Multi-Objective Optimization of Electric Vehicle Spare Capacity Based on User Wishes
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 wish...
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Format: | Article |
Language: | zho |
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Editorial Office of Journal of Shanghai Jiao Tong University
2023-11-01
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Series: | Shanghai Jiaotong Daxue xuebao |
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Online Access: | https://xuebao.sjtu.edu.cn/article/2023/1006-2467/1006-2467-57-11-1501.shtml |
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author | SHAO Ping, YANG Zhile, LI Kang, ZHU Xiaodong |
author_facet | SHAO Ping, YANG Zhile, LI Kang, ZHU Xiaodong |
author_sort | SHAO Ping, YANG Zhile, LI Kang, ZHU Xiaodong |
collection | DOAJ |
description | 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. |
first_indexed | 2024-03-09T10:48:09Z |
format | Article |
id | doaj.art-255f794758b9415fa1f3e52d28a3ebcd |
institution | Directory Open Access Journal |
issn | 1006-2467 |
language | zho |
last_indexed | 2024-03-09T10:48:09Z |
publishDate | 2023-11-01 |
publisher | Editorial Office of Journal of Shanghai Jiao Tong University |
record_format | Article |
series | Shanghai Jiaotong Daxue xuebao |
spelling | doaj.art-255f794758b9415fa1f3e52d28a3ebcd2023-12-01T09:44:15ZzhoEditorial Office of Journal of Shanghai Jiao Tong UniversityShanghai Jiaotong Daxue xuebao1006-24672023-11-0157111501151110.16183/j.cnki.jsjtu.2022.131Multi-Objective Optimization of Electric Vehicle Spare Capacity Based on User WishesSHAO Ping, YANG Zhile, LI Kang, ZHU Xiaodong01. School of Electrical and Information Engineering, Zhengzhou University, Zhengzhou 450001, China;2. Shenzhen Institute of Advanced Technology of the Chinese Academy of Sciences, Shenzhen 518000, Guangdong, China;3. School of Electronics and Electrical Engineering, University of Leeds, Leeds LS2 9JT, U.K.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.https://xuebao.sjtu.edu.cn/article/2023/1006-2467/1006-2467-57-11-1501.shtmlspare capacityuser wishesmulti-objectivemulti-time scaleload demand uncertainty |
spellingShingle | SHAO Ping, YANG Zhile, LI Kang, ZHU Xiaodong Multi-Objective Optimization of Electric Vehicle Spare Capacity Based on User Wishes Shanghai Jiaotong Daxue xuebao spare capacity user wishes multi-objective multi-time scale load demand uncertainty |
title | Multi-Objective Optimization of Electric Vehicle Spare Capacity Based on User Wishes |
title_full | Multi-Objective Optimization of Electric Vehicle Spare Capacity Based on User Wishes |
title_fullStr | Multi-Objective Optimization of Electric Vehicle Spare Capacity Based on User Wishes |
title_full_unstemmed | Multi-Objective Optimization of Electric Vehicle Spare Capacity Based on User Wishes |
title_short | Multi-Objective Optimization of Electric Vehicle Spare Capacity Based on User Wishes |
title_sort | multi objective optimization of electric vehicle spare capacity based on user wishes |
topic | spare capacity user wishes multi-objective multi-time scale load demand uncertainty |
url | https://xuebao.sjtu.edu.cn/article/2023/1006-2467/1006-2467-57-11-1501.shtml |
work_keys_str_mv | AT shaopingyangzhilelikangzhuxiaodong multiobjectiveoptimizationofelectricvehiclesparecapacitybasedonuserwishes |