A Bilevel Multi-objective Planning of Electric Vehicle Charging Station Considering Uncertainty of Wind Power and Photovoltaic

Abstract

Purposes In order to meet the expansion planning needs of electric vehicle charging stations under the “double carbon” goal and study the influence of charging station location and capacity on the absorption of distributed power supply. Methods This paper establishes a multi-objective double-layer configuration optimization model considering the uncertainty and correlation of wind-power output, and analyzes the influence of charging behavior change of electric vehicle(EV) users on charging pile location and volume scheme under time of use(TOU) power price incentive. The upper layer comprehensively considers the two objective functions of operator investment and construction, operation and maintenance, network loss cost and the minimum equivalent cost of user charging and queuing. The upper layer also uses the improved multi-objective particle swarm optimization algorithm to generate pareto optimal planning scheme. In order to minimize the wind and light discarding rate, the lower model verifies the Pareto solution set generated by the upper model. Findings Finally, the model is verified by IEEE33 node road network diagram, and the optimal site selection scheme of charging piles under uncertain scenery is obtained.

Keywords

• uncertainty of wind power and photovoltaic power
• electric vehicle charging stations
• location and capacity determination
• bilevel programming model