A multi-objective optimization model for fast electric vehicle charging stations with wind, PV power and energy storage

The construction of fast electric vehicle (EV) charging stations is critical for the development EV industry. integration renewable energy into comprises both threats and chances. A successful reasonable capacity configuration scheduling strategy beneficial significant. This paper studies optimal design with wind, PV power storage system (FEVCS-WPE), which determines components strategy. Firstly, an load simulation model considering demand response built, dynamically modified expectation under time-of-use electricity price. Secondly, based on design, a multi-objective optimization proposed minimum objectives cost pollution emissions. Then, this solved by hybrid algorithm combines particle swarm (MOPSO) Technique Order Preference Similarity to Ideal Solution (TOPSIS) method. Finally, framework applied case in Inner Mongolia, China. scenario analysis conducted concludes that supplies, connection utility grid can help improve performance objectives. sensitivity also performed verity model’s effectiveness. In addition, method compared simulated annealing genetic show its faster computation speed higher solution quality.