Coordinated Scheduling for Improving Uncertain Wind Power Adsorption in Electric Vehicles—Wind Integrated Power Systems by Multiobjective Optimization Approach
Yuanzheng Li, Zhixian Ni, Tianyang Zhao, Minghui Yu, Yun Liu, Lei Wu, Yong Zhao
Abstract
Electric vehicles (EVs) and renewable energy, such as wind power, have been widely utilized to meet the sustainable development of our society. To this end, research articles on the operation performance of the EV-wind integrated power system are important. This article proposes a coordinated scheduling model, which aims to improve the wind power adsorption while considering the energy conservation and emission reduction of thermal generators. Besides, to conduct a comprehensive investigation among these multiple objectives, we formulate the coordinated scheduling model as a multiobjective optimization problem. Then, a multiobjective optimization algorithm based on a parameter adaptive differential evolution is proposed to solve this problem. Simulation results based on a modified Midwestern USA power system verify that the proposed scheduling model could reveal the relationship among multiple objectives, and the integration of EVs can improve the wind power adsorption and cost effectiveness of the power system.