A Bi-Objective Optimal Scheduling Method for the Charging and Discharging of EVs Considering the Uncertainty of Wind and Photovoltaic Output in the Context of Time-of-Use Electricity Price

Abstract

With the increasing share of renewable energy generation and the integration of large-scale electric vehicles (EVs) into the grid, the reasonable charging and discharging scheduling of electric vehicles is essential for the stable operation of power grid. Therefore, this paper proposes a bi-objective optimal scheduling strategy for microgrids based on the participation of electric vehicles in vehicle-to-grid technology (V2G) mode. Firstly, the system structure for electric vehicles participating in the charging and discharging schedule was established. Secondly, a bi-objective optimization model was formulated, considering load mean square error and user charging cost. A heuristic method was employed to handle constraints related to system energy balance and equipment output. Then, the Monte Carlo method was employed to simulate electric vehicle loads and to facilitate the generation of and reduction in scenario scenes. Finally, the model was solved using an improved multi-objective barebones particle swarm optimization algorithm. The simulation results show that the proposed scheduling strategy has a lower charging cost (CNY 11,032.4) and lower load mean square error (12.84 × 105 kW2) than the strategy employed in the comparison experiment, which ensures the economic and stable operation of the microgrid.

Keywords

• bi-objective optimal schedule
• charging and discharging
• generation of and reduction in scenarios
• improved barebones multi-objective particle algorithm
• V2G