Multi-Objective Optimization of Electric Vehicle Spare Capacity Based on User Wishes

被引：0
|
作者：
Shao P. [1 ]
Yang Z. [2 ]
Li K. [3 ]
Zhu X. [1 ]
机构：
[1] School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou
[2] Shenzhen Institute of Advanced Technology, The Chinese Academy of Sciences, Guangdong, Shenzhen
[3] School of Electronics and Electrical Engineering, University of Leeds, Leeds
来源：
Shanghai Jiaotong Daxue Xuebao/Journal of Shanghai Jiaotong University | 2023年 / 57卷 / 11期
关键词：
load demand uncertainty; multi-objective; multi-time scale; spare capacity; user wishes;
D O I：
10.16183/j.cnki.jsjtu.2022.131
中图分类号：
学科分类号：
摘要：
Due to the considerable number and the characteristics of energy storage, it is possible for electric vehicles (EVs) to participate in the operation and regulation of power system to provide reserve service. In view of this, a multi-objective optimal scheduling model is established based on the wishes of electric vehicle users, with the objectives of the economic benefits of electricity collectors, microgrid power fluctuations and user satisfaction. Considering the uncertainty of load demand, the optimal scheduling analysis of multi-time scale scenes with the day-ahead time scale and the intra-day real-time correction time scale is conducted. The mainstream multi-objective intelligent optimization algorithm NSGA-III algorithm is adopted in the solution method, and the NSGA-II and MOEA/D algorithms are used for comparison. The optimal dispatching scheme is selected through comparative experiments and scenarios where EVs provide spare capacity are analyzed. The simulation results verify the feasibility and effectiveness of the proposed model. © 2023 Shanghai Jiao Tong University. All rights reserved.
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页码：1501 / 1511
页数：10
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