Coordinated Stochastic Scheduling for Improving Wind Power Adsorption in Electric Vehicles-Wind Integrated Power Systems by Multi-objective Optimization Approach

Electric vehicles (EVs) and renewable energy (RE), such as wind power, have been widely utilized to meet the sustainable development of our society. To this end, researches on operation performance of the EV-wind integrated power system are important. This paper proposes a coordinated stochastic scheduling model based on a multi-objective optimization approach, which aims to improve wind power adsorption while considering energy conservation and emission reduction of thermal generators. Besides, to conduct comprehensive investigation among these multiple objectives, we formulate the coordinated stochastic scheduling model as a multi-objective optimization problem. Then, a multi-objective optimization algorithm based on a parameter adaptive differential evolution is proposed to solve this problem. Simulation results based on a modified Midwestern US power system verify that the proposed scheduling model could reveal the relationship among multiple objectives, and the integration of EVs can improve wind power adsorption and cost effectiveness of the power system.