Enhanced Red Panda Optimization Algorithm for Smart Energy Management in Electric Vehicle Charging at Solar-Powered Charging Station

As electric vehicles (EVs) become more popular and widely available, they have the potential to significantly reduce direct greenhouse gas emissions. In recent years, EV charging and discharging management has emerged as a significant topic and a major research focus in power systems. This paper offers an optimal charge scheduling approach for EVs at solar-powered charging stations (CSs) that rely on solar power generation. The primary objective of the proposed algorithm is to schedule EV charging based on the availability of solar PV energy in order to reduce total charging costs. This paper uses an enhanced red panda optimization (ERPO) algorithm to effectively schedule charging and discharging in EV battery management, thereby improving the operation of solar-powered EV charging stations (EVCSs). The optimal operation is achieved by regulating the power flow among the PV system, energy storage unit, EVCS, and the grid. The proposed ERPO algorithm is highly efficient compared to other conventional algorithms. The results demonstrated that the proposed algorithm resulted in a reduction in operational costs, highlighting the model's effectiveness.