**3.5 Fuel consumption and emissions**

The *Calculate Other Parameters* block calculates parameters like the total kWhrs/gallon supplied by the generator, the fuel consumed in lbs, the fuel consumed in gallons, the total cost of fuel in USD, the amount of CO2 emissions, the amount of particulate matter (PM10) emissions, and the amount of NOx emissions. For example, the kWhrs/gallon supplied by the generator and the total cost of fuel in USD are calculated as

$$\text{kWhrs/gallon} = \frac{\text{kWhr\_{Gen}}}{\text{F}\_{\text{C}}} \tag{10}$$

and

$$\text{Total cost (USD)} = \text{F}\_{\text{C}}\text{\*cost/gallon} \,\text{.}\tag{11}$$

Energy-Efficient Standalone Fossil-Fuel Based

Fig. 7. Flow chart for model algorithm.

Hybrid Power Systems Employing Renewable Energy Sources 131

where kWhrGen is the total kWhr supplied by the diesel generator and FC is the total fuel consumed in gallons. The quantity cost/gallon is the cost of fuel (USD) per gallon and varies for different locations.

The total CO2 emissions were estimated based on the equation for the combustion of diesel fuel. For example, one empirical formula for light diesel CnH1.8n is given in (Cengel & Boles, 2002). For this empirical formula, with 0 % excess air the combustion reaction is given as

$$\begin{aligned} \text{C}\_{\text{n}}\text{H}\_{1.8\text{n}} + \text{(1.45\text{n})(O}\_{2} + \text{3.76N}\_{2}) &= \\ n\text{CO}\_{2} + 0.9n\text{H}\_{2}\text{O} + \text{(1.45N}\_{2}) &\text{(3.76N}\_{2}\text{)} \text{ }' \end{aligned} \tag{12}$$

where n is the number of atoms. For any n, the mass in kg (lb) of CO2 per unit mass in kg (lb) of fuel = 44/(12 + 1.8) = 3.19. For example, to get the emissions per unit electrical energy output, the above is combined with an engine efficiency of 3.17 kWh/liter (12 kWhr/gallon) and a fuel density of 0.804 kg/liter (6.7 lb/gallon). Doing this results in specific CO2 emissions of 3.1\*(0.804/3.17) = 0.786 kg (1.73 lb) of CO2 per kWh of electricity which agrees closely with 0.794 kg/kWh (1.75 lb/kWh) obtained from the DEG manufacturer.

The annual CO2 amount was calculated from the lb CO2/kWh and the annual kWh produced and is given as follows:

$$\text{Total pollutant in kg (lb)} = \frac{\text{pollutant}}{\text{kWh}} \text{\*kWh}\_{\text{Gen}} \tag{13}$$

where kWhGen is the total kWh supplied by the diesel generator during the simulation period. The corresponding values for PM10 and NOx emissions can be obtained from the manufacturer using relations similar to (13).

#### **3.6 Overall model operation and algorithm flow**

Fig. 7 shows the algorithm flow chart for the PV-wind-diesel-battery hybrid power system. In the PV-wind-diesel-battery system, the PV array and the WTGs have the highest priority to supply the load. If the load is not met by the PV array and WTGs, the battery bank is used to supply the required load, and if the battery bank is less than 20% charged, the controller sends a signal to the diesel generator to turn "on" and the diesel generator is then used to supply the desired load and charge the batteries at the same time. On the other hand if there is excess power available from the PV array and WTGs, the excess power is sent to a resistive/dump load which can be used for space heating purposes. It should be noted that there is a high demand for heating load during the long winter months in remote communities of Alaska.

Various output parameters from the model include: the second law efficiency of the WTGs (%), the power supplied by the WTGs (kW), the power supplied by the PV array (kW), total fuel consumed in liters (gallons), total fuel cost (USD), total CO2 emitted (metric tons), total NOx emitted in kg (pounds), and total PM10 emitted in kg (pounds). These output parameters are used to calculate the life cycle cost (LCC) and net present value (NPV), the cost of electricity (COE), the payback period for the PV array and the WTGs, and the avoided cost of pollutants.

where kWhrGen is the total kWhr supplied by the diesel generator and FC is the total fuel consumed in gallons. The quantity cost/gallon is the cost of fuel (USD) per gallon and varies

The total CO2 emissions were estimated based on the equation for the combustion of diesel fuel. For example, one empirical formula for light diesel CnH1.8n is given in (Cengel & Boles, 2002). For this empirical formula, with 0 % excess air the combustion reaction is given as

where n is the number of atoms. For any n, the mass in kg (lb) of CO2 per unit mass in kg (lb) of fuel = 44/(12 + 1.8) = 3.19. For example, to get the emissions per unit electrical energy output, the above is combined with an engine efficiency of 3.17 kWh/liter (12 kWhr/gallon) and a fuel density of 0.804 kg/liter (6.7 lb/gallon). Doing this results in specific CO2 emissions of 3.1\*(0.804/3.17) = 0.786 kg (1.73 lb) of CO2 per kWh of electricity which agrees

The annual CO2 amount was calculated from the lb CO2/kWh and the annual kWh

where kWhGen is the total kWh supplied by the diesel generator during the simulation period. The corresponding values for PM10 and NOx emissions can be obtained from the

Fig. 7 shows the algorithm flow chart for the PV-wind-diesel-battery hybrid power system. In the PV-wind-diesel-battery system, the PV array and the WTGs have the highest priority to supply the load. If the load is not met by the PV array and WTGs, the battery bank is used to supply the required load, and if the battery bank is less than 20% charged, the controller sends a signal to the diesel generator to turn "on" and the diesel generator is then used to supply the desired load and charge the batteries at the same time. On the other hand if there is excess power available from the PV array and WTGs, the excess power is sent to a resistive/dump load which can be used for space heating purposes. It should be noted that there is a high demand for heating load during the long winter months in remote

Various output parameters from the model include: the second law efficiency of the WTGs (%), the power supplied by the WTGs (kW), the power supplied by the PV array (kW), total fuel consumed in liters (gallons), total fuel cost (USD), total CO2 emitted (metric tons), total NOx emitted in kg (pounds), and total PM10 emitted in kg (pounds). These output parameters are used to calculate the life cycle cost (LCC) and net present value (NPV), the cost of electricity (COE), the payback period for the PV array and the WTGs, and the

2 2 22

, (12)

Gen

pollutant Total pollutant in kg (lb) \*kWh kWh , (13)

*n*CO 0.9nH O (1.45N )(3.76N )

n 1.8n 2 2

closely with 0.794 kg/kWh (1.75 lb/kWh) obtained from the DEG manufacturer.

C H (1.45n)(O 3.76N )

for different locations.

produced and is given as follows:

communities of Alaska.

avoided cost of pollutants.

manufacturer using relations similar to (13).

**3.6 Overall model operation and algorithm flow** 

Fig. 7. Flow chart for model algorithm.

Energy-Efficient Standalone Fossil-Fuel Based

Fig. 10. Annual solar flux for Kongiganak Village, Alaska.

diesel-battery system, and (iv) PV-wind-diesel-battery system.

2. Fuel cost of 0.80 USD/liter (3.00 USD/gallon). 3. Life cycle period for PV and WTG (n) = 20 years. 4. Life cycle period for diesel-battery system = 5 years.

The following assumptions were used for the Kongiganak Village simulations:

**4.2 Simulation cases and results** 

1. Interest rate *i* = 7%.

years.

Solar Radiation Resource, 2007).

Hybrid Power Systems Employing Renewable Energy Sources 133

of the system is about 150 kW, the minimum load is about 45 kW and the average load is about 95 kW. From Fig. 9 it can be observed that the annual average wind speed is about 7 m/s (15.66 miles/hr). From Fig. 01 it can be observed that the village has low solar flux during winter months and high solar flux during summer months. The clearness index data for the solar insolation profile is obtained using the solar maps developed by NREL (NREL

Simulations were performed for the standalone hybrid power system using the annual load profile for four systems: (i) diesel-battery system, (ii) PV-diesel-battery system, (iii) wind-

5. Life cycle period for diesel-battery system when operating with PV and WTG = 5.5

Table 2 shows the installation costs (USD) for different components for the hybrid electric power system. The post simulation results obtained from the HARPSim model were compared with those obtained from the HOMER software. Table 3 shows the comparison of results from the HARPSim model with HOMER for the hybrid electric power system. It can be observed from the table that the wind-diesel-battery system is the most cost effective system with the lowest NPV, COE, and payback period. This is because of the high energy
