ADN规划中储能系统的集成运行策略

Zheng Yunfei, Wang Yingxiang, Yan Jiong, Yi Chenying, Li Weiwei, Ning Yue, Chen Zhi, H. Zhijian
{"title":"ADN规划中储能系统的集成运行策略","authors":"Zheng Yunfei, Wang Yingxiang, Yan Jiong, Yi Chenying, Li Weiwei, Ning Yue, Chen Zhi, H. Zhijian","doi":"10.1109/ISGT-Asia.2019.8881603","DOIUrl":null,"url":null,"abstract":"This paper proposes an operation strategy of energy storage system, considering the effect of gaining profit and peak load shifting. In the strategy, the charging-discharging periods are divided based on the TOU price and the charging or discharging power in each period is determined by the actual operation of distribution network. This paper applies the strategy to Active Distribution Network (ADN) planning and establishes a bi-level programming model that includes investment layer and operation layer. Battery Energy Storage System (BESS) is selected as the research object and improved particle swarm optimization algorithm is used to solve the problem. The simulation results of an improved IEEE 33-bus distribution system and the comparison with an existing BESS operation strategy verify that the proposed strategy obtains better economic benefits and the effect of peak load shifting, and it is conducive to improving DG permeability.","PeriodicalId":257974,"journal":{"name":"2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An Integrated Operation Strategy of Energy Storage System in ADN Planning\",\"authors\":\"Zheng Yunfei, Wang Yingxiang, Yan Jiong, Yi Chenying, Li Weiwei, Ning Yue, Chen Zhi, H. Zhijian\",\"doi\":\"10.1109/ISGT-Asia.2019.8881603\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes an operation strategy of energy storage system, considering the effect of gaining profit and peak load shifting. In the strategy, the charging-discharging periods are divided based on the TOU price and the charging or discharging power in each period is determined by the actual operation of distribution network. This paper applies the strategy to Active Distribution Network (ADN) planning and establishes a bi-level programming model that includes investment layer and operation layer. Battery Energy Storage System (BESS) is selected as the research object and improved particle swarm optimization algorithm is used to solve the problem. The simulation results of an improved IEEE 33-bus distribution system and the comparison with an existing BESS operation strategy verify that the proposed strategy obtains better economic benefits and the effect of peak load shifting, and it is conducive to improving DG permeability.\",\"PeriodicalId\":257974,\"journal\":{\"name\":\"2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)\",\"volume\":\"7 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ISGT-Asia.2019.8881603\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Innovative Smart Grid Technologies - Asia (ISGT Asia)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISGT-Asia.2019.8881603","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

本文提出了一种考虑获取利润和调峰影响的储能系统运行策略。该策略根据分时电价划分充放电周期,每个周期的充放电功率由配电网的实际运行情况决定。本文将该策略应用于主动配电网(ADN)规划中,建立了包括投资层和运营层的双层规划模型。以电池储能系统(BESS)为研究对象,采用改进的粒子群优化算法求解该问题。对改进后的IEEE 33总线配电系统进行仿真,并与现有BESS运行策略进行对比,验证了所提策略具有更好的经济效益和移峰效果,有利于提高DG的渗透率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An Integrated Operation Strategy of Energy Storage System in ADN Planning
This paper proposes an operation strategy of energy storage system, considering the effect of gaining profit and peak load shifting. In the strategy, the charging-discharging periods are divided based on the TOU price and the charging or discharging power in each period is determined by the actual operation of distribution network. This paper applies the strategy to Active Distribution Network (ADN) planning and establishes a bi-level programming model that includes investment layer and operation layer. Battery Energy Storage System (BESS) is selected as the research object and improved particle swarm optimization algorithm is used to solve the problem. The simulation results of an improved IEEE 33-bus distribution system and the comparison with an existing BESS operation strategy verify that the proposed strategy obtains better economic benefits and the effect of peak load shifting, and it is conducive to improving DG permeability.
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