Metaheuristic-Based Optimization for Electric Vehicle Charging Station Deployment in the Electrical Distribution Networks

The transportation sector is one of the largest consumers of fossil fuels globally. To alleviate the environmental impact of hazardous emissions and mitigate dependence on conventional fossil fuels, electrifying the transportation network, including the adoption of electrical vehicles (EVs), has become imperative. For the successful deployment of EVs, a robust and well-planned charging infrastructure is essential. Among the challenges, the optimum placement of charging stations (CSs) stands out as a critical issue. This study proposes an effective approach to determine the optimum locations of electric vehicle charging stations (EVCSs) in the East Delta Network (EDN). Transition to electric mobility significantly impacts the electric distribution system parameters. Thus, key considerations in deploying EVCSs include real and reactive power loss, and installation costs. Additionally, integrating EVCSs into the electrical system increases energy demand on the grid. To address this, the research recommends incorporating renewable energy sources (RESs) at strategic locations within the electrical system to alleviate the additional load imposed by EVCSs, thereby enhancing system reliability and sustainability. This paper also evaluates the electric distribution system reliability after deploying EVCSs and RESs. Six cases are proposed to analyze the deployment of EVCSs, with and without RESs integration. As a result, the total loss is reduced from 1021.34 kW to 832.23 kW in all cases.