Development of optimal integrated renewable energy model with battery storage for a remote Indian area

Over the past few years, renewable energy has come to be seen as a possible solution to the energy problems of people. The present work focuses on optimal sizing of an integrated renewable energy system (IRES) considering locally available different renewable energy sources namely micro hydro, solar, wind, biomass and biogas with battery system for electrification of a remote area in Karnataka state in India. Genetic algorithm (GA) has been used to minimize the total net present cost (TNPC) and cost of energy (COE) of the developed IRES model considering the three decision variables-total active sunshine area occupied by the SPV modules, total swept area required to install wind mills and state of charge (SOC) of battery system. Scenario based results of optimal sizes, TNPC and COE have been obtained based on suitable device types and time schedule of biomass generator. Based on optimization results, three IRE scenarios are proposed for the study area. Of the three, scenario-S1 for zone 2 and zone 3. While, scenario-S2 for zone 1 and zone 4 are found to be most feasible for the study area. Further, optimal time schedule, resource combination and device type for all zones have also been determined.