Planning of Electric Vehicle Charging Stations With PV and Energy Storage Using a Fuzzy Inference System

Abstract

Electric vehicles (EVs) have emerged as a promising solution to reduce greenhouse gas emissions in urban areas. The construction of electric vehicle charging stations (EVCSs) is critical to the development of the EV industry. This paper proposes a novel integrated fuzzy inference system (FIS)-based planning framework for determining the optimal locations and capacities of EVCSs with PV systems and energy storage units. Several off-site factors that will affect the planning results of EVCSs are analyzed and incorporated into a multi-objective optimization problem, aiming at minimizing the cost of electricity (COE) and emission pollutants simultaneously. The proposed FIS-based planning approach introduces novel fuzzy criteria that account for the nonlinear and difficult-to-model joint effect of social and environmental factors. By incorporating these off-site factors, a more realistic framework for EVCS planning is presented. Numerical studies are conducted on a coupled 33-bus distribution system and 25-bus transportation system to illustrate the proposed planning method. According to the simulation results, by employing the proposed FIS-based planning framework, not only reduces the search space and simplifies the optimization problem, but the results obtained are more realistic according to practical system conditions.