Optimization of an off-grid integrated hybrid renewable energy system with different battery technologies for rural electrification in India

A large population of India is living in villages, some of them are living in remote areas isolated from the grid. It is not feasible or economical to extend the grid connection to provide electricity for those villages, but an autonomous integrated hybrid renewable energy system can be a viable option. This study focused on emerging a grid-independent integrated hybrid renewable energy system (IHRES) to provide electricity and freshwater availability for a cluster of un-electrified villages located at Odisha state in India. In order to provide a continuous power supply, the study focused on three different types of battery technologies, such as Lead-Acid (LA), Lithium-Ion (Li-Ion) and Nickel-Iron (Ni-Fe). To obtain an optimal IHRES configuration, twelve different IHRES configurations are modelled using nine metaheuristic algorithms in the MATLAB (c) environment. From the results, it is found that the Ni-Fe battery-based IHRES results in a minimum Annual Levelized Cost (ALC) as $66,650 and Levelized Cost of Energy (LCOE) as 0.21779 $/kWh when compared to other battery-based IHRESs. The proposed Salp Swarm Algorithm (SSA) has proven its robustness and convergence efficiency by providing the optimal ALC and LCOEs with fast convergence to the global best optimal solutions. Further, the proposed system has been examined at a different maximum allowable loss of power supply probability (LPSP*) values. Finally, the sensitivity analysis has been conducted with the variable input parameters, such as interest rate, biomass collection rate and cost of biomass. It is found that the variation in interest rate affects the system performance significantly.