An optimal subsidy scheduling strategy for electric vehicles in multi-energy systems

• Main Authors: Yubao Zhang, Hui Hou, Junli Huang, Qingyong Zhang, Aihong Tang, Shaohua Zhu
• Format: Article
• Language: English
• Published: Elsevier 2021-04-01
• Series: Energy Reports
• Subjects: Electric vehicles; Multi-beneficial; Game theory; Subsidy model; Scheduling strategy; Multi-energy systems
• Online Access: http://www.sciencedirect.com/science/article/pii/S2352484721001232

With the increasing demand for multi-purpose energy, multi-energy systems (MES) have become the trend of urban development. To coordinate disorder charging among electric vehicles(EVs) in MES, this paper presents an optimal subsidy scheduling strategy for EVs. The strategy can decrease the fluctuation of the load of grids. Firstly, we use Monte Carlo approach based on historical data to simulate users’ charging behaviors. Orderly charging model is established according to simulation results. Then, multi-beneficial model is established based on time of use(TOU) tariff. The multi-beneficial model can be optimized by using Particle Swarm Optimization(PSO). Next, Weber-Fechner law is applied to further enhance users’ satisfaction. Moreover, dynamic non-cooperative game simulation is used to adjust both the users and the grids’ behaviors. By using the method of traverse and PSO, data including the optimal subsidy time and quantity can be obtained. In the end, the results of case study show that multi-beneficial benefit increases by 23.19%, the users benefit increases by 1.33% and the grid benefit increases by 21.86%. This can prove that the strategy is beneficial both to the users and the grid.