Optimal sizing of off grid hybrid system for DC microgrid incorporating utilisation of V2G storage

Abstract In this paper, the optimal sizing of a stand-alone hybrid system including solar, biogas, biomass, and battery integrated with Electric Vehicle (EV) has been carried out for a rural region located in Haryana, India. The objective is to minimize the overall cost of the system and loss of power supply probability for the hybrid system utilizing EV battery storage. For the same, different case studies has been carried out by utilizing the computational intelligence based optimization technique, a multi-objective genetic algorithm (MOGA). In Configuration I, the sizing of the off-grid hybrid system consisting of solar, biogas, biomass, and battery systems has been optimally worked out. To minimize the large battery storage systems, electric vehicle-connected off-grid systems has been considered under Configuration II and the optimal sizing of resources has been determined. A comparative analysis has been carried out across the two configurations for sizing the hybrid practical system. Results indicate that the EV-integrated system reduces the required battery capacity of the off grid hybrid system. Hence, reducing the total system cost by 19.29% and cost of energy by 19.67% compared to Configuration I. Furthermore, the performance of the MOGA-based optimization is compared with the Grey Wolf Optimization (GWO) technique. The analysis reveals that MOGA delivers superior outcomes. This research provides valuable insights for the design and implementation of sustainable off-grid energy systems integrated with EVs.