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A Heuristic Ranking Approach on Capacity Benefit Margin Determination Using Pareto-Based Evolutionary Programming Technique
This paper introduces a novel multiobjective approach for capacity benefit margin (CBM) assessment taking into account tie-line reliability of interconnected systems. CBM is the imperative information utilized as a reference by the load-serving entities (LSE) to estimate a certain margin of transfer...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi Publishing Corporation
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4386672/ https://www.ncbi.nlm.nih.gov/pubmed/25879068 http://dx.doi.org/10.1155/2015/731013 |
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author | Othman, Muhammad Murtadha Abd Rahman, Nurulazmi Musirin, Ismail Fotuhi-Firuzabad, Mahmud Rajabi-Ghahnavieh, Abbas |
author_facet | Othman, Muhammad Murtadha Abd Rahman, Nurulazmi Musirin, Ismail Fotuhi-Firuzabad, Mahmud Rajabi-Ghahnavieh, Abbas |
author_sort | Othman, Muhammad Murtadha |
collection | PubMed |
description | This paper introduces a novel multiobjective approach for capacity benefit margin (CBM) assessment taking into account tie-line reliability of interconnected systems. CBM is the imperative information utilized as a reference by the load-serving entities (LSE) to estimate a certain margin of transfer capability so that a reliable access to generation through interconnected system could be attained. A new Pareto-based evolutionary programming (EP) technique is used to perform a simultaneous determination of CBM for all areas of the interconnected system. The selection of CBM at the Pareto optimal front is proposed to be performed by referring to a heuristic ranking index that takes into account system loss of load expectation (LOLE) in various conditions. Eventually, the power transfer based available transfer capability (ATC) is determined by considering the firm and nonfirm transfers of CBM. A comprehensive set of numerical studies are conducted on the modified IEEE-RTS79 and the performance of the proposed method is numerically investigated in detail. The main advantage of the proposed technique is in terms of flexibility offered to an independent system operator in selecting an appropriate solution of CBM simultaneously for all areas. |
format | Online Article Text |
id | pubmed-4386672 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Hindawi Publishing Corporation |
record_format | MEDLINE/PubMed |
spelling | pubmed-43866722015-04-15 A Heuristic Ranking Approach on Capacity Benefit Margin Determination Using Pareto-Based Evolutionary Programming Technique Othman, Muhammad Murtadha Abd Rahman, Nurulazmi Musirin, Ismail Fotuhi-Firuzabad, Mahmud Rajabi-Ghahnavieh, Abbas ScientificWorldJournal Research Article This paper introduces a novel multiobjective approach for capacity benefit margin (CBM) assessment taking into account tie-line reliability of interconnected systems. CBM is the imperative information utilized as a reference by the load-serving entities (LSE) to estimate a certain margin of transfer capability so that a reliable access to generation through interconnected system could be attained. A new Pareto-based evolutionary programming (EP) technique is used to perform a simultaneous determination of CBM for all areas of the interconnected system. The selection of CBM at the Pareto optimal front is proposed to be performed by referring to a heuristic ranking index that takes into account system loss of load expectation (LOLE) in various conditions. Eventually, the power transfer based available transfer capability (ATC) is determined by considering the firm and nonfirm transfers of CBM. A comprehensive set of numerical studies are conducted on the modified IEEE-RTS79 and the performance of the proposed method is numerically investigated in detail. The main advantage of the proposed technique is in terms of flexibility offered to an independent system operator in selecting an appropriate solution of CBM simultaneously for all areas. Hindawi Publishing Corporation 2015 2015-03-23 /pmc/articles/PMC4386672/ /pubmed/25879068 http://dx.doi.org/10.1155/2015/731013 Text en Copyright © 2015 Muhammad Murtadha Othman et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Othman, Muhammad Murtadha Abd Rahman, Nurulazmi Musirin, Ismail Fotuhi-Firuzabad, Mahmud Rajabi-Ghahnavieh, Abbas A Heuristic Ranking Approach on Capacity Benefit Margin Determination Using Pareto-Based Evolutionary Programming Technique |
title | A Heuristic Ranking Approach on Capacity Benefit Margin Determination Using Pareto-Based Evolutionary Programming Technique |
title_full | A Heuristic Ranking Approach on Capacity Benefit Margin Determination Using Pareto-Based Evolutionary Programming Technique |
title_fullStr | A Heuristic Ranking Approach on Capacity Benefit Margin Determination Using Pareto-Based Evolutionary Programming Technique |
title_full_unstemmed | A Heuristic Ranking Approach on Capacity Benefit Margin Determination Using Pareto-Based Evolutionary Programming Technique |
title_short | A Heuristic Ranking Approach on Capacity Benefit Margin Determination Using Pareto-Based Evolutionary Programming Technique |
title_sort | heuristic ranking approach on capacity benefit margin determination using pareto-based evolutionary programming technique |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4386672/ https://www.ncbi.nlm.nih.gov/pubmed/25879068 http://dx.doi.org/10.1155/2015/731013 |
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