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Improved Fitness-Dependent Optimizer for Solving Economic Load Dispatch Problem

Economic load dispatch depicts a fundamental role in the operation of power systems, as it decreases the environmental load, minimizes the operating cost, and preserves energy resources. The optimal solution to economic load dispatch problems and various constraints can be obtained by evolving sever...

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Autores principales: Tahir, Barzan Hussein, Rashid, Tarik A., Rauf, Hafiz Tayyab, Bacanin, Nebojsa, Chhabra, Amit, Vimal, S., Yaseen, Zaher Mundher
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9293509/
https://www.ncbi.nlm.nih.gov/pubmed/35860638
http://dx.doi.org/10.1155/2022/7055910
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author Tahir, Barzan Hussein
Rashid, Tarik A.
Rauf, Hafiz Tayyab
Bacanin, Nebojsa
Chhabra, Amit
Vimal, S.
Yaseen, Zaher Mundher
author_facet Tahir, Barzan Hussein
Rashid, Tarik A.
Rauf, Hafiz Tayyab
Bacanin, Nebojsa
Chhabra, Amit
Vimal, S.
Yaseen, Zaher Mundher
author_sort Tahir, Barzan Hussein
collection PubMed
description Economic load dispatch depicts a fundamental role in the operation of power systems, as it decreases the environmental load, minimizes the operating cost, and preserves energy resources. The optimal solution to economic load dispatch problems and various constraints can be obtained by evolving several evolutionary and swarm-based algorithms. The major drawback to swarm-based algorithms is premature convergence towards an optimal solution. Fitness-dependent optimizer is a novel optimization algorithm stimulated by the decision-making and reproductive process of bee swarming. Fitness-dependent optimizer (FDO) examines the search spaces based on the searching approach of particle swarm optimization. To calculate the pace, the fitness function is utilized to generate weights that direct the search agents in the phases of exploitation and exploration. In this research, the authors have used a fitness-dependent optimizer to solve the economic load dispatch problem by reducing fuel cost, emission allocation, and transmission loss. Moreover, the authors have enhanced a novel variant of the fitness-dependent optimizer, which incorporates novel population initialization techniques and dynamically employed sine maps to select the weight factor for the fitness-dependent optimizer. The enhanced population initialization approach incorporates a quasi-random Sabol sequence to generate the initial solution in the multidimensional search space. A standard 24-unit system is employed for experimental evaluation with different power demands. The empirical results obtained using the enhanced variant of the fitness-dependent optimizer demonstrate superior performance in terms of low transmission loss, low fuel cost, and low emission allocation compared to the conventional fitness-dependent optimizer. The experimental study obtained 7.94E−12, the lowest transmission loss using the enhanced fitness-dependent optimizer. Correspondingly, various standard estimations are used to prove the stability of the fitness-dependent optimizer in phases of exploitation and exploration.
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spelling pubmed-92935092022-07-19 Improved Fitness-Dependent Optimizer for Solving Economic Load Dispatch Problem Tahir, Barzan Hussein Rashid, Tarik A. Rauf, Hafiz Tayyab Bacanin, Nebojsa Chhabra, Amit Vimal, S. Yaseen, Zaher Mundher Comput Intell Neurosci Review Article Economic load dispatch depicts a fundamental role in the operation of power systems, as it decreases the environmental load, minimizes the operating cost, and preserves energy resources. The optimal solution to economic load dispatch problems and various constraints can be obtained by evolving several evolutionary and swarm-based algorithms. The major drawback to swarm-based algorithms is premature convergence towards an optimal solution. Fitness-dependent optimizer is a novel optimization algorithm stimulated by the decision-making and reproductive process of bee swarming. Fitness-dependent optimizer (FDO) examines the search spaces based on the searching approach of particle swarm optimization. To calculate the pace, the fitness function is utilized to generate weights that direct the search agents in the phases of exploitation and exploration. In this research, the authors have used a fitness-dependent optimizer to solve the economic load dispatch problem by reducing fuel cost, emission allocation, and transmission loss. Moreover, the authors have enhanced a novel variant of the fitness-dependent optimizer, which incorporates novel population initialization techniques and dynamically employed sine maps to select the weight factor for the fitness-dependent optimizer. The enhanced population initialization approach incorporates a quasi-random Sabol sequence to generate the initial solution in the multidimensional search space. A standard 24-unit system is employed for experimental evaluation with different power demands. The empirical results obtained using the enhanced variant of the fitness-dependent optimizer demonstrate superior performance in terms of low transmission loss, low fuel cost, and low emission allocation compared to the conventional fitness-dependent optimizer. The experimental study obtained 7.94E−12, the lowest transmission loss using the enhanced fitness-dependent optimizer. Correspondingly, various standard estimations are used to prove the stability of the fitness-dependent optimizer in phases of exploitation and exploration. Hindawi 2022-07-11 /pmc/articles/PMC9293509/ /pubmed/35860638 http://dx.doi.org/10.1155/2022/7055910 Text en Copyright © 2022 Barzan Hussein Tahir et al. https://creativecommons.org/licenses/by/4.0/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 Review Article
Tahir, Barzan Hussein
Rashid, Tarik A.
Rauf, Hafiz Tayyab
Bacanin, Nebojsa
Chhabra, Amit
Vimal, S.
Yaseen, Zaher Mundher
Improved Fitness-Dependent Optimizer for Solving Economic Load Dispatch Problem
title Improved Fitness-Dependent Optimizer for Solving Economic Load Dispatch Problem
title_full Improved Fitness-Dependent Optimizer for Solving Economic Load Dispatch Problem
title_fullStr Improved Fitness-Dependent Optimizer for Solving Economic Load Dispatch Problem
title_full_unstemmed Improved Fitness-Dependent Optimizer for Solving Economic Load Dispatch Problem
title_short Improved Fitness-Dependent Optimizer for Solving Economic Load Dispatch Problem
title_sort improved fitness-dependent optimizer for solving economic load dispatch problem
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9293509/
https://www.ncbi.nlm.nih.gov/pubmed/35860638
http://dx.doi.org/10.1155/2022/7055910
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