An Arithmetic Optimization Algorithm for the Optimal Deployment of Electric Vehicle Fast Charging Stations in the Distribution Network with PV Integration
Received: 4 September 2025 | Revised: 12 October 2025 | Accepted: 18 October 2025 | Online: 17 November 2025
Corresponding author: Hung Duc Nguyen
Abstract
Electric Vehicles (EVs) have attracted significant interest from the automotive sector and government bodies due to their lower carbon dioxide emissions and reduced maintenance and operational expenses. However, the increasing adoption of EVs impacts distribution network factors, including power losses and voltage stability. To ensure network reliability, it is crucial to strategically locate EV Fast-Charging Stations (EV-FCSs). This study presents a two-stage approach for optimal FCS placement. In Stage 1, a Charging Station Owner Decision Index (CSODI) is proposed to identify cost-effective locations with high EV traffic. In Stage 2, an Enhanced Arithmetic Optimization Algorithm (EAOA) is applied to minimize real power loss and investment costs, while ensuring that system constraints are met. The proposed method is validated using the IEEE 34-bus distribution system under two scenarios: one without Vehicle-to-Grid (V2G) and the other with V2G. Further analysis considers three subcases: optimizing for investment cost (Case 1), a balanced trade-off (Case 2), and power loss minimization (Case 3). The results demonstrate that V2G significantly reduces power loss and improves voltage stability across all cases, with Case 2 offering the best balance between cost and efficiency. The findings confirm that optimized FCS placement, coupled with V2G and renewable integration, enhances grid performance, sustainability, and cost efficiency in modern distribution networks.
Keywords:
distribution networks, electric vehicles, fast charging stations, distributed generationDownloads
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