考虑最优日调度的混合整数粒子群优化双层规划模型

Korawitch Kaiyawong, Chakit Plongkrathoke, Keerati Chayakulkheeree
{"title":"考虑最优日调度的混合整数粒子群优化双层规划模型","authors":"Korawitch Kaiyawong, Chakit Plongkrathoke, Keerati Chayakulkheeree","doi":"10.4186/ej.2023.27.8.13","DOIUrl":null,"url":null,"abstract":". This paper proposes a bi-level optimization (BLO) approach for optimal battery energy storage system (BESS) allocation (OBA) in distribution network (DN) considering optimal BESS daily scheduling (OBDS). The objective is to obtain the best locations and daily scheduling of BESSs that minimize total energy loss in DNs. In the upper-level of the proposed BLO method, the OBA is solved by mixed-integer particle swarm optimization (MIPSO). Meanwhile, the OBDS is solved as a sub-problem by particle swarm optimization in the lower-level of BLO. The proposed BLO based OBA considering OBDS algorithm had been tested with IEEE 33-bus radial distribution test system using load profile of Thai’s power system during summer, winter, and rainy seasons comparing to mixed-integer genetic algorithm (MIGA) method. The simulation result showed that the proposed lower-level OBDS can efficiently minimize the total daily loss by BESS scheduling. Moreover, the proposed algorithm can also achieve the optimal placement of BESS.","PeriodicalId":11618,"journal":{"name":"Engineering Journal","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Bi-level Planning Model for Optimal Battery Energy Storage Allocation Considering Optimal Daily Scheduling Using Mixed-Integer Particle Swarm Optimization\",\"authors\":\"Korawitch Kaiyawong, Chakit Plongkrathoke, Keerati Chayakulkheeree\",\"doi\":\"10.4186/ej.2023.27.8.13\",\"DOIUrl\":null,\"url\":null,\"abstract\":\". This paper proposes a bi-level optimization (BLO) approach for optimal battery energy storage system (BESS) allocation (OBA) in distribution network (DN) considering optimal BESS daily scheduling (OBDS). The objective is to obtain the best locations and daily scheduling of BESSs that minimize total energy loss in DNs. In the upper-level of the proposed BLO method, the OBA is solved by mixed-integer particle swarm optimization (MIPSO). Meanwhile, the OBDS is solved as a sub-problem by particle swarm optimization in the lower-level of BLO. The proposed BLO based OBA considering OBDS algorithm had been tested with IEEE 33-bus radial distribution test system using load profile of Thai’s power system during summer, winter, and rainy seasons comparing to mixed-integer genetic algorithm (MIGA) method. The simulation result showed that the proposed lower-level OBDS can efficiently minimize the total daily loss by BESS scheduling. Moreover, the proposed algorithm can also achieve the optimal placement of BESS.\",\"PeriodicalId\":11618,\"journal\":{\"name\":\"Engineering Journal\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Engineering Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4186/ej.2023.27.8.13\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Engineering Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4186/ej.2023.27.8.13","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

摘要

本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bi-level Planning Model for Optimal Battery Energy Storage Allocation Considering Optimal Daily Scheduling Using Mixed-Integer Particle Swarm Optimization
. This paper proposes a bi-level optimization (BLO) approach for optimal battery energy storage system (BESS) allocation (OBA) in distribution network (DN) considering optimal BESS daily scheduling (OBDS). The objective is to obtain the best locations and daily scheduling of BESSs that minimize total energy loss in DNs. In the upper-level of the proposed BLO method, the OBA is solved by mixed-integer particle swarm optimization (MIPSO). Meanwhile, the OBDS is solved as a sub-problem by particle swarm optimization in the lower-level of BLO. The proposed BLO based OBA considering OBDS algorithm had been tested with IEEE 33-bus radial distribution test system using load profile of Thai’s power system during summer, winter, and rainy seasons comparing to mixed-integer genetic algorithm (MIGA) method. The simulation result showed that the proposed lower-level OBDS can efficiently minimize the total daily loss by BESS scheduling. Moreover, the proposed algorithm can also achieve the optimal placement of BESS.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信