Coordinated optimization of electric vehicle charging infrastructure and reactive power compensation in active distribution networks with V2G services

Abstract

This work presents an innovative strategy to augment the efficiency and profitability of electrical distribution networks (DNs) in the context of increasing plug-in electric vehicle (PEV) acceptance. The method focuses on the optimal assignment of PEV charging stations and capacitor units within DNs, specifically considering Vehicle-to-Grid (V2G) functionality, with the aim of reducing energy losses, lowering system outage costs, and improving network reliability. The proposed approach employs a hybrid technique, namely the Hybrid Grey Wolf Cuckoo Search Algorithm (HGWOCSA), which leverages the best features of Grey Wolf Optimization (GWO) and the Cuckoo Search Algorithm (CSA) to solve the optimization problem. This technique helps maintain a balance between incurred expenses and overall system efficiency. The HGWOCSA outperforms both GWO and CSA in optimally locating PEV charging stations and capacitors within a DN. The main goal is to optimize network performance by lowering power losses, stabilizing voltage profiles, and supporting bidirectional energy flow through the integration of V2G functionality. The proposed strategy is validated on the IEEE 33-bus system, and the achieved outcomes showed a substantial decrease in energy losses along with improved voltage stability. The proposed approach reduced energy loss costs by 51.62% and achieved an annual profit of $54,983.01 for the studied system. The optimal configuration of three PEV charging stations and three capacitors reduced active and reactive power losses from 202.67 kW to 98.06 kW and from 135.14 kVAr to 66.57 kVAr, respectively, while V2G integration improved the weakest bus voltage from 0.913 p.u. to 0.9625 p.u. at 30% penetration. Moreover, it demonstrated strong compatibility with the effective integration of PEV charging stations and reactive power compensation. Therefore, the findings suggest that the proposed approach is highly suitable for policymakers aiming to improve both the economic performance and reliability of electrical distribution networks.