Evaluation of Heuristic Techniques for Solving the Short-Term Hydrothermal Scheduling based on Key Performance Indicators (KPIs)

Peter Vallejo-Correa, Carlos Barrera-Singaña, A. Valenzuela
{"title":"Evaluation of Heuristic Techniques for Solving the Short-Term Hydrothermal Scheduling based on Key Performance Indicators (KPIs)","authors":"Peter Vallejo-Correa, Carlos Barrera-Singaña, A. Valenzuela","doi":"10.1109/ETCM53643.2021.9590707","DOIUrl":null,"url":null,"abstract":"The economic operation of hydrothermal systems is one of the most challenging problems in the area of power systems because it is a non-linear and non-convex problem. The use of heuristic optimization methods are an attractive alternative to traditional deterministic methods by offering excellent quality in their results with an implementation that is characterized by having a simple concept. This document solves the hydrothermal coordination problem considering the hydraulic coupling of hydroelectric power plants and the valve point effect in thermal power plants using genetic algorithms (GA), the novel grey wolf algorithm (GWO) and particle swarm optimization method (PSO). In addition, different Key Performance Indicators are proposed to validate the performance achieved by each heuristic technique applied to the planning of the economic dispatch of a multiple set of thermal and hydroelectric power plants for a daily scheduling horizon of 24-hour.","PeriodicalId":438567,"journal":{"name":"2021 IEEE Fifth Ecuador Technical Chapters Meeting (ETCM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE Fifth Ecuador Technical Chapters Meeting (ETCM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ETCM53643.2021.9590707","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3

Abstract

The economic operation of hydrothermal systems is one of the most challenging problems in the area of power systems because it is a non-linear and non-convex problem. The use of heuristic optimization methods are an attractive alternative to traditional deterministic methods by offering excellent quality in their results with an implementation that is characterized by having a simple concept. This document solves the hydrothermal coordination problem considering the hydraulic coupling of hydroelectric power plants and the valve point effect in thermal power plants using genetic algorithms (GA), the novel grey wolf algorithm (GWO) and particle swarm optimization method (PSO). In addition, different Key Performance Indicators are proposed to validate the performance achieved by each heuristic technique applied to the planning of the economic dispatch of a multiple set of thermal and hydroelectric power plants for a daily scheduling horizon of 24-hour.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于关键绩效指标的热液短期调度启发式方法评价
水热系统的经济运行是电力系统领域最具挑战性的问题之一,因为它是一个非线性和非凸问题。启发式优化方法的使用是传统确定性方法的一个有吸引力的替代方案,因为它的实现以具有简单的概念为特征,提供了高质量的结果。本文采用遗传算法(GA)、新型灰狼算法(GWO)和粒子群优化方法(PSO)求解了考虑水电站水力耦合和火电厂阀点效应的水热协调问题。此外,提出了不同的关键绩效指标,以验证每种启发式技术应用于多组火电厂和水力发电厂24小时每日调度水平的经济调度规划所取得的绩效。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Relevant and Non-Redundant Feature Subset Selection Applied to the Detection of Malware in a Network Multi-objective Optimization of Active and Reactive Power to assess Bus Loadability Limit On the Monitoring of the Electromagnetic Fields Accompanying the Seismic and Volcanic Activity of the Chiles Volcano: Preliminary Results Text-based CAPTCHA Vulnerability Assessment using a Deep Learning-based Solver Secure Systems via Reconfigurable Intelligent Surfaces over Correlated Rayleigh Channels
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1