Dynamic economic emission dispatch using whale optimization algorithm for multi-objective function

Introduction. Dynamic Economic Emission Dispatch is the extended version of the traditional economic emission dispatch problem in which ramp rate is taken into account for the limit of generators in a power network. Purpose. Dynamic Economic Emission Dispatch considered the treats of economy and emi...

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Autores principales:	M. F. Mehdi, A. Ahmad, S. S. Ul Haq, M. Saqib, M. F. Ullah
Formato:	article
Lenguaje:	EN RU UK
Publicado:	National Technical University "Kharkiv Polytechnic Institute" 2021
Materias:	whale optimization algorithm dynamic economic emission dispatch ramp rate multi-objective problem economic emission Electrical engineering. Electronics. Nuclear engineering TK1-9971
Acceso en línea:	https://doaj.org/article/28dfc523256843a8be3ab18bd0e593c0
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spelling	oai:doaj.org-article:28dfc523256843a8be3ab18bd0e593c02021-12-02T15:28:26ZDynamic economic emission dispatch using whale optimization algorithm for multi-objective function10.20998/2074-272X.2021.2.092074-272X2309-3404https://doaj.org/article/28dfc523256843a8be3ab18bd0e593c02021-04-01T00:00:00Zhttp://eie.khpi.edu.ua/article/view/228893/227906https://doaj.org/toc/2074-272Xhttps://doaj.org/toc/2309-3404Introduction. Dynamic Economic Emission Dispatch is the extended version of the traditional economic emission dispatch problem in which ramp rate is taken into account for the limit of generators in a power network. Purpose. Dynamic Economic Emission Dispatch considered the treats of economy and emissions as competitive targets for optimal dispatch problems, and to reach a solution it requires some conflict resolution. Novelty. The decision-making method to solve the Dynamic Economic Emission Dispatch problem has a goal for each objective function, for this purpose, the multi-objective problem is transformed into single goal optimization by using the weighted sum method and then control/solve by Whale Optimization Algorithm. Methodology. This paper presents a newly developed metaheuristic technique based on Whale Optimization Algorithm to solve the Dynamic Economic Emission Dispatch problem. The main inspiration for this optimization technique is the fact that metaheuristic algorithms are becoming popular day by day because of their simplicity, no gradient information requirement, easily bypass local optima, and can be used for a variety of other problems. This algorithm includes all possible factors that will yield the minimum cost and emissions of a Dynamic Economic Emission Dispatch problem for the efficient operation of generators in a power network. The proposed approach performs well to perform in diverse problem and converge the solution to near best optimal solution. Results. The proposed strategy is validated by simulating on MATLAB® for 5 IEEE standard test system. Numerical results show the capabilities of the proposed algorithm to establish an optimal solution of the Dynamic Economic Emission Dispatch problem in a several runs. The proposed algorithm shows good performance over the recently proposed algorithms such as Multi-Objective Neural Network trained with Differential Evolution, Particle swarm optimization, evolutionary programming, simulated annealing, Pattern search, multi-objective differential evolution, and multi-objective hybrid differential evolution with simulated annealing technique.M. F. MehdiA. AhmadS. S. Ul HaqM. SaqibM. F. UllahNational Technical University "Kharkiv Polytechnic Institute"articlewhale optimization algorithmdynamic economic emission dispatchramp ratemulti-objective problemeconomic emissionElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENRUUKElectrical engineering & Electromechanics, Iss 2, Pp 64-69 (2021)
institution	DOAJ
collection	DOAJ
language	EN RU UK
topic	whale optimization algorithm dynamic economic emission dispatch ramp rate multi-objective problem economic emission Electrical engineering. Electronics. Nuclear engineering TK1-9971
spellingShingle	whale optimization algorithm dynamic economic emission dispatch ramp rate multi-objective problem economic emission Electrical engineering. Electronics. Nuclear engineering TK1-9971 M. F. Mehdi A. Ahmad S. S. Ul Haq M. Saqib M. F. Ullah Dynamic economic emission dispatch using whale optimization algorithm for multi-objective function
description	Introduction. Dynamic Economic Emission Dispatch is the extended version of the traditional economic emission dispatch problem in which ramp rate is taken into account for the limit of generators in a power network. Purpose. Dynamic Economic Emission Dispatch considered the treats of economy and emissions as competitive targets for optimal dispatch problems, and to reach a solution it requires some conflict resolution. Novelty. The decision-making method to solve the Dynamic Economic Emission Dispatch problem has a goal for each objective function, for this purpose, the multi-objective problem is transformed into single goal optimization by using the weighted sum method and then control/solve by Whale Optimization Algorithm. Methodology. This paper presents a newly developed metaheuristic technique based on Whale Optimization Algorithm to solve the Dynamic Economic Emission Dispatch problem. The main inspiration for this optimization technique is the fact that metaheuristic algorithms are becoming popular day by day because of their simplicity, no gradient information requirement, easily bypass local optima, and can be used for a variety of other problems. This algorithm includes all possible factors that will yield the minimum cost and emissions of a Dynamic Economic Emission Dispatch problem for the efficient operation of generators in a power network. The proposed approach performs well to perform in diverse problem and converge the solution to near best optimal solution. Results. The proposed strategy is validated by simulating on MATLAB® for 5 IEEE standard test system. Numerical results show the capabilities of the proposed algorithm to establish an optimal solution of the Dynamic Economic Emission Dispatch problem in a several runs. The proposed algorithm shows good performance over the recently proposed algorithms such as Multi-Objective Neural Network trained with Differential Evolution, Particle swarm optimization, evolutionary programming, simulated annealing, Pattern search, multi-objective differential evolution, and multi-objective hybrid differential evolution with simulated annealing technique.
format	article
author	M. F. Mehdi A. Ahmad S. S. Ul Haq M. Saqib M. F. Ullah
author_facet	M. F. Mehdi A. Ahmad S. S. Ul Haq M. Saqib M. F. Ullah
author_sort	M. F. Mehdi
title	Dynamic economic emission dispatch using whale optimization algorithm for multi-objective function
title_short	Dynamic economic emission dispatch using whale optimization algorithm for multi-objective function
title_full	Dynamic economic emission dispatch using whale optimization algorithm for multi-objective function
title_fullStr	Dynamic economic emission dispatch using whale optimization algorithm for multi-objective function
title_full_unstemmed	Dynamic economic emission dispatch using whale optimization algorithm for multi-objective function
title_sort	dynamic economic emission dispatch using whale optimization algorithm for multi-objective function
publisher	National Technical University "Kharkiv Polytechnic Institute"
publishDate	2021
url	https://doaj.org/article/28dfc523256843a8be3ab18bd0e593c0
work_keys_str_mv	AT mfmehdi dynamiceconomicemissiondispatchusingwhaleoptimizationalgorithmformultiobjectivefunction AT aahmad dynamiceconomicemissiondispatchusingwhaleoptimizationalgorithmformultiobjectivefunction AT ssulhaq dynamiceconomicemissiondispatchusingwhaleoptimizationalgorithmformultiobjectivefunction AT msaqib dynamiceconomicemissiondispatchusingwhaleoptimizationalgorithmformultiobjectivefunction AT mfullah dynamiceconomicemissiondispatchusingwhaleoptimizationalgorithmformultiobjectivefunction
_version_	1718387192237129728

Dynamic economic emission dispatch using whale optimization algorithm for multi-objective function

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