求解混合动力经济排放调度的进化优化算法约束处理方法

Yubin Yao, Tianfeng Ren
{"title":"求解混合动力经济排放调度的进化优化算法约束处理方法","authors":"Yubin Yao, Tianfeng Ren","doi":"10.1109/AEES56284.2022.10079493","DOIUrl":null,"url":null,"abstract":"With the rapid development of renewable energy, hybrid dynamic economic emission dispatch (HDEED) which considering renewable energy has gradually become a heated topic. HDEED is a non-convex, strongly constrained, high-dimensional multi-objective optimization problem, which usually solved by evolutionary optimization algorithm. In order to meet the constraints in HDEED, this paper proposes a new constraints handling method. The proposed method distributes the imbalance power among power generators in a weighted or prioritized way under the premise of preferential consumption of renewable energy and satisfying inequality constraints. The method not only meets all constraints in HDEED problem, but also improves convergence of the algorithm and the diversity of the Pareto solution set. A case involving thermal power units, wind farms and photovoltaic plant is used to test the performance of the proposed method which combined with a classical multi-objective evolutionary optimization algorithm NSGA-II. The result shows that the proposed method is effective and superior to the compared methods.","PeriodicalId":227496,"journal":{"name":"2022 3rd International Conference on Advanced Electrical and Energy Systems (AEES)","volume":"11 3","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Constraints Handling Method for Evolutionary Optimization Algorithm in Solving Hybrid Dynamic Economic Emission Dispatch\",\"authors\":\"Yubin Yao, Tianfeng Ren\",\"doi\":\"10.1109/AEES56284.2022.10079493\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the rapid development of renewable energy, hybrid dynamic economic emission dispatch (HDEED) which considering renewable energy has gradually become a heated topic. HDEED is a non-convex, strongly constrained, high-dimensional multi-objective optimization problem, which usually solved by evolutionary optimization algorithm. In order to meet the constraints in HDEED, this paper proposes a new constraints handling method. The proposed method distributes the imbalance power among power generators in a weighted or prioritized way under the premise of preferential consumption of renewable energy and satisfying inequality constraints. The method not only meets all constraints in HDEED problem, but also improves convergence of the algorithm and the diversity of the Pareto solution set. A case involving thermal power units, wind farms and photovoltaic plant is used to test the performance of the proposed method which combined with a classical multi-objective evolutionary optimization algorithm NSGA-II. The result shows that the proposed method is effective and superior to the compared methods.\",\"PeriodicalId\":227496,\"journal\":{\"name\":\"2022 3rd International Conference on Advanced Electrical and Energy Systems (AEES)\",\"volume\":\"11 3\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 3rd International Conference on Advanced Electrical and Energy Systems (AEES)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/AEES56284.2022.10079493\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 3rd International Conference on Advanced Electrical and Energy Systems (AEES)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AEES56284.2022.10079493","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

摘要

随着可再生能源的快速发展,考虑可再生能源的混合动力经济排放调度(HDEED)逐渐成为人们关注的热点。HDEED是一个非凸、强约束、高维的多目标优化问题,通常采用进化优化算法求解。为了满足HDEED中的约束,本文提出了一种新的约束处理方法。该方法在优先使用可再生能源和满足不平等约束的前提下,对不平衡功率在发电机组之间进行加权或优先分配。该方法不仅满足HDEED问题的所有约束条件,而且提高了算法的收敛性和Pareto解集的多样性。以火电机组、风电场和光伏电站为例,结合经典的多目标进化优化算法NSGA-II,验证了所提方法的性能。结果表明,所提出的方法是有效的,并且优于比较的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Constraints Handling Method for Evolutionary Optimization Algorithm in Solving Hybrid Dynamic Economic Emission Dispatch
With the rapid development of renewable energy, hybrid dynamic economic emission dispatch (HDEED) which considering renewable energy has gradually become a heated topic. HDEED is a non-convex, strongly constrained, high-dimensional multi-objective optimization problem, which usually solved by evolutionary optimization algorithm. In order to meet the constraints in HDEED, this paper proposes a new constraints handling method. The proposed method distributes the imbalance power among power generators in a weighted or prioritized way under the premise of preferential consumption of renewable energy and satisfying inequality constraints. The method not only meets all constraints in HDEED problem, but also improves convergence of the algorithm and the diversity of the Pareto solution set. A case involving thermal power units, wind farms and photovoltaic plant is used to test the performance of the proposed method which combined with a classical multi-objective evolutionary optimization algorithm NSGA-II. The result shows that the proposed method is effective and superior to the compared methods.
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