An improved arithmetic method for determining the optimum placement and size of EV charging stations

Abstract

The increasing number of electric vehicles (EVs) will result in a rise in electric vehicle charging stations (EVCSs), which will have a significant effect on the electrical grid. One major issue is deciding where to place EVCSs in the power grid in the most optimal way. The distribution network is greatly impacted by inadequate EVCS prediction, which results in issues with frequency and voltage stability. This paper suggests an optimization method called Binary Random Dynamic Arithmetic Optimization Algorithm (BRDAOA) that is applied on an IEEE 33 bus network to determine the best position for EVCSs as efficiently as possible, and the Loss Sensitivity Factor (LSF) was used in the analysis. Considering the system voltage, the load (actual power), and the system losses, LSF was calculated for a variety of buses. The efficacy of the suggested method is demonstrated by a final comparison of its findings with those of the Arithmetic Optimization Algorithm (AOA) and two additional metaheuristic algorithms. In addition to reducing line losses by 2% compared to the AOA method and 4% compared to the other two metaheuristic optimization methods, the suggested optimization approach known as BRDAOA requires less computing time than the other three methods. Finally, a reliability test was conducted to determine the best location for EVCS in the IEEE 33 BUS system.