Uncertainty Modeling for the Management of Distributed Generation Units using PSO

V. S. Pappala, I. Erlich
{"title":"Uncertainty Modeling for the Management of Distributed Generation Units using PSO","authors":"V. S. Pappala, I. Erlich","doi":"10.1109/PCT.2007.4538367","DOIUrl":null,"url":null,"abstract":"This paper addresses a multistage stochastic model for the operation of distributed generation (DG) units under stochastic load demands. The stochastic load demands have a significant effect on the economic model of the DG units. The uncertainties are modeled as scenario trees. But as the number of decision making stages increase, the scenario tree becomes extremely large, which leads to complex computation. Therefore a novel approach to generate a scenario tree using classical particle swarm optimization (PSO) approach is presented. The resulting multistage nonlinear stochastic model is solved using adaptive PSO.","PeriodicalId":356805,"journal":{"name":"2007 IEEE Lausanne Power Tech","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 IEEE Lausanne Power Tech","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PCT.2007.4538367","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7

Abstract

This paper addresses a multistage stochastic model for the operation of distributed generation (DG) units under stochastic load demands. The stochastic load demands have a significant effect on the economic model of the DG units. The uncertainties are modeled as scenario trees. But as the number of decision making stages increase, the scenario tree becomes extremely large, which leads to complex computation. Therefore a novel approach to generate a scenario tree using classical particle swarm optimization (PSO) approach is presented. The resulting multistage nonlinear stochastic model is solved using adaptive PSO.
基于粒子群算法的分布式发电机组管理的不确定性建模
本文研究了随机负荷条件下分布式发电机组运行的多阶段随机模型。随机负荷需求对发电机组的经济模型有重要影响。不确定性以情景树的形式建模。但随着决策阶段的增加,情景树会变得非常庞大,导致计算复杂。为此,提出了一种利用经典粒子群算法生成场景树的新方法。采用自适应粒子群算法求解得到的多阶段非线性随机模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
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