Solution of Combined Economic Emission Dispatch Problem Using Improved and Chaotic Population-Based Polar Bear Optimization Algorithm
This paper proposes a novel improved polar bear optimization (IPBO) algorithm and employs it along with polar bear optimization (PBO) and chaotic population-based variants of polar bear optimization algorithm to solve combined economic emission dispatch (CEED) problem. PBO is a meta-heuristic techni...
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ftdoajarticles:oai:doaj.org/article:7ec4f80cbe2347329d0108e124d96fce 2023-05-15T15:12:01+02:00 Solution of Combined Economic Emission Dispatch Problem Using Improved and Chaotic Population-Based Polar Bear Optimization Algorithm Saqib Fayyaz Muhammad Kashif Sattar Muhammad Waseem M. Usman Ashraf Aftab Ahmad Hafiz Ashiq Hussain Khalid Alsubhi 2021-01-01T00:00:00Z https://doi.org/10.1109/ACCESS.2021.3072012 https://doaj.org/article/7ec4f80cbe2347329d0108e124d96fce EN eng IEEE https://ieeexplore.ieee.org/document/9398862/ https://doaj.org/toc/2169-3536 2169-3536 doi:10.1109/ACCESS.2021.3072012 https://doaj.org/article/7ec4f80cbe2347329d0108e124d96fce IEEE Access, Vol 9, Pp 56152-56167 (2021) Improved polar bear optimization (IPBO) economic emission dispatch (CEED) optimization cost emission Electrical engineering. Electronics. Nuclear engineering TK1-9971 article 2021 ftdoajarticles https://doi.org/10.1109/ACCESS.2021.3072012 2022-12-31T06:49:42Z This paper proposes a novel improved polar bear optimization (IPBO) algorithm and employs it along with polar bear optimization (PBO) and chaotic population-based variants of polar bear optimization algorithm to solve combined economic emission dispatch (CEED) problem. PBO is a meta-heuristic technique inspired by the hunting mechanisms of polar bears in harsh arctic regions based only on their sense of sight. Polar bears in nature exhibits hunting of prey not only on their sight but also on their keen sense of smell. Hence, a novel improved variant of PBO which enhances its operation by equipping it with tracking capabilities utilizing polar bears sense of smell has been proposed in this study. The validity of novel IPBO is tested through 5 benchmark functions and 140 units Korean ED problem. Furthermore, the impact of different population initialization methods is also observed on the capabilities of conventional PBO. The proposed chaotic population based PBO, improved PBO (IPBO) and PBO are employed to solve IEEE 3 unit and 6-unit CEED problem. CEED is a multi-objective power system optimization problem with conflicting objectives of cost and emission. The simulations performed undertake each objective individually as well as collectively. The results achieved by each technique are analyzed statistically through Wilcoxon rank sum test (WRST), probability density function and cumulative density function. Both the statistical and numerical analysis of results showcase the strength of each solution technique as well as their ability to improve cost and emissions in the solution of CEED problem. Article in Journal/Newspaper Arctic Directory of Open Access Journals: DOAJ Articles Arctic IEEE Access 9 56152 56167 |
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Directory of Open Access Journals: DOAJ Articles |
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language |
English |
topic |
Improved polar bear optimization (IPBO) economic emission dispatch (CEED) optimization cost emission Electrical engineering. Electronics. Nuclear engineering TK1-9971 |
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Improved polar bear optimization (IPBO) economic emission dispatch (CEED) optimization cost emission Electrical engineering. Electronics. Nuclear engineering TK1-9971 Saqib Fayyaz Muhammad Kashif Sattar Muhammad Waseem M. Usman Ashraf Aftab Ahmad Hafiz Ashiq Hussain Khalid Alsubhi Solution of Combined Economic Emission Dispatch Problem Using Improved and Chaotic Population-Based Polar Bear Optimization Algorithm |
topic_facet |
Improved polar bear optimization (IPBO) economic emission dispatch (CEED) optimization cost emission Electrical engineering. Electronics. Nuclear engineering TK1-9971 |
description |
This paper proposes a novel improved polar bear optimization (IPBO) algorithm and employs it along with polar bear optimization (PBO) and chaotic population-based variants of polar bear optimization algorithm to solve combined economic emission dispatch (CEED) problem. PBO is a meta-heuristic technique inspired by the hunting mechanisms of polar bears in harsh arctic regions based only on their sense of sight. Polar bears in nature exhibits hunting of prey not only on their sight but also on their keen sense of smell. Hence, a novel improved variant of PBO which enhances its operation by equipping it with tracking capabilities utilizing polar bears sense of smell has been proposed in this study. The validity of novel IPBO is tested through 5 benchmark functions and 140 units Korean ED problem. Furthermore, the impact of different population initialization methods is also observed on the capabilities of conventional PBO. The proposed chaotic population based PBO, improved PBO (IPBO) and PBO are employed to solve IEEE 3 unit and 6-unit CEED problem. CEED is a multi-objective power system optimization problem with conflicting objectives of cost and emission. The simulations performed undertake each objective individually as well as collectively. The results achieved by each technique are analyzed statistically through Wilcoxon rank sum test (WRST), probability density function and cumulative density function. Both the statistical and numerical analysis of results showcase the strength of each solution technique as well as their ability to improve cost and emissions in the solution of CEED problem. |
format |
Article in Journal/Newspaper |
author |
Saqib Fayyaz Muhammad Kashif Sattar Muhammad Waseem M. Usman Ashraf Aftab Ahmad Hafiz Ashiq Hussain Khalid Alsubhi |
author_facet |
Saqib Fayyaz Muhammad Kashif Sattar Muhammad Waseem M. Usman Ashraf Aftab Ahmad Hafiz Ashiq Hussain Khalid Alsubhi |
author_sort |
Saqib Fayyaz |
title |
Solution of Combined Economic Emission Dispatch Problem Using Improved and Chaotic Population-Based Polar Bear Optimization Algorithm |
title_short |
Solution of Combined Economic Emission Dispatch Problem Using Improved and Chaotic Population-Based Polar Bear Optimization Algorithm |
title_full |
Solution of Combined Economic Emission Dispatch Problem Using Improved and Chaotic Population-Based Polar Bear Optimization Algorithm |
title_fullStr |
Solution of Combined Economic Emission Dispatch Problem Using Improved and Chaotic Population-Based Polar Bear Optimization Algorithm |
title_full_unstemmed |
Solution of Combined Economic Emission Dispatch Problem Using Improved and Chaotic Population-Based Polar Bear Optimization Algorithm |
title_sort |
solution of combined economic emission dispatch problem using improved and chaotic population-based polar bear optimization algorithm |
publisher |
IEEE |
publishDate |
2021 |
url |
https://doi.org/10.1109/ACCESS.2021.3072012 https://doaj.org/article/7ec4f80cbe2347329d0108e124d96fce |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic |
genre_facet |
Arctic |
op_source |
IEEE Access, Vol 9, Pp 56152-56167 (2021) |
op_relation |
https://ieeexplore.ieee.org/document/9398862/ https://doaj.org/toc/2169-3536 2169-3536 doi:10.1109/ACCESS.2021.3072012 https://doaj.org/article/7ec4f80cbe2347329d0108e124d96fce |
op_doi |
https://doi.org/10.1109/ACCESS.2021.3072012 |
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IEEE Access |
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9 |
container_start_page |
56152 |
op_container_end_page |
56167 |
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