**2.6 Hybrid energy system (HES)**

It will be good to start with hybrid energy system (HES). Hybrid energy system is the engineering design of hybridizing power supply components or pairing them, for example, arranging diverse energy resources to work in parallel (equivalent) is very common in power. So, hybridizing is defined as forming crossbreed of pairs of agent for working together to achieve a purpose. Thus, hybridizing is to manually or automatically synchronize two or more electric power generator resources or components to supply electric power to the grid, therefore forming hybrid energy system. Hybrid energy system is an infrastructural design that integrates diverse or multiple energy converters to energy storage, energy conditioners, energy management system. By and large hybrid renewable energy system (HRES) is an extension of HES that uses mix diverse resources as hybrid or all hybrid renewable energy resources to supply the electric power system.

The concept of the hybrid RE power system is the perception to implement reliability portfolio to avert LPSP that will affect the quality of power supply resulting in dynamic change and transient. Hence, reliability is the dependability of systems or components to be able to function appropriately under stated conditions for a specified period without failure. Furthermore, reliability is said to be a probability of success, expressed as reliability (R) equal to "1" minus (Pf) probability of failure i.e., *R* = 1 − *Pf*. Hence, reliability relates to safety factors and cost factor caused by system downtime, cost of equipment repairs, spare parts, personnel, and cost of warranty claims. High reliability level will of course result from good engineering, reliability concept such as employing the concept of electric power system design optimization. Stochastic parameter dynamics in power supply do affect system reliability as failure is unabated, unless the concept of hybridization is embraced and integrated in the power supply structure as stated [13]. Redundancy is provision of more than one alternative resource power supply or system component to perform certain task (important), duplication of active or passive subsystem, and complete energy storage backup integration in case of failure according to Ashourian et al. [14].

On the other hand, reliability covers several unique modus operandi which provides high quality output, affording utmost availability through redundancy, and advanced problem-solving capabilities of hybrid RE power system as stated by Mat et al. [15]. Thus, HES assume several design types such as multiple fossil fuel energy sources, diesel generator-SPV renewable energy sources or other hybrid renewable energy resources mixture. And the hybrid system reliability can be improved through the integration and optimization of essential components such as energy resources, energy storage and energy management. Hybrid energy renewable systems are economical, less or no fossil fuel consumption for all RER, and have no or less greenhouse gas emission. Solar, hydro and other renewable energy sources are environmentally safe and have adequate power generation potentials. Therefore the integration of these sources with energy storage as hybrid system has economic returns as supported by Mat et al. [15].

### **2.7 Hybrid renewable energy power system (HREPS)**

Hybrid renewable energy power system (HREPS) is a cross breed or mixture of matching (parallel) power system infrastructure designed to offer power supply reliability. Hybrid renewable energy power system (HREPS) has enormous designs or models that consists of five common subunits, namely, (i) renewable energy resource (RER) or energy harvester, (ii) electrical system (energy conditioners), and (iii) energy storages system (ESS), however, (iv) a common Bus and (v) electronic logic controller (ECS) is included for system management. Hence, HREPS has several designs of hybridizing by optimal selection of appropriate components that consists of energy harvester, electrical energy conditioner, ESS, common bus and electronic logic controller, however, all hybrid design emphases on hybridizing RER than any of the five components. Thus, adapting redundancy norm on all subunits in order to avoid loss of power supply probability (LPSP) is necessary in order to realize optimal design. The nomenclature hybrid renewable energy power supply (HREPS) design requires the following project proposal subunits to be, the hybrid renewable energy resource (HRER)-hybrid energy storage system (HESS)-hybrid energy conditioner (HEC)-hybrid energy management (HEMS) of four modules hybridized subunits. Each of the subunit is expected to complement its pair to compromise optimal design to be modulated and simulated using simulation-based optimization in order to achieve power supply reliability devoid of loss of power supply probability (LPSP).

#### **2.8 Hybrid feasibility factors (optimization and levelized costs of electricity)**

Hybrid renewable energy power system (HREPS) optimization is hereby defined by Giraud et al. [16] as finding the utmost feasible performance or the most cost

**101**

*A Review of Hybrid Renewable Energy Systems Based on Wind and Solar Energy: Modeling…*

effective approach under given constraints by maximizing desired factors and minimizing undesired ones. In the case of this design performance was considered priority so, energy reliability is more pleasant than its scarcity (energy shortages). For illustration, gasoline generators were the only electricity source in the remote and rural areas else the community had to live with lanterns. Consequently, maximization of the means to obtain the highest result for electricity provision is better regardless of the cost. Therefore, an act, process or methodology of making a design to function effectively for specific purpose is termed system optimization as from [17]. Two factors are the probable yardstick in determining the hybrid potential of any given site constraints, namely, the optimization and levelized costs of electricity (LOCE).

Optimum or best methods to explore the hybrid renewable energy system for power supply reliability are enormous. The RE use has been historically, abundantly everywhere, omnipresent, free cost, and non-polluting characteristics leading to the increase of required storage capacity. A small hybrid system is understood to economical and may not meet the user load demand, whereas the large one can provide reasonable power, but it is expensive. Hence, optimal sizing of RE power system demand mathematical model of the system component characteristics using special techniques to extract maximum power from the models. Also, hybrid system has a complex control system due to the stochastic and multiple power harvesters, for example, the maximum power point (MPPT) technique employed in system SPV makes the system more complex [18]. This hybrid and MPPT approach is termed the optimization of the SPV stochastic power component to meet opera-

In addition, optimization of hybrid renewable energy power systems has two techniques, the optimum tools or component based on site available energy resources and the sizing of the components, and use the appropriate control strategy that will [19] automate operation of the integrated hybrid system. Optimum HREPS design, configuration can be conducted using several optimization algorithms such as numerical, probabilistic and heuristic methods under some conditions as reported by these authors [11]. Whereas, feasibility factor is an index called localized cost of energy (LCOE) used to find cost of the average price of electricity produced by the HRES over its life. These variables include initial investment, development, capital,

However, feasibility factors of using optimization are complex, nonlinear, and nonconvex because of the unique mixed constraints. Optimization approach are said to be fundamentally two, namely, the Simulation-based that is tedious, time consuming, prone to human errors and the metaheuristic method using multiple objectives involving cost, performance, supply-demand management, grid limitations, algorithms such as numerical, probabilistic and heuristic methodology as stressed by these authors [20, 10]. Optimization provides economic, efficient, and reliable power supply alternative energy without LPSP. Several of hybrid renewable energy power system optimization concepts were listed in **Table 1** in six groups. Their names are the graphical construction, probabilistic approach, deterministic approach, iterative approach, artificial intelligence, and software based (simulation-based) as stated by these authors [15]. However, a read-made HOMER software is a tool used to model hybrid configuration for optimization that emphasize on two factors, minimizing cost and maximizing performance constraints as

Next, search-based and Monte Carlo simulation (SMCS) is another optimization pattern use for HREPS and energy storage system (ESS) to check power supply

operation and maintenance, and fuel costs put together for costs analysis.

*DOI: http://dx.doi.org/10.5772/intechopen.85838*

**2.9 Optimization**

tional power supply demand.

asserted by Hong and Lian [6].

*A Review of Hybrid Renewable Energy Systems Based on Wind and Solar Energy: Modeling… DOI: http://dx.doi.org/10.5772/intechopen.85838*

effective approach under given constraints by maximizing desired factors and minimizing undesired ones. In the case of this design performance was considered priority so, energy reliability is more pleasant than its scarcity (energy shortages). For illustration, gasoline generators were the only electricity source in the remote and rural areas else the community had to live with lanterns. Consequently, maximization of the means to obtain the highest result for electricity provision is better regardless of the cost. Therefore, an act, process or methodology of making a design to function effectively for specific purpose is termed system optimization as from [17]. Two factors are the probable yardstick in determining the hybrid potential of any given site constraints, namely, the optimization and levelized costs of electricity (LOCE).

## **2.9 Optimization**

*Wind Solar Hybrid Renewable Energy System*

returns as supported by Mat et al. [15].

**2.7 Hybrid renewable energy power system (HREPS)**

or components to be able to function appropriately under stated conditions for a specified period without failure. Furthermore, reliability is said to be a probability of success, expressed as reliability (R) equal to "1" minus (Pf) probability of failure i.e., *R* = 1 − *Pf*. Hence, reliability relates to safety factors and cost factor caused by system downtime, cost of equipment repairs, spare parts, personnel, and cost of warranty claims. High reliability level will of course result from good engineering, reliability concept such as employing the concept of electric power system design optimization. Stochastic parameter dynamics in power supply do affect system reliability as failure is unabated, unless the concept of hybridization is embraced and integrated in the power supply structure as stated [13]. Redundancy is provision of more than one alternative resource power supply or system component to perform certain task (important), duplication of active or passive subsystem, and complete energy stor-

age backup integration in case of failure according to Ashourian et al. [14].

On the other hand, reliability covers several unique modus operandi which provides high quality output, affording utmost availability through redundancy, and advanced problem-solving capabilities of hybrid RE power system as stated by Mat et al. [15]. Thus, HES assume several design types such as multiple fossil fuel energy sources, diesel generator-SPV renewable energy sources or other hybrid renewable energy resources mixture. And the hybrid system reliability can be improved through the integration and optimization of essential components such as energy resources, energy storage and energy management. Hybrid energy renewable systems are economical, less or no fossil fuel consumption for all RER, and have no or less greenhouse gas emission. Solar, hydro and other renewable energy sources are environmentally safe and have adequate power generation potentials. Therefore the integration of these sources with energy storage as hybrid system has economic

Hybrid renewable energy power system (HREPS) is a cross breed or mixture of matching (parallel) power system infrastructure designed to offer power supply reliability. Hybrid renewable energy power system (HREPS) has enormous designs or models that consists of five common subunits, namely, (i) renewable energy resource (RER) or energy harvester, (ii) electrical system (energy conditioners), and (iii) energy storages system (ESS), however, (iv) a common Bus and (v) electronic logic controller (ECS) is included for system management. Hence, HREPS has several designs of hybridizing by optimal selection of appropriate components that consists of energy harvester, electrical energy conditioner, ESS, common bus and electronic logic controller, however, all hybrid design emphases on hybridizing RER than any of the five components. Thus, adapting redundancy norm on all subunits in order to avoid loss of power supply probability (LPSP) is necessary in order to realize optimal design. The nomenclature hybrid renewable energy power supply (HREPS) design requires the following project proposal subunits to be, the hybrid renewable energy resource (HRER)-hybrid energy storage system (HESS)-hybrid energy conditioner (HEC)-hybrid energy management (HEMS) of four modules hybridized subunits. Each of the subunit is expected to complement its pair to compromise optimal design to be modulated and simulated using simulation-based optimization in order to achieve power supply reliability devoid of loss of power supply probability (LPSP).

**2.8 Hybrid feasibility factors (optimization and levelized costs of electricity)**

by Giraud et al. [16] as finding the utmost feasible performance or the most cost

Hybrid renewable energy power system (HREPS) optimization is hereby defined

**100**

Optimum or best methods to explore the hybrid renewable energy system for power supply reliability are enormous. The RE use has been historically, abundantly everywhere, omnipresent, free cost, and non-polluting characteristics leading to the increase of required storage capacity. A small hybrid system is understood to economical and may not meet the user load demand, whereas the large one can provide reasonable power, but it is expensive. Hence, optimal sizing of RE power system demand mathematical model of the system component characteristics using special techniques to extract maximum power from the models. Also, hybrid system has a complex control system due to the stochastic and multiple power harvesters, for example, the maximum power point (MPPT) technique employed in system SPV makes the system more complex [18]. This hybrid and MPPT approach is termed the optimization of the SPV stochastic power component to meet operational power supply demand.

In addition, optimization of hybrid renewable energy power systems has two techniques, the optimum tools or component based on site available energy resources and the sizing of the components, and use the appropriate control strategy that will [19] automate operation of the integrated hybrid system. Optimum HREPS design, configuration can be conducted using several optimization algorithms such as numerical, probabilistic and heuristic methods under some conditions as reported by these authors [11]. Whereas, feasibility factor is an index called localized cost of energy (LCOE) used to find cost of the average price of electricity produced by the HRES over its life. These variables include initial investment, development, capital, operation and maintenance, and fuel costs put together for costs analysis.

However, feasibility factors of using optimization are complex, nonlinear, and nonconvex because of the unique mixed constraints. Optimization approach are said to be fundamentally two, namely, the Simulation-based that is tedious, time consuming, prone to human errors and the metaheuristic method using multiple objectives involving cost, performance, supply-demand management, grid limitations, algorithms such as numerical, probabilistic and heuristic methodology as stressed by these authors [20, 10]. Optimization provides economic, efficient, and reliable power supply alternative energy without LPSP. Several of hybrid renewable energy power system optimization concepts were listed in **Table 1** in six groups. Their names are the graphical construction, probabilistic approach, deterministic approach, iterative approach, artificial intelligence, and software based (simulation-based) as stated by these authors [15]. However, a read-made HOMER software is a tool used to model hybrid configuration for optimization that emphasize on two factors, minimizing cost and maximizing performance constraints as asserted by Hong and Lian [6].

Next, search-based and Monte Carlo simulation (SMCS) is another optimization pattern use for HREPS and energy storage system (ESS) to check power supply reliability. The SMCS allow chronological behavior and reliability of HREPS to be evaluated through of series of simulated experiments for high power loads reported by Ekren and Ekren [21].

Each of the optimization techniques is considered unique because it has design elements that are most appropriate for its application in order to get optimal results. Artificial intelligence optimization consists of five subcategories, generic algorithm, particle swarm, fuzzy logic, artificial neural network, and hybrid model by Arabali et al. [22].

Perturb and Observe method is a conventional maximum power point tracking (MPPT) approach used in the energy conditioner subunit. It is said to be a global maximum point (GMP) because the combination of Perturb and Observe quickly searches for first local maximum point (LMP) and the particle swarm optimization (PSO) search for the global maximum point. Experimental report shows this method to be good for hybrid power system because it can track GMP with faster convergence time and better dynamic response than using just PSO alone according to Hakimi and Moghaddas-Tafreshi [23]. Hence, optimization has several approaches, some of them are hereby listed in **Table 1**, according to techniques and RE system elements under study.

A hybrid renewable energy system optimization and components sizing has found to be economically and reliably better in meeting all load conditions with minimum investment and operation cost. This was a disclosure of many research using genetic algorithm, particle swarm optimization, simulated annealing, ant colony algorithm and artificial immune system algorithm results as reported by these authors [23]. **Figure 2** depicts a graphical representation of optimization showing that it possesses two edges, the energy production and the energy demand control, conversely, the objective function is optimal design reliability inclined toward its constraints. These constraints determine the energy inputs maximize performance and the other hands LOCE minimize costs by Boubekri [4].

Hybridizing diesel with renewable energy to demonstrate the potential of RE to replace diesel generator. HOMER software platform was used to study the load pattern and modeled for HOMER hybrid RE optimization. Hybrid solar-wind-DG


**103**

performance.

**Figure 2.**

*A Review of Hybrid Renewable Energy Systems Based on Wind and Solar Energy: Modeling…*

were simulated to get four different technology models. The results show PV/hydro/ DG has the highest optimization value in comparison to diesel generator only, [6]. Renewable energy (RE) and hybrid energy system (HES) are expanding and the current design method is a simulation based optimization and meta-heuristic optimization methods. HES are medium scale application in remote areas and stand-alone, but they are needed for large scale integration to grid. HES are nonlinear, non-convex and composed of mixed variables that cannot be solved using traditional optimization methods. In the alternative, two approaches are used for optional HES design. Simulation based optimization and mete-heuristics optimization methods are limited in view of time consuming, rework, and error proneness analyzed by Arabali et al. [22]. From the onset, design of the hybrid power generation system (HPGS) begins with feasibility studies, analyze the potential and effectiveness using computer simulation as observed by Soysal and Soysal [41].

A systematic optimization methodology is to derive formulae hybrid RE system (HRES) Optimization by integration of demand response, day-ahead and real-time weather forecasting, and uploading model using a receding horizon optimization strategy is another approach. Practically demonstrated to a single family residential house HRES by Nfah et al. [24]. The demand-response and weather forecast methods are used to optimize the HRES in order to have minimize costs and maximize

Furthermore, the state of the arts advanced generators; power electronic logic controller, grid requirements and control are optimized to improve wind power plant characteristics for efficient power delivery and integration according to Khan and Iqbal [25]. Consequently, the power electronic logic controllers, crossbreed SPV, hybrid ESS, and hybrid RER technology are therefore applicable to a solar

However, the approaches here consider optimization in terms of power supply reliability, but not only of the costs. Therefore, operating HREPS in the long run is economically preferable as costs are reduced no replacement reinvestment costs, fueling costs, maintenance costs, loss of power supply probability costs, and unquantifiable environmental degradation costs as economic parameters that indicate running diesel generator alone for power supply is bears exorbitant cost

Levelized energy cost (LEC) or (LCOE) is the unit-cost of electricity during the life period of power supply system in net present value (NPV) terms, often taken as alternative electricity average price to break even over generating system lifetime. However, LCOE is a general critical decision to proceed with a project development or not. There are two simulation models of the levelized cost of electricity (LCOE) available, namely, the EGC spread sheet and the system advisor model (SAM).

photovoltaic power system for improved power reliability.

variables than operating hybrid REPS energy system.

**2.10 Levelized cost of energy (LCOE)**

*DOI: http://dx.doi.org/10.5772/intechopen.85838*

*Hybrid optimization, control and RE power production diagram [4].*

#### **Table 1.**

*Possible optimization techniques.*

*A Review of Hybrid Renewable Energy Systems Based on Wind and Solar Energy: Modeling… DOI: http://dx.doi.org/10.5772/intechopen.85838*

#### **Figure 2.**

*Wind Solar Hybrid Renewable Energy System*

by Ekren and Ekren [21].

RE system elements under study.

et al. [22].

reliability. The SMCS allow chronological behavior and reliability of HREPS to be evaluated through of series of simulated experiments for high power loads reported

Each of the optimization techniques is considered unique because it has design elements that are most appropriate for its application in order to get optimal results. Artificial intelligence optimization consists of five subcategories, generic algorithm, particle swarm, fuzzy logic, artificial neural network, and hybrid model by Arabali

Perturb and Observe method is a conventional maximum power point tracking (MPPT) approach used in the energy conditioner subunit. It is said to be a global maximum point (GMP) because the combination of Perturb and Observe quickly searches for first local maximum point (LMP) and the particle swarm optimization (PSO) search for the global maximum point. Experimental report shows this method to be good for hybrid power system because it can track GMP with faster convergence time and better dynamic response than using just PSO alone according to Hakimi and Moghaddas-Tafreshi [23]. Hence, optimization has several approaches, some of them are hereby listed in **Table 1**, according to techniques and

A hybrid renewable energy system optimization and components sizing has found to be economically and reliably better in meeting all load conditions with minimum investment and operation cost. This was a disclosure of many research using genetic algorithm, particle swarm optimization, simulated annealing, ant colony algorithm and artificial immune system algorithm results as reported by these authors [23]. **Figure 2** depicts a graphical representation of optimization showing that it possesses two edges, the energy production and the energy demand control, conversely, the objective function is optimal design reliability inclined toward its constraints. These constraints determine the energy inputs maximize

Hybridizing diesel with renewable energy to demonstrate the potential of RE to replace diesel generator. HOMER software platform was used to study the load pattern and modeled for HOMER hybrid RE optimization. Hybrid solar-wind-DG

hybrid system

battery bank

system

Hybrid-solar-wind

Hybrid solar-wind system with battery Based on statistical data collection

Use an equation for determining specific values with constant

Based on LPSP to find possible combination of solar-wind

Based on evolution technique

information is supplied. The software takes care of other things

approach

parameters

combination

All of the above Input file with all necessary

performance and the other hands LOCE minimize costs by Boubekri [4].

**S/N Optimization technique Elements Remarks**

2 Probabilistic approach Performance of

4 Iterative approach: hill climbing,

multiple objective

hybrid model

*Possible optimization techniques.*

6 Software based: homer, and

5 Artificial intelligence: generic

dynamic programming, linear, and

algorithm, particle swarm, fuzzy logic, artificial neural network, and

developed GUI application software

3 Deterministic approach Stand-alone PV with

1 Graphical construction Battery and PV array Use two parameters

**102**

**Table 1.**

*Hybrid optimization, control and RE power production diagram [4].*

were simulated to get four different technology models. The results show PV/hydro/ DG has the highest optimization value in comparison to diesel generator only, [6].

Renewable energy (RE) and hybrid energy system (HES) are expanding and the current design method is a simulation based optimization and meta-heuristic optimization methods. HES are medium scale application in remote areas and stand-alone, but they are needed for large scale integration to grid. HES are nonlinear, non-convex and composed of mixed variables that cannot be solved using traditional optimization methods. In the alternative, two approaches are used for optional HES design. Simulation based optimization and mete-heuristics optimization methods are limited in view of time consuming, rework, and error proneness analyzed by Arabali et al. [22]. From the onset, design of the hybrid power generation system (HPGS) begins with feasibility studies, analyze the potential and effectiveness using computer simulation as observed by Soysal and Soysal [41].

A systematic optimization methodology is to derive formulae hybrid RE system (HRES) Optimization by integration of demand response, day-ahead and real-time weather forecasting, and uploading model using a receding horizon optimization strategy is another approach. Practically demonstrated to a single family residential house HRES by Nfah et al. [24]. The demand-response and weather forecast methods are used to optimize the HRES in order to have minimize costs and maximize performance.

Furthermore, the state of the arts advanced generators; power electronic logic controller, grid requirements and control are optimized to improve wind power plant characteristics for efficient power delivery and integration according to Khan and Iqbal [25]. Consequently, the power electronic logic controllers, crossbreed SPV, hybrid ESS, and hybrid RER technology are therefore applicable to a solar photovoltaic power system for improved power reliability.

However, the approaches here consider optimization in terms of power supply reliability, but not only of the costs. Therefore, operating HREPS in the long run is economically preferable as costs are reduced no replacement reinvestment costs, fueling costs, maintenance costs, loss of power supply probability costs, and unquantifiable environmental degradation costs as economic parameters that indicate running diesel generator alone for power supply is bears exorbitant cost variables than operating hybrid REPS energy system.

#### **2.10 Levelized cost of energy (LCOE)**

Levelized energy cost (LEC) or (LCOE) is the unit-cost of electricity during the life period of power supply system in net present value (NPV) terms, often taken as alternative electricity average price to break even over generating system lifetime. However, LCOE is a general critical decision to proceed with a project development or not. There are two simulation models of the levelized cost of electricity (LCOE) available, namely, the EGC spread sheet and the system advisor model (SAM).

LCOE is mathematically expressed as the life-cycle cost divided by lifetime energy produced interpreted as to break even. The renewable energy systems have higher initial capital costs outlay (ICC), it however amortizes in the long run with free natural fuel, less operation/maintenance costs and environmental friendliness free of GHG impact plus poisonous gases according to Refs. [25, 27]. Finally, localized cost of energy (LCOE) is an index use to cost average price of electricity produced by the HRES over its life initial investment, development, capital, operation and maintenance, and fuel costs as variables.

Hence, effective ways to cut energy cost are:


Cut in operation costs includes fossil fuel, and then increase the price and global greenhouse gas emission concern has motivated hybrid renewable energy system standalone applications. Modeling, simulation and multi objective optimization decision tools supporting the leveraged cost of electricity (LCOE), life cycle cost (LCC), greenhouse gas (GHG) emission objective functions use to evaluate power supply reliability, optimization and market price sensitivity. However, it is difficult to justify LCOE and LCC of standalone RE components in rural electrification projects. Conversely, LEC, LCC and GHG fronts are simplified by pairing LCC-LEC and LEC-GHG for decision making according to Khan and Iqbal [25]. HOMER simulation reported that the LCOE of energy of optimized hybrid PV-Wind-diesel-battery is lower than hybrid energy system without renewable energy mix. Consequently, it was concluded that diesel generator supply alone is not feasible as fossil fuel price increases rapidly as reported by Ekren and Ekren [21].

Solar, wind and other renewable integration with energy storage as hybrid system has economic returns of LCOE of providing adequate power, environmental friendliness and reliability for all load conditions as supported by Nema et al. [26] Alternatively, three analyses model were put to test costs-benefits of solar PV, thus, short-run, medium-run and the long-run analyses. The short-run considers costseffectiveness on incremental increases, the medium-run focus on non-incremental change implications in solar capacity, whereas, the long-run dwell on carbon targets of the twenty-first century. Hence, economics depends on grid integration costs, low-carbon technologies and technological advances potential [27].

The common cost-effective criteria in photovoltaic phenomena rely on policy jurisdiction, frame work such as incentives like fit-in-tariff (FIT), tax credits, carbon reduction certificates variables motivates investors. Economically, return on investment (ROI) is always a prominent business yard stick and motivator for an investor. Conversely, feasibility study on solar PV indicated that it has long term high yield rate of return (ROR), see **Table 2** give details as reported [28].

#### **2.11 Hybrid renewable energy power system (HREPS) bus**

Electricity bus is a good conductor in made into a bus-bar for transporting energy from power generator/converter to the grid. Hybrid renewable energy power system (HRES) has two levels of voltage bus the DC and AC produced by the mixture and crossbreed of energy resources.

**105**

**Figure 4.**

*A Review of Hybrid Renewable Energy Systems Based on Wind and Solar Energy: Modeling…*

1 Thin film 0.75–3.5 10.5–50 Environmentally

I High concentration 0.7–2.0 Lower than above rate Environmentally

III Dye-sensitized – – Rate research is ongoing

**Emission rate (gCO2-eq/KWh)** **Remarks**

friendly and suitable

friendly and suitable

**range (years)**

2 Mono-silicon 1.7–2.7 29–45 Ditto

II Hetero-junction Ditto Higher than above rate Ditto

*Feasibility on PV types with payback period and environmental impacts.*

*Series hybrid RE power system with single AC bus for all AC load [15].*

The two levels AC and DC bus by extension are fundamentally two configurations, namely, the series and the parallel bus arrangements as shown in **Figure 3** for the series connection, **Figure 4** and **Figure 5** for parallel bus as reported by Zhou

*Parallel (hybrid) RE power system with both AC and DC bus plus AC and DC loads [15].*

*DOI: http://dx.doi.org/10.5772/intechopen.85838*

3 Advanced PV system technologies

**Table 2.**

**Figure 3.**

**S/No PV type Payback period** 

*A Review of Hybrid Renewable Energy Systems Based on Wind and Solar Energy: Modeling… DOI: http://dx.doi.org/10.5772/intechopen.85838*


#### **Table 2.**

*Wind Solar Hybrid Renewable Energy System*

maintenance, and fuel costs as variables.

Hence, effective ways to cut energy cost are:

increases rapidly as reported by Ekren and Ekren [21].

LCOE is mathematically expressed as the life-cycle cost divided by lifetime energy produced interpreted as to break even. The renewable energy systems have higher initial capital costs outlay (ICC), it however amortizes in the long run with free natural fuel, less operation/maintenance costs and environmental friendliness free of GHG impact plus poisonous gases according to Refs. [25, 27]. Finally, localized cost of energy (LCOE) is an index use to cost average price of electricity produced by the HRES over its life initial investment, development, capital, operation and

a.Cut down on development cost, capital cost, operation and maintenance cost

model of wind generator life was improved to last between 20 and 25 years in Denmark, so this applies to other RE infrastructure as observed these authors [19]. However, informed decisions demand trade off in projects selection

Cut in operation costs includes fossil fuel, and then increase the price and global greenhouse gas emission concern has motivated hybrid renewable energy system standalone applications. Modeling, simulation and multi objective optimization decision tools supporting the leveraged cost of electricity (LCOE), life cycle cost (LCC), greenhouse gas (GHG) emission objective functions use to evaluate power supply reliability, optimization and market price sensitivity. However, it is difficult to justify LCOE and LCC of standalone RE components in rural electrification projects. Conversely, LEC, LCC and GHG fronts are simplified by pairing LCC-LEC and LEC-GHG for decision making according to Khan and Iqbal [25]. HOMER simulation reported that the LCOE of energy of optimized hybrid PV-Wind-diesel-battery is lower than hybrid energy system without renewable energy mix. Consequently, it was concluded that diesel generator supply alone is not feasible as fossil fuel price

Solar, wind and other renewable integration with energy storage as hybrid system has economic returns of LCOE of providing adequate power, environmental friendliness and reliability for all load conditions as supported by Nema et al. [26] Alternatively, three analyses model were put to test costs-benefits of solar PV, thus, short-run, medium-run and the long-run analyses. The short-run considers costseffectiveness on incremental increases, the medium-run focus on non-incremental change implications in solar capacity, whereas, the long-run dwell on carbon targets of the twenty-first century. Hence, economics depends on grid integration costs,

The common cost-effective criteria in photovoltaic phenomena rely on policy jurisdiction, frame work such as incentives like fit-in-tariff (FIT), tax credits, carbon reduction certificates variables motivates investors. Economically, return on investment (ROI) is always a prominent business yard stick and motivator for an investor. Conversely, feasibility study on solar PV indicated that it has long term

low-carbon technologies and technological advances potential [27].

high yield rate of return (ROR), see **Table 2** give details as reported [28].

Electricity bus is a good conductor in made into a bus-bar for transporting energy from power generator/converter to the grid. Hybrid renewable energy power system (HRES) has two levels of voltage bus the DC and AC produced by the

**2.11 Hybrid renewable energy power system (HREPS) bus**

mixture and crossbreed of energy resources.

b.Energy production or increase life span of generation infrastructure. A

using pressing priority or objective functions to maximize.

**104**

*Feasibility on PV types with payback period and environmental impacts.*

**Figure 3.**

*Series hybrid RE power system with single AC bus for all AC load [15].*

#### **Figure 4.**

*Parallel (hybrid) RE power system with both AC and DC bus plus AC and DC loads [15].*

The two levels AC and DC bus by extension are fundamentally two configurations, namely, the series and the parallel bus arrangements as shown in **Figure 3** for the series connection, **Figure 4** and **Figure 5** for parallel bus as reported by Zhou

#### **Figure 5.**

*Parallel hybrid RE system with both AC and DC bus for only all AC loads [15].*

**Figure 6.** *Hybrid RE three phase output voltage waveforms [30].*

and Sun [29]. These authors have illustrated the ideology of hybrid methodology can be synchronized to serve the electric load better, meaning mixing energy to improve the power of equivalent RE converter infrastructure to have reliability in power supply delivery.

The **Figures 3**–**5** are in one line/block schematic representing three phase system for hybrid RE resources to produce output voltage waveform shown in **Figure 6**. However, hybrid RE can be also be designed to supply single phase system for smaller single phase load demand and its output voltage wave is single implied.

### **2.12 Renewable energy resources (RER) optimal sizing**

Hybridizing is a common strategy for improving the sizing of renewable resource (RER) energy resources; it is also known as crossbreeding in the SPV. The optimum scale of renewable energy resource to harvest energy reliably depends on the optimal design of conversion model. Energy converters are RER and come with assorted characteristics, sizes, and brands guide in the design and the implementation of projects. The RER characteristics of solar photovoltaic and micro hydro are the main

**107**

**Figure 7.**

*Schematic diagram of a grid PV-Wind system.*

*A Review of Hybrid Renewable Energy Systems Based on Wind and Solar Energy: Modeling…*

focal area to be considered for discussion and analysis in this study. Henceforward, RER as the name implies, are replenish able resource that naturally are regenerated in accordance with the climatic condition and topography of the locality of solar, hydro, and so on as established by Mohammadi et al. [12]. The common among the renewable energy resources are solar and hydro considering their technical and economic benefits as considered by Daut et al. [13]. Solar photovoltaic and micro hydro resources have several statistical variations in nature and are therefore are dependent

From the deep literature survey conducted, a lot of studies are being done with divergent ideas and necessities on the possibility of integrating wind and PV system. The studies can be classified into, modeling, design, optimization, control and techno-economic strategies. On the other hand, some researchers proposed a stand-alone hybrid system, while others applied wind and PV system in grid con-

A lot of modeling and design of the PV and Wind have been developed using different approaches. The design can be categorized into two, it can be a grid or stand-alone. A grid PV-Wind system proposed by Harini et al. [31] used Wind generator, wind side converter, DC-DC converter, and grid interface inverter. The MPPT is used to optimize the DC voltage coming from the solar panels. The design was implemented in Matlab environment using Simulink. The schematic diagram of

PV-Wind hybrid system was used to generate electricity in Iraq; the planned system was simulated using MATLAB solver, where the input variables for the solver were the meteorological data for the selected areas and the sizes of PV and wind turbines. Outcomes revealed that it is achievable in Iraq to implement the solar and wind energy to come up with enough power for some communities in the desert or rural area. Additionally, it is feasible to use such a system as a black start source of power in the course of total shutdown time. Final results also showed that the desired place for this system is in Basrah for both solar and wind energy [32]. A Wind-PV-diesel hybrid power system is developed using HOMER software for a small town in Saudi Arabia which happens to be at the moment powered by a diesel power plant comprising of eight diesel generating sets of 1120 kW each, The

*DOI: http://dx.doi.org/10.5772/intechopen.85838*

on the peculiarity of specific geographical location's weather.

**3. Wind energy and photovoltaic systems**

**3.1 Modeling and design of PV-Wind system**

the overall system is shown in **Figure 7**.

nected mode.

*A Review of Hybrid Renewable Energy Systems Based on Wind and Solar Energy: Modeling… DOI: http://dx.doi.org/10.5772/intechopen.85838*

focal area to be considered for discussion and analysis in this study. Henceforward, RER as the name implies, are replenish able resource that naturally are regenerated in accordance with the climatic condition and topography of the locality of solar, hydro, and so on as established by Mohammadi et al. [12]. The common among the renewable energy resources are solar and hydro considering their technical and economic benefits as considered by Daut et al. [13]. Solar photovoltaic and micro hydro resources have several statistical variations in nature and are therefore are dependent on the peculiarity of specific geographical location's weather.
