An Improved Mean-Variance Optimization for Nonconvex Economic Dispatch Problems
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kim, Min Jeong | - |
dc.contributor.author | Song, Hyoung-Yong | - |
dc.contributor.author | Park, Jong-Bae | - |
dc.contributor.author | Roh, Jae-Hyung | - |
dc.contributor.author | Lee, Sang Un | - |
dc.contributor.author | Son, Sung-Yong | - |
dc.date.available | 2020-02-29T00:46:05Z | - |
dc.date.created | 2020-02-06 | - |
dc.date.issued | 2013-01 | - |
dc.identifier.issn | 1975-0102 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/14830 | - |
dc.description.abstract | This paper presents an efficient approach for solving economic dispatch (ED) problems with nonconvex cost functions using a 'Mean-Variance Optimization (MVO)' algorithm with Kuhn-Tucker condition and swap process. The aim of the ED problem, one of the most important activities in power system operation and planning, is to determine the optimal combination of power outputs of all generating units so as to meet the required load demand at minimum operating cost while satisfying system equality and inequality constraints. This paper applies Kuhn-Tucker condition and swap process to a MVO algorithm to improve a global minimum searching capability. The proposed MVO is applied to three different nonconvex ED problems with valve-point effects, prohibited operating zones, transmission network losses, and multi-fuels with valve-point effects. Additionally, it is applied to the large-scale power system of Korea. The results are compared with those of the state-of-the-art methods as well. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | KOREAN INST ELECTR ENG | - |
dc.relation.isPartOf | JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY | - |
dc.subject | PARTICLE SWARM OPTIMIZATION | - |
dc.subject | LOAD DISPATCH | - |
dc.subject | GENETIC ALGORITHM | - |
dc.subject | COST-FUNCTIONS | - |
dc.subject | UNITS | - |
dc.subject | PSO | - |
dc.title | An Improved Mean-Variance Optimization for Nonconvex Economic Dispatch Problems | - |
dc.type | Article | - |
dc.type.rims | ART | - |
dc.description.journalClass | 1 | - |
dc.identifier.wosid | 000313152300010 | - |
dc.identifier.doi | 10.5370/JEET.2013.8.1.080 | - |
dc.identifier.bibliographicCitation | JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY, v.8, no.1, pp.80 - 89 | - |
dc.identifier.kciid | ART001727635 | - |
dc.identifier.scopusid | 2-s2.0-84872025528 | - |
dc.citation.endPage | 89 | - |
dc.citation.startPage | 80 | - |
dc.citation.title | JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY | - |
dc.citation.volume | 8 | - |
dc.citation.number | 1 | - |
dc.contributor.affiliatedAuthor | Son, Sung-Yong | - |
dc.type.docType | Article | - |
dc.subject.keywordAuthor | Nonconvex optimization | - |
dc.subject.keywordAuthor | Economic dispatch | - |
dc.subject.keywordAuthor | Mean-variance optimization | - |
dc.subject.keywordAuthor | Kuhn-Tucker condition | - |
dc.subject.keywordPlus | PARTICLE SWARM OPTIMIZATION | - |
dc.subject.keywordPlus | LOAD DISPATCH | - |
dc.subject.keywordPlus | GENETIC ALGORITHM | - |
dc.subject.keywordPlus | COST-FUNCTIONS | - |
dc.subject.keywordPlus | UNITS | - |
dc.subject.keywordPlus | PSO | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.description.journalRegisteredClass | kci | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
1342, Seongnam-daero, Sujeong-gu, Seongnam-si, Gyeonggi-do, Republic of Korea(13120)031-750-5114
COPYRIGHT 2020 Gachon University All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.