Multi-Region Optimal Scheduling Strategy for Electric Vehicles Considering Compensation Incentives

Abstract

Aimed at the problem of uneven supply and distributed renewable energy (DRE) in charging regions and electric vehicle (EV) loads, a multi-region optimal scheduling strategy for EVs considering compensation incentives is proposed to guide EVs to choose different charging regions, so as to promote local consumption of distributed energy. First, an EV charging response model is established based on the price elasticity of demand and users’ time anxiety. Then, based on the principle of remaining power availability and idle time redundancy, EVs are divided into responsive cluster and non-responsive cluster. A charging area decision model based on regret theory is used to further divide the responsive cluster by region. Finally, a multi-region optimal scheduling model for EVs is established, and the charging price is optimized in terms of maximizing the economic benefits of charging service providers and the consumption of DRE. Simulation cases show that the proposed optimization strategy can fully consider the impact of time anxiety and price elasticity on EV users, fully tap the users’ response potential, and has obvious effects in reducing the deviation of distributed new energy consumption and improving the economic benefits of charging service providers.

Keywords

• electric vehicle (ev)
• distributed renewable energy (dre)
• charging compensation
• time anxiety