基于混沌映射优化BOA算法的微电网群经济优化调度

Q2 Energy
Milu Zhou, Yu Wang, Tingting Li, Tian Yang, Xi Luo
{"title":"基于混沌映射优化BOA算法的微电网群经济优化调度","authors":"Milu Zhou,&nbsp;Yu Wang,&nbsp;Tingting Li,&nbsp;Tian Yang,&nbsp;Xi Luo","doi":"10.1186/s42162-024-00422-3","DOIUrl":null,"url":null,"abstract":"<div><p>Due to the intermittency and volatility of distributed power sources, the microgrid system has poor stability and high operation cost. Therefore, the study proposes an economic optimization scheduling strategy based on the chaotic mapping butterfly optimization algorithm and the mathematical model of microgrid group system. The study creates simulation trials of function poles and microgrid group operation to confirm the strategy’s efficacy. According to the experimental findings, the multimodal function of the enhanced butterfly optimization method had a variance of 0.0000E + 00, and the function’s optimal value was less than 10–30, and the calculation time is 4.5s. The variance on the fixed dimensional function was 0.0000E + 00 and the optimal value of the function was 10 − 3.5,and the calculation time is 4.7s. The algorithmic curve all digging depth was maximum and convergence speed was fastest. The microgrid group system had the lowest economic cost of 4029.32 yuan in the grid-connected mode and 3343.39 yuan in the off-grid mode. The study proves that the energy coordination and economic management of this strategy are greatly optimized, which can effectively protect the energy storage equipment and guarantee the smooth power consumption of the system. This provides an innovative theoretical basis for optimization scheduling of microgrid group.</p></div>","PeriodicalId":538,"journal":{"name":"Energy Informatics","volume":"7 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://energyinformatics.springeropen.com/counter/pdf/10.1186/s42162-024-00422-3","citationCount":"0","resultStr":"{\"title\":\"Economic optimization scheduling of microgrid group based on chaotic mapping optimization BOA algorithm\",\"authors\":\"Milu Zhou,&nbsp;Yu Wang,&nbsp;Tingting Li,&nbsp;Tian Yang,&nbsp;Xi Luo\",\"doi\":\"10.1186/s42162-024-00422-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Due to the intermittency and volatility of distributed power sources, the microgrid system has poor stability and high operation cost. Therefore, the study proposes an economic optimization scheduling strategy based on the chaotic mapping butterfly optimization algorithm and the mathematical model of microgrid group system. The study creates simulation trials of function poles and microgrid group operation to confirm the strategy’s efficacy. According to the experimental findings, the multimodal function of the enhanced butterfly optimization method had a variance of 0.0000E + 00, and the function’s optimal value was less than 10–30, and the calculation time is 4.5s. The variance on the fixed dimensional function was 0.0000E + 00 and the optimal value of the function was 10 − 3.5,and the calculation time is 4.7s. The algorithmic curve all digging depth was maximum and convergence speed was fastest. The microgrid group system had the lowest economic cost of 4029.32 yuan in the grid-connected mode and 3343.39 yuan in the off-grid mode. The study proves that the energy coordination and economic management of this strategy are greatly optimized, which can effectively protect the energy storage equipment and guarantee the smooth power consumption of the system. This provides an innovative theoretical basis for optimization scheduling of microgrid group.</p></div>\",\"PeriodicalId\":538,\"journal\":{\"name\":\"Energy Informatics\",\"volume\":\"7 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-12-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://energyinformatics.springeropen.com/counter/pdf/10.1186/s42162-024-00422-3\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Energy Informatics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://link.springer.com/article/10.1186/s42162-024-00422-3\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Energy\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Energy Informatics","FirstCategoryId":"1085","ListUrlMain":"https://link.springer.com/article/10.1186/s42162-024-00422-3","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Energy","Score":null,"Total":0}
引用次数: 0

摘要

由于分布式电源的间歇性和波动性,微电网系统稳定性差,运行成本高。因此,本研究提出了一种基于混沌映射蝴蝶优化算法和微网群系统数学模型的经济优化调度策略。通过功能极和微网群运行的仿真试验,验证了该策略的有效性。实验结果表明,增强型蝶形优化方法的多模态函数方差为0.0000E + 00,函数最优值小于10-30,计算时间为4.5s。定维函数的方差为0.0000E + 00,函数的最优值为10−3.5,计算时间为4.7s。算法曲线全部挖掘深度最大,收敛速度最快。微网群系统并网模式的经济成本最低,为4029.32元,离网模式为3343.39元。研究证明,该策略的能量协调和经济管理得到了极大的优化,可以有效地保护储能设备,保证系统的平稳用电。这为微网群优化调度提供了创新的理论基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Economic optimization scheduling of microgrid group based on chaotic mapping optimization BOA algorithm

Due to the intermittency and volatility of distributed power sources, the microgrid system has poor stability and high operation cost. Therefore, the study proposes an economic optimization scheduling strategy based on the chaotic mapping butterfly optimization algorithm and the mathematical model of microgrid group system. The study creates simulation trials of function poles and microgrid group operation to confirm the strategy’s efficacy. According to the experimental findings, the multimodal function of the enhanced butterfly optimization method had a variance of 0.0000E + 00, and the function’s optimal value was less than 10–30, and the calculation time is 4.5s. The variance on the fixed dimensional function was 0.0000E + 00 and the optimal value of the function was 10 − 3.5,and the calculation time is 4.7s. The algorithmic curve all digging depth was maximum and convergence speed was fastest. The microgrid group system had the lowest economic cost of 4029.32 yuan in the grid-connected mode and 3343.39 yuan in the off-grid mode. The study proves that the energy coordination and economic management of this strategy are greatly optimized, which can effectively protect the energy storage equipment and guarantee the smooth power consumption of the system. This provides an innovative theoretical basis for optimization scheduling of microgrid group.

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
Energy Informatics
Energy Informatics Computer Science-Computer Networks and Communications
CiteScore
5.50
自引率
0.00%
发文量
34
审稿时长
5 weeks
×
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