Multi-objective evolutionary programming for solving economic dispatch problem

Economic dispatch (ED) is an optimisation strategy to ensure power systems operate in an economic manner. This paper proposes a multi-objective optimisation method to minimise the total generation cost and total system loss simultaneously and find the best adjustment for this economic dispatch probl...

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Main Authors: Adnan N.A., Mansor M.H., Roslan N., Musirin I., Khader P.S.A., Kamil K., Jelani S., Zuhdi A.W.M.
Other Authors: 57212722015
Format: Article
Published: World Academy of Research in Science and Engineering 2023
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spelling my.uniten.dspace-248732023-05-29T15:28:10Z Multi-objective evolutionary programming for solving economic dispatch problem Adnan N.A. Mansor M.H. Roslan N. Musirin I. Khader P.S.A. Kamil K. Jelani S. Zuhdi A.W.M. 57212722015 56372667100 57205233093 8620004100 36926269300 57195622807 57193388570 56589966300 Economic dispatch (ED) is an optimisation strategy to ensure power systems operate in an economic manner. This paper proposes a multi-objective optimisation method to minimise the total generation cost and total system loss simultaneously and find the best adjustment for this economic dispatch problem. This study focused on solving the multi-objective economic dispatch problem using a Heuristic Optimisation (HO) method, namely Multi-Objective Evolutionary Programming (MOEP). The Weighted Sum Method (WSM) is integrated with EP to find a trade-off solution between two objectives: total generation cost minimisation and total system loss minimisation. The practicable proposed method was tested on the IEEE 30-Bus Reliability Test System (RTS) for three different scenarios. MATLAB programming language was used to run the designated algorithm of MOEP. The performance of MOEP to solve the multi-objective ED problem was then compared with another method; the Multi-Objective Artificial Immune System (MOAIS). The experimental results show that MOEP dominates in all cases that have been tested, proving that MOEP is superior than MOAIS in providing high-quality solution to economic dispatch problem with multiple objectives in terms of cheap total generation cost and low total system loss. � 2019, World Academy of Research in Science and Engineering. All rights reserved. Final 2023-05-29T07:28:10Z 2023-05-29T07:28:10Z 2019 Article 10.30534/ijatcse/2019/4481.62019 2-s2.0-85078254747 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078254747&doi=10.30534%2fijatcse%2f2019%2f4481.62019&partnerID=40&md5=bc32e959b370163dd44275f7ea685d0e https://irepository.uniten.edu.my/handle/123456789/24873 8 1.6 Special Issue 44 296 302 All Open Access, Bronze World Academy of Research in Science and Engineering Scopus
institution Universiti Tenaga Nasional
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description Economic dispatch (ED) is an optimisation strategy to ensure power systems operate in an economic manner. This paper proposes a multi-objective optimisation method to minimise the total generation cost and total system loss simultaneously and find the best adjustment for this economic dispatch problem. This study focused on solving the multi-objective economic dispatch problem using a Heuristic Optimisation (HO) method, namely Multi-Objective Evolutionary Programming (MOEP). The Weighted Sum Method (WSM) is integrated with EP to find a trade-off solution between two objectives: total generation cost minimisation and total system loss minimisation. The practicable proposed method was tested on the IEEE 30-Bus Reliability Test System (RTS) for three different scenarios. MATLAB programming language was used to run the designated algorithm of MOEP. The performance of MOEP to solve the multi-objective ED problem was then compared with another method; the Multi-Objective Artificial Immune System (MOAIS). The experimental results show that MOEP dominates in all cases that have been tested, proving that MOEP is superior than MOAIS in providing high-quality solution to economic dispatch problem with multiple objectives in terms of cheap total generation cost and low total system loss. � 2019, World Academy of Research in Science and Engineering. All rights reserved.
author2 57212722015
author_facet 57212722015
Adnan N.A.
Mansor M.H.
Roslan N.
Musirin I.
Khader P.S.A.
Kamil K.
Jelani S.
Zuhdi A.W.M.
format Article
author Adnan N.A.
Mansor M.H.
Roslan N.
Musirin I.
Khader P.S.A.
Kamil K.
Jelani S.
Zuhdi A.W.M.
spellingShingle Adnan N.A.
Mansor M.H.
Roslan N.
Musirin I.
Khader P.S.A.
Kamil K.
Jelani S.
Zuhdi A.W.M.
Multi-objective evolutionary programming for solving economic dispatch problem
author_sort Adnan N.A.
title Multi-objective evolutionary programming for solving economic dispatch problem
title_short Multi-objective evolutionary programming for solving economic dispatch problem
title_full Multi-objective evolutionary programming for solving economic dispatch problem
title_fullStr Multi-objective evolutionary programming for solving economic dispatch problem
title_full_unstemmed Multi-objective evolutionary programming for solving economic dispatch problem
title_sort multi-objective evolutionary programming for solving economic dispatch problem
publisher World Academy of Research in Science and Engineering
publishDate 2023
_version_ 1806428031059755008
score 13.222552