Cargando…

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...

Descripción completa

Detalles Bibliográficos
Autores principales: Othman, Muhammad Murtadha, Abd Rahman, Nurulazmi, Musirin, Ismail, Fotuhi-Firuzabad, Mahmud, Rajabi-Ghahnavieh, Abbas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2015
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
_version_ 1782365194882646016
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
work_keys_str_mv AT othmanmuhammadmurtadha aheuristicrankingapproachoncapacitybenefitmargindeterminationusingparetobasedevolutionaryprogrammingtechnique
AT abdrahmannurulazmi aheuristicrankingapproachoncapacitybenefitmargindeterminationusingparetobasedevolutionaryprogrammingtechnique
AT musirinismail aheuristicrankingapproachoncapacitybenefitmargindeterminationusingparetobasedevolutionaryprogrammingtechnique
AT fotuhifiruzabadmahmud aheuristicrankingapproachoncapacitybenefitmargindeterminationusingparetobasedevolutionaryprogrammingtechnique
AT rajabighahnaviehabbas aheuristicrankingapproachoncapacitybenefitmargindeterminationusingparetobasedevolutionaryprogrammingtechnique
AT othmanmuhammadmurtadha heuristicrankingapproachoncapacitybenefitmargindeterminationusingparetobasedevolutionaryprogrammingtechnique
AT abdrahmannurulazmi heuristicrankingapproachoncapacitybenefitmargindeterminationusingparetobasedevolutionaryprogrammingtechnique
AT musirinismail heuristicrankingapproachoncapacitybenefitmargindeterminationusingparetobasedevolutionaryprogrammingtechnique
AT fotuhifiruzabadmahmud heuristicrankingapproachoncapacitybenefitmargindeterminationusingparetobasedevolutionaryprogrammingtechnique
AT rajabighahnaviehabbas heuristicrankingapproachoncapacitybenefitmargindeterminationusingparetobasedevolutionaryprogrammingtechnique