Sensitivity analysis of GA parameters for ECED problem

To meet the requirement of the regulations and to reduce the pollution to the targeted level, minimization of emission level has been added into the dispatch strategies of generators by formulating emission constrained economic dispatch (ECED). Besides the conventional method by using the Lagrange M...

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Main Authors: Kamil K., Razali N.M.M., Teh Y.Y.
Other Authors: 57195622807
Format: Conference paper
Published: 2023
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spelling my.uniten.dspace-294012023-12-28T12:12:55Z Sensitivity analysis of GA parameters for ECED problem Kamil K. Razali N.M.M. Teh Y.Y. 57195622807 36440450000 55786392300 Genetic algorithms Lagrange multipliers Particle swarm optimization (PSO) Scheduling Conventional methods Differential Evolution Economic Dispatch Economic dispatch problems Emission constrained economic dispatches Evolutionary computation techniques Particle swarm optimisation Stochastic search techniques Sensitivity analysis To meet the requirement of the regulations and to reduce the pollution to the targeted level, minimization of emission level has been added into the dispatch strategies of generators by formulating emission constrained economic dispatch (ECED). Besides the conventional method by using the Lagrange Multiplier several evolutionary computation techniques such as Genetic Algorithm, Particle Swarm Optimisation, Ant Colony and Differential Evolution have been gaining popularity in solving general economic dispatch problems due to their desirable characteristics such as non-gradient dependent and ability to search for global optima. The effectiveness of these stochastic search techniques however is heavily dependent on the genetic operators and their parameters. The paper presents the study on sensitivity analysis of the parameters of Genetic Algorithm (GA) for the ECED problem. The results discuss the range of parameters suitable to be employed for the optimization and compare the difference between conventional economic dispatch and the ECED solutions. � 2013 IEEE. Final 2023-12-28T04:12:54Z 2023-12-28T04:12:54Z 2013 Conference paper 10.1109/PEOCO.2013.6564553 2-s2.0-84882779766 https://www.scopus.com/inward/record.uri?eid=2-s2.0-84882779766&doi=10.1109%2fPEOCO.2013.6564553&partnerID=40&md5=de28129bf514277f564f71d97f6e3de5 https://irepository.uniten.edu.my/handle/123456789/29401 6564553 256 260 Scopus
institution Universiti Tenaga Nasional
building UNITEN Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Tenaga Nasional
content_source UNITEN Institutional Repository
url_provider http://dspace.uniten.edu.my/
topic Genetic algorithms
Lagrange multipliers
Particle swarm optimization (PSO)
Scheduling
Conventional methods
Differential Evolution
Economic Dispatch
Economic dispatch problems
Emission constrained economic dispatches
Evolutionary computation techniques
Particle swarm optimisation
Stochastic search techniques
Sensitivity analysis
spellingShingle Genetic algorithms
Lagrange multipliers
Particle swarm optimization (PSO)
Scheduling
Conventional methods
Differential Evolution
Economic Dispatch
Economic dispatch problems
Emission constrained economic dispatches
Evolutionary computation techniques
Particle swarm optimisation
Stochastic search techniques
Sensitivity analysis
Kamil K.
Razali N.M.M.
Teh Y.Y.
Sensitivity analysis of GA parameters for ECED problem
description To meet the requirement of the regulations and to reduce the pollution to the targeted level, minimization of emission level has been added into the dispatch strategies of generators by formulating emission constrained economic dispatch (ECED). Besides the conventional method by using the Lagrange Multiplier several evolutionary computation techniques such as Genetic Algorithm, Particle Swarm Optimisation, Ant Colony and Differential Evolution have been gaining popularity in solving general economic dispatch problems due to their desirable characteristics such as non-gradient dependent and ability to search for global optima. The effectiveness of these stochastic search techniques however is heavily dependent on the genetic operators and their parameters. The paper presents the study on sensitivity analysis of the parameters of Genetic Algorithm (GA) for the ECED problem. The results discuss the range of parameters suitable to be employed for the optimization and compare the difference between conventional economic dispatch and the ECED solutions. � 2013 IEEE.
author2 57195622807
author_facet 57195622807
Kamil K.
Razali N.M.M.
Teh Y.Y.
format Conference paper
author Kamil K.
Razali N.M.M.
Teh Y.Y.
author_sort Kamil K.
title Sensitivity analysis of GA parameters for ECED problem
title_short Sensitivity analysis of GA parameters for ECED problem
title_full Sensitivity analysis of GA parameters for ECED problem
title_fullStr Sensitivity analysis of GA parameters for ECED problem
title_full_unstemmed Sensitivity analysis of GA parameters for ECED problem
title_sort sensitivity analysis of ga parameters for eced problem
publishDate 2023
_version_ 1806427572746059776
score 13.222552