RESERVOIR OPERATION USING HYBRID OPTIMIZATION ALGORITHMS
DC Field | Value | Language |
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dc.contributor.author | Ho, V. H. | - |
dc.contributor.author | Kougias, I. | - |
dc.contributor.author | Kim, J. H. | - |
dc.date.accessioned | 2021-09-04T18:30:29Z | - |
dc.date.available | 2021-09-04T18:30:29Z | - |
dc.date.created | 2021-06-15 | - |
dc.date.issued | 2015-03 | - |
dc.identifier.issn | 1790-7632 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/94192 | - |
dc.description.abstract | In the present paper, the authors present a new hybrid optimization technique toward optimum reservoir planning and operation. The basis of the developed hybrid algorithms is the combination of harmony search (HS) and incremental dynamic programming (IDP). This resulted in the development of a new algorithm and two variants, all of which are described in detail. The algorithms were used for optimally operating the Huong Dien hydroelectric dam, located in the Hue Basin in central Vietnam. Initially, the authors designed the model that describes the water balance equation and the operation of the hydroelectric station. The developed algorithms were then used for defining the optimum reservoir operation (ORO), using observed records of the years 1997-2005. The aims of ORO include maximum hydropower energy production, flood prevention and ensuring drinking/irrigation water availability. In addition to that, the present study investigated probable future alterations in the reservoir's operation. The hybrid algorithm that showed the best performance in the first phase was selected for processing meteorological data of different future climate scenarios (2020-2039). Following the calibration of the climate model on observed data, the created hybrid method optimized the operation of Huong Dien reservoir, indicatively for the target-year 2020. Finally, the ranges of the decision variables that result in the best management have been defined, offering a framework for efficient scheduling under environmental change. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | GLOBAL NETWORK ENVIRONMENTAL SCIENCE & TECHNOLOGY | - |
dc.subject | HARMONY SEARCH | - |
dc.subject | SYSTEM OPERATION | - |
dc.subject | MODEL | - |
dc.subject | SIMULATION | - |
dc.title | RESERVOIR OPERATION USING HYBRID OPTIMIZATION ALGORITHMS | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, J. H. | - |
dc.identifier.scopusid | 2-s2.0-84928165371 | - |
dc.identifier.wosid | 000352254200011 | - |
dc.identifier.bibliographicCitation | GLOBAL NEST JOURNAL, v.17, no.1, pp.103 - 117 | - |
dc.relation.isPartOf | GLOBAL NEST JOURNAL | - |
dc.citation.title | GLOBAL NEST JOURNAL | - |
dc.citation.volume | 17 | - |
dc.citation.number | 1 | - |
dc.citation.startPage | 103 | - |
dc.citation.endPage | 117 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Environmental Sciences & Ecology | - |
dc.relation.journalWebOfScienceCategory | Environmental Sciences | - |
dc.subject.keywordPlus | HARMONY SEARCH | - |
dc.subject.keywordPlus | SYSTEM OPERATION | - |
dc.subject.keywordPlus | MODEL | - |
dc.subject.keywordPlus | SIMULATION | - |
dc.subject.keywordAuthor | Reservoir Operation | - |
dc.subject.keywordAuthor | Water Resources Management | - |
dc.subject.keywordAuthor | Hybrid Optimization Algorithms | - |
dc.subject.keywordAuthor | Harmony Search | - |
dc.subject.keywordAuthor | Hydropower | - |
dc.subject.keywordAuthor | Climate Change | - |
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