Optimum location of electric vehicle charging station and DG production sources in power networks

Abstract— This paper investigates the optimal placement of electric vehicle (EV) charging stations and distributed generation (DG) sources in power networks to minimize power and voltage losses. With air pollution recognized as a leading environmental health risk, the transition to electric vehicles is posited as a sustainable solution to reduce greenhouse gas emissions. The study employs multi-objective optimization models, specifically utilizing algorithms such as Multi-Objective Particle Swarm Optimization (MOPSO) and Non-Dominated Sorting Genetic Algorithm II (NSGA-II), to determine ideal charging station locations. This approach aims to enhance network reliability while accommodating the increasing demand for EVs. This paper also addresses economic factors related to the construction of charging stations, highlighting the need for efficient management of charging times and locations to improve user experience. Additionally, it discusses the dual challenges of battery technology limitations and the necessity for widespread charging infrastructure. The research ultimately aims to contribute to sustainable development goals by providing insights into optimizing EV charging systems, thereby facilitating a smoother transition to cleaner transportation solutions.

Keywords:

Electric Vehicles (EVs) , Charging Stations , Distributed Generation (DG) , Power Loss Reduction , Multi-Objective Optimization.