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

被引：0
|
作者：
Sun Y. [1 ]
Ge M. [1 ]
Wang X. [2 ]
Bao H. [1 ]
Yang H. [1 ]
Yao T. [2 ]
机构：
[1] School of Electrical and Electronic Engineering, North China Electric Power University, Beijing
[2] Information and Telecommunication Branch, State Grid Hebei Electric Power Co., Ltd., Shijiazhuang
来源：
Shanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University | 2024年 / 58卷 / 05期
关键词：
charging compensation; distributed renewable energy (DRE); electric vehicle (EV); time anxiety;
D O I：
10.16183/j.cnki.jsjtu.2022.348
中图分类号：
学科分类号：
摘要：
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 arc 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. © 2024 Shanghai Jiaotong University. All rights reserved.
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页码：636 / 646
页数：10
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