2, NH3) which is promoted under the room temperature degraded the system performance, while it was not

Figure 6. Comparison of the OCV obtained from the simulation and experiment.

Figure 7 shows the effect of actual permselectivity on RED performance when the concentrated and diluted solutions were fixed as 1 and 0.01 mol, respectively. Figure 7(a) and (b) show the polarization curves when applying actual permselectivity, and Figure 7(c) and (d) present the power density curves, calculated with α = 1 and the experimentally obtained value α = 0.891, respectively. The experimental result is the average of the actual permselectivity of CEM and AEM. The maximum difference of the power density between the calculated and

experiments), however, the gap was reduced to 0.04 W/m<sup>2</sup> (0.5%). Therefore, the consideration of the actual permselectivity plays a critical role in modeling the RED process with ammonium

We numerically and experimentally evaluated the power density based on the variation of concentration ratio. The evaluation results are shown in Figure 8. In the six cases evaluated, the concentrated solution varied, while the diluted solution was fixed as constant at 0.01 M. The intermembrane distance was 0.3 mm, and the feed flow rate was fixed as 10 mL/min for each cell. The dashed lines represent the simulation results, and the symbols represent the experimental results. When the concentrated solution was equal to or exceeded 1 M, then all the simulation results of the power density curve fall in the error bar area. However, the simulation results deviated from the error bars when the concentrated solution was 0.5 M or less. This phenomenon could be caused by the lower concentration of the concentrated solu-

tion which induces an increase of the membrane resistance [24, 52].

. When we considered the actual permselectivity (in the

considered in this study [17, 51].

178 Organic Rankine Cycle Technology for Heat Recovery

experimental results was 0.2 W/m<sup>2</sup>

4.2. Model validation with experiments

bicarbonate.

Figure 8. Power density curves with varying concentration ratios. The dashed lines denote the simulation results, and the symbols denote the experimental results.

The change time of the solution in the flow channel depends on the solution feed flow rate. This results in the change of OCV difference between the concentrated and diluted solutions. The influence of the flow rate on the RED system power density and the OCV were estimated.

4.3. RED system performance prediction and optimization

The flow rate and the intermembrane distance terms in Eqs. (5), (12), and (13) are vital parameters of the RED system. These two parameters influence the residence time in such a way that they control the mixing rate and the internal resistance of the system. In the part, the RED performance in terms of the flow rate and the intermembrane distance was validated by using the aforementioned model. Figure 10(a) shows the power density relative to the intermembrane distance. The feed solution flow rate in the channel was set at a constant value of 10 mL/min. Both intermembrane distances for the two compartments were varied from 0.02 to 1 mm. The rich and lean solutions were configured at 2 and 0.01 M, respectively. When the

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Figure 10. Three different power densities (Pd) of RED relative to (a) intermembrane distance and (b) flow rate.

Figure 9. (a) OCV and (b) power density with varying flow rates.

The power density is given in Figure 9(a) where the OCV was varied with the solution flow rate simulated from 0.1 mL to 20 mL/min. The diluted and concentrated solutions were kept constant at 2 and 0.01 M, respectively. The intermembrane distance was configured at 0.3 mm. The OCV was increased rapidly below 2 mL/min. Then, it was almost saturated when the flow rate was over 5 mL/min. It shows that the calculated results quite match with the experimental ones.

Figure 9(b) shows the effect of flow rate on power density of the system. The simulation results of power density also showed a slightly different trend from that of OCV. It firstly showed a steep increase below 2 mL/min and then showed a maximum value at a flow rate value of 8 mL/min. After the power density reached a maximum value, it decreased gradually. Overall, the simulation can predict the power density trend very well.

#### 4.3. RED system performance prediction and optimization

The flow rate and the intermembrane distance terms in Eqs. (5), (12), and (13) are vital parameters of the RED system. These two parameters influence the residence time in such a way that they control the mixing rate and the internal resistance of the system. In the part, the RED performance in terms of the flow rate and the intermembrane distance was validated by using the aforementioned model. Figure 10(a) shows the power density relative to the intermembrane distance. The feed solution flow rate in the channel was set at a constant value of 10 mL/min. Both intermembrane distances for the two compartments were varied from 0.02 to 1 mm. The rich and lean solutions were configured at 2 and 0.01 M, respectively. When the

Figure 10. Three different power densities (Pd) of RED relative to (a) intermembrane distance and (b) flow rate.

The power density is given in Figure 9(a) where the OCV was varied with the solution flow rate simulated from 0.1 mL to 20 mL/min. The diluted and concentrated solutions were kept constant at 2 and 0.01 M, respectively. The intermembrane distance was configured at 0.3 mm. The OCV was increased rapidly below 2 mL/min. Then, it was almost saturated when the flow rate was over 5 mL/min. It shows that the calculated results quite match with the experimental

Figure 9(b) shows the effect of flow rate on power density of the system. The simulation results of power density also showed a slightly different trend from that of OCV. It firstly showed a steep increase below 2 mL/min and then showed a maximum value at a flow rate value of 8 mL/min. After the power density reached a maximum value, it decreased gradually. Overall,

the simulation can predict the power density trend very well.

Figure 9. (a) OCV and (b) power density with varying flow rates.

180 Organic Rankine Cycle Technology for Heat Recovery

ones.

intermembrane distance was less than 0.5 mm, the power density is increased evidently and arrived at 1.8 W/m<sup>2</sup> at an intermembrane distance of 0.02 mm.

Here, we also considered the pumping loss in the RED system. This can help us to develop the actual RED system in practice [53, 54]. The pumping loss is proportional to the pressure drop, Δp, between the inlet and outlet of the channel, while the flow rate Q is inversely proportional to the pump efficiency, ηpump, as listed in Eq. (15):

$$P\_{pump}^{RED} = \frac{\Delta p\_H \mathcal{Q}\_H^{RED} + \Delta p\_L \mathcal{Q}\_L^{RED}}{\eta\_{pump}} \tag{15}$$

The pumping loss can be normalized to the effective ion exchange area as Eq. (16):

$$p\_{pump}^{RED} = \frac{P\_{pump}^{RED}}{2LW} \tag{16}$$

The pressure drop was modeled as the well-known Darcy-Weisbach equation, which considers the effect of the spacer [54], as follows:

$$
\Delta p = \frac{12\,\mu L^2}{0.25d\_h^2 t} \tag{17}
$$

$$d\_h = \frac{4n}{\left(\frac{2}{\mathcal{S}}\right) + (1 - n)\left(\frac{8}{\mathcal{S}}\right)}\tag{18}$$

to the concentration ratio. For the case of δ = 0.3 mm, the performance was less sensitive to the

Figure 11. Optimization of net power density with changes in flow rate and concentration ratio. The intermembrane

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An ammonium bicarbonate-based RED system operating as a closed-loop system was designed to convert low-grade waste heat into electricity. It is possible to harness a variety of waste heat such as released from industrial plants and vehicles or generated by geothermal and solar heat. In this chapter, a mathematical model for the power generation from a RED system used NH4HCO3 instead of NaCl. The properties of NH4HCO3 were used, and the activity of NH4HCO3 in the Nernst equation was substituted by the electrical conductivity via the Planck-Henderson equation. The molar conductivity of NH4HCO3 was also replaced by a calculated value. To predict the performance of the RED system, it is very important to

measure the membrane potential precisely so as to obtain the actual permselectivity.

flow rate, whereas it was more sensitive to the concentration ratio.

distances (δ) are (a) 0.1, (b) 0.2, and (c) 0.3 mm, and the diluted solution was fixed at 0.01 M.

5. Conclusion

Here, μ denotes the viscosity (25�C), and dh denotes the hydraulic diameter considering the effect of the spacer porosity n.

Figure 10(a) shows the effect of intermembrane distance on power density including the pumping loss. The pumping loss increases greatly when the intermembrane distance is smaller than 0.3 mm. We calculated the power density by subtracting the pumping loss from the total power. The net power density reached a maximum value at the intermembrane distance of 0.2 mm, and then, it was reduced to below zero at 0.1 mm. This is due to the high pumping loss. Figure 10(b) shows the relation between the power density and the flow rate when the intermembrane distance was specified at 0.3 mm, and the rich and lean solutions were 2 and 0.01 M, respectively. The highest power density value was 0.76 W/m2 at a flow rate of 6 mL/min. The optimal value of 0.73 W/m2 for the net power density was obtained at a flow rate of 4 mL/min. Afterwards, the power density decreased gradually.

Figure 11 shows the effects of the intermembrane distance (δ), the flow rate (Q), and the concentration ratio on the net power density. In this figure, the net power densities arrived their maximum values of 0.85 W/m<sup>2</sup> at δ = 0.1 mm and Q = 3 mL/min, 0.82 W/m<sup>2</sup> at δ = 0.2 mm and Q = 4 mL/min, and 0.73 W/m2 at δ = 0.3 mm and Q = 5 mL/min.

The highest net power density is obtained when δ = 0.1 mm. The flow rate has a very important impact on the system performance due to the high pumping loss. However, it is less sensitive

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Figure 11. Optimization of net power density with changes in flow rate and concentration ratio. The intermembrane distances (δ) are (a) 0.1, (b) 0.2, and (c) 0.3 mm, and the diluted solution was fixed at 0.01 M.

to the concentration ratio. For the case of δ = 0.3 mm, the performance was less sensitive to the flow rate, whereas it was more sensitive to the concentration ratio.

#### 5. Conclusion

intermembrane distance was less than 0.5 mm, the power density is increased evidently and

Here, we also considered the pumping loss in the RED system. This can help us to develop the actual RED system in practice [53, 54]. The pumping loss is proportional to the pressure drop, Δp, between the inlet and outlet of the channel, while the flow rate Q is inversely proportional

The pressure drop was modeled as the well-known Darcy-Weisbach equation, which considers

Here, μ denotes the viscosity (25�C), and dh denotes the hydraulic diameter considering the

Figure 10(a) shows the effect of intermembrane distance on power density including the pumping loss. The pumping loss increases greatly when the intermembrane distance is smaller than 0.3 mm. We calculated the power density by subtracting the pumping loss from the total power. The net power density reached a maximum value at the intermembrane distance of 0.2 mm, and then, it was reduced to below zero at 0.1 mm. This is due to the high pumping loss. Figure 10(b) shows the relation between the power density and the flow rate when the intermembrane distance was specified at 0.3 mm, and the rich and lean solutions were 2 and 0.01 M, respectively. The highest power density value was 0.76 W/m2 at a flow rate of 6 mL/min. The optimal value of 0.73 W/m2 for the net power density was obtained at a flow rate of 4 mL/min.

Figure 11 shows the effects of the intermembrane distance (δ), the flow rate (Q), and the concentration ratio on the net power density. In this figure, the net power densities arrived their maximum values of 0.85 W/m<sup>2</sup> at δ = 0.1 mm and Q = 3 mL/min, 0.82 W/m<sup>2</sup> at δ = 0.2 mm

The highest net power density is obtained when δ = 0.1 mm. The flow rate has a very important impact on the system performance due to the high pumping loss. However, it is less sensitive

The pumping loss can be normalized to the effective ion exchange area as Eq. (16):

ð15Þ

ð16Þ

ð17Þ

ð18Þ

arrived at 1.8 W/m<sup>2</sup> at an intermembrane distance of 0.02 mm.

to the pump efficiency, ηpump, as listed in Eq. (15):

182 Organic Rankine Cycle Technology for Heat Recovery

the effect of the spacer [54], as follows:

effect of the spacer porosity n.

Afterwards, the power density decreased gradually.

and Q = 4 mL/min, and 0.73 W/m2 at δ = 0.3 mm and Q = 5 mL/min.

An ammonium bicarbonate-based RED system operating as a closed-loop system was designed to convert low-grade waste heat into electricity. It is possible to harness a variety of waste heat such as released from industrial plants and vehicles or generated by geothermal and solar heat. In this chapter, a mathematical model for the power generation from a RED system used NH4HCO3 instead of NaCl. The properties of NH4HCO3 were used, and the activity of NH4HCO3 in the Nernst equation was substituted by the electrical conductivity via the Planck-Henderson equation. The molar conductivity of NH4HCO3 was also replaced by a calculated value. To predict the performance of the RED system, it is very important to measure the membrane potential precisely so as to obtain the actual permselectivity.

The model simulation showed an accurate estimation of the OCV within a wide range of flow rates and concentration ratios. The simulation results also fit well for power density with the experimental results relative to the various flow rates and concentration ratios. Especially, when the concentrated solution is equal to or exceeds 1 M, which is a preferable operating condition for high power generation. The difference between the simulation and experiment for the solution with lower concentration could be potentially attributed to the concentration of electrolytes, which affects the membrane resistance. The improvement in the membrane resistance model with the concentration variation is an interesting topic in order to obtain a better estimation.

V electric voltage [V]

dh hydraulic diameter [m] h membrane thickness [m]

i current density [A/m2

p power density [W/m<sup>2</sup>

t residence time [s]

Δp pressure drop [Pa]

α permselectivity [-]

γ activity coefficient [-]

ε permittivity [F/m]

ηpump pump efficiency [-]

μ viscosity [Pa�s]

Subscripts

Acronyms

δ intermembrane distance [m]

H high concentration solution L low concentration solution CEM cation exchange membrane AEM anion exchange membrane

RED reverse electrodialysis

4Ha Ammonium bicarbonate ORC organic Rankine cycle

β open ratio [-]

<sup>Λ</sup> molar conductivity [S�m2

W width [m]

n porosity [-]

Greek symbols

Vw molar volume of water [mol/m3

ti transport number of ion species i [-]

zi valence number of ion species i [-]

]

]

/mol]

]

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We evaluated the net power density through the validated model including the pumping loss as a function of the flow rate, intermembrane distance, and concentration ratio. Consequently, the best performance for the working parameters was obtained. When we fixed the intermembrane distance at 0.1 mm and the flow rate was 3 mL/min, we obtained the highest net power density of 0.84 W/m2 with the feed solution concentration ratio was 200 (2 M/0.01 M).

The results of this study can help to improve our understanding of the RED system with ammonium bicarbonate. This study also provides a good reference for the RED system modeling to get a higher energy density by using NH4HCO3 or other compounds.

## Acknowledgements

The study was supported by a National Research Foundation of Korea (NRF) grant funded by the Korean government (MEST) (No. NRF-2014R1A2A2A01003618).

## Nomenclature


Power Generation with Thermolytic Reverse Electrodialysis for Low-Grade Waste Heat Recovery http://dx.doi.org/10.5772/intechopen.81006 185


#### Greek symbols

The model simulation showed an accurate estimation of the OCV within a wide range of flow rates and concentration ratios. The simulation results also fit well for power density with the experimental results relative to the various flow rates and concentration ratios. Especially, when the concentrated solution is equal to or exceeds 1 M, which is a preferable operating condition for high power generation. The difference between the simulation and experiment for the solution with lower concentration could be potentially attributed to the concentration of electrolytes, which affects the membrane resistance. The improvement in the membrane resistance model with the concentration variation is an interesting topic in order to obtain a better estimation.

We evaluated the net power density through the validated model including the pumping loss as a function of the flow rate, intermembrane distance, and concentration ratio. Consequently, the best performance for the working parameters was obtained. When we fixed the intermembrane distance at 0.1 mm and the flow rate was 3 mL/min, we obtained the highest net power density

The results of this study can help to improve our understanding of the RED system with ammonium bicarbonate. This study also provides a good reference for the RED system model-

The study was supported by a National Research Foundation of Korea (NRF) grant funded by

/s]

s]

of 0.84 W/m2 with the feed solution concentration ratio was 200 (2 M/0.01 M).

ing to get a higher energy density by using NH4HCO3 or other compounds.

the Korean government (MEST) (No. NRF-2014R1A2A2A01003618).

Acknowledgements

184 Organic Rankine Cycle Technology for Heat Recovery

Nomenclature

C solution concentration [M] D diffusion coefficient [m2

I electric current [A] J molar flux [mol/m2

L length [m] P power [W]

R resistance [Ω]

F Faraday constant [96485 C/mol]

Q volumetric flow rate [mL/min]

T ambient temperature [K]

Rg universal gas constant [8.314 J/mol�K]


#### Subscripts


#### Acronyms



## Author details

Deok Han Kim, Byung Ho Park, Kilsung Kwon, Longnan Li and Daejoong Kim\*

\*Address all correspondence to: daejoong@sogang.ac.kr

Department of Mechanical Engineering, Sogang University, Seoul, Republic of Korea

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## *Edited by Enhua Wang*

This book on organic Rankine cycle technology presents nine chapters on research activities covering the wide range of current issues on the organic Rankine cycle. The first section deals with working fluid selection and component design. The second section is related to dynamic modeling, starting from internal combustion engines to industrial power plants. The third section discusses industrial applications of waste heat recovery, including internal combustion engines, LNG, and waste water. A comprehensive analysis of the technology and application of organic Rankine cycle systems is beyond the aim of the book. However, the content of this volume can be useful for scientists and students to broaden their knowledge of technologies and applications of organic Rankine cycle systems.

Published in London, UK © 2018 IntechOpen © ba11istic / iStock

Organic Rankine Cycle Technology for Heat Recovery

Organic Rankine Cycle

Technology for Heat Recovery

*Edited by Enhua Wang*