Hybrid Optimization for Economic Deployment of ESS in PV-Integrated EV Charging Stations

Electric vehicle (EV) charging stations will play an important role in the smart city. Uncoordinated and statistical EV charging loads would further stress the distribution system. Photovoltaic (PV) systems, which can reduce this stress, also show variation due to weather conditions. In this paper, a hybrid optimization algorithm for energy storage management is proposed, which shifts its mode of operation between the deterministic and rule-based approaches depending on the electricity price band allocation. The cost degradation model of the energy storage system (ESS) along with the levelized cost of PV power is used in the case of EV charging stations. The algorithm comprises of three parts: categorization of real-time electricity price in different price bands, real-time calculation of PV power from solar irradiation data, and optimization for minimizing the operating cost of EV charging station integrated with PV and ESS. An extensive simulation study is carried out with an uncoordinated and statistical EV charging model in the context of Singapore to check effectiveness of this algorithm. Furthermore, detailed analysis of subsidy and incentive to be given by the government agencies for higher penetration of renewable energy is also presented. This work would aid in planning of adoption of PV-integrated EV charging stations, which would expectedly replace traditional gas stations in future.