Hybrid CHGSO Approach-Based EV Energy Regulation by Considering Incentive-Based Prosumer and Uncertainty

Abstract

This paper proposes the hybrid approach for increasing the profit of prosumers and reducing the energy cost of the residents. The hybrid method is the combination of chaotic maps and the Henry gas solubility optimization algorithm (HGSO), hence it is called chaotic Henry gas solubility optimization (CHGSO). The proposed approach is the community-based microgrid that incorporates energy storage systems (ESS), electric vehicles (EVs) and photovoltaics (PV). Both ESS and EV are conserved as alternative sources of energy. The stored EV energy is used as a power source for homes and the grid by utilizing the Grid-to-Vehicle (G2V) and Vehicle-to-Grid (V2G) modes. The power flow of EV/ESS is controlled depending on the rate of charging and discharging. Here, the battery degradation cost is considered. The proposed approach solves the optimization problems, like battery degradation of EV/ESS, regulation of charge/discharge and provides optimal economic benefits. The proposed approach increases the prosumer profit through encouraging EV energy transactions through incentive-based pricing. Finally, the CHGSO method is performed in MATLAB and is compared with existing methods. From the simulation analysis, it can be concluded that the cost of CHGSO method is less and the prosumer participation has increased.