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Energy required by remote village areas can be met quite reliably by hybrid energy technologies. The project under consideration is for electrifying a group of three villages in Kollegal block of Chamarajanagar district, Karnataka State in India using an off-grid hybrid renewable energy system. The process of optimizing such hybrid energy system control, sizing and choice of components is to provide it with a cost effective power solution for the society. The main objective of this paper is to reduce the Total System Net Preset Cost (TNPC), Cost of Energy (COE), unmet load, CO2 emissions using Genetic Algorithm (GA) and HOMER Pro Software. The results of the two methods are compared with four combinations of hybrid renewable energy systems (HRES). A sensitivity analysis is also performed on the best possible solution to the study for changes in annual wind speed and biomass fuel prices. Finally, a comparative analysis is performed between the GA and HOMER. Compared to HOMER, GA based HRES of combination-1 (biogas+biomass+solar+ wind+ fuel cell with battery) is found to be the optimal solution supplying energy with 0% unmet load at the least cost of energy, which is at 0. 163 per KWH. Thus PV saturation in GA is more cost effective than the HOMER.
Vendoti et al. (Sat,) studied this question.
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