A Hybrid Approach for Economic Integration of Electric Vehicle Charging Stations and Shunt Capacitors for Performance Enhancement in Radial Distribution System

Abstract

The increasing adoption of electric vehicles (EVs) is expected to significantly transform the transportation sector due to their environmental benefits and reduced carbon emissions. However, the rapid growth in EV charging demand introduces several challenges in Radial distribution Systems (RDS), including increased power losses, voltage instability, and imbalance between generation and consumption. This study addresses these challenges by optimizing the integration of EV charging stations (EVCSs) and shunt capacitors (SCs) within the RDS. The objective is to maximize Net Present Value (NPV) by simultaneously reducing power losses, improving voltage profiles, and reducing Expected Interruption Cost (EIC), while incorporating compensation coefficients for reliability assessment. To achieve this, a Hybrid Gray Wolf–Cuckoo Optimization (HGCO) algorithm is proposed, combining the exploitation capability of Gray Wolf Optimization (GWO) with the exploration strength of the Cuckoo Search (CU) algorithm. The proposed method is validated on IEEE 33‐bus and 118‐bus systems. Simulation results demonstrate a reduction in active power loss (APL) of 34.45% and 31.08% for the respective systems. Annual energy loss cost savings are 35 268 and 209 153.10 $/year, while EIC is reduced by 14 029.80 and 48 699.30 $/year. The proposed approach also achieves a net annual profit of 27 049 and 221 281 $/year, confirming its economic effectiveness. In addition, the study incorporates Vehicle‐to‐Grid (V2G) operation using an aggregated modeling approach, enabling bidirectional power flow and further enhancing system performance. The obtained results confirm that the proposed HGCO‐based approach effectively enhances both the technical performance and economic viability of modern RDS.