Solving economic dispatch problem using particle swarm optimization by an evolutionary technique for initializing particles

One of the important optimization problems regarding power system issues is to determine and provide an economic condition for generation units based on the generation and transmission constraints, which is called Economic Dispatch (ED). The nonlinearity of the present problems makes conventional ma...

Full description

Saved in:
Bibliographic Details
Main Authors: Rahmani, R., Othman, Mohd. Fauzi, Khalid, Noor Khafifah
Format: Article
Published: 2012
Subjects:
Online Access:http://eprints.utm.my/id/eprint/47520/
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Universiti Teknologi Malaysia
id my.utm.47520
record_format eprints
spelling my.utm.475202019-04-25T01:22:04Z http://eprints.utm.my/id/eprint/47520/ Solving economic dispatch problem using particle swarm optimization by an evolutionary technique for initializing particles Rahmani, R. Othman, Mohd. Fauzi Khalid, Noor Khafifah T Technology One of the important optimization problems regarding power system issues is to determine and provide an economic condition for generation units based on the generation and transmission constraints, which is called Economic Dispatch (ED). The nonlinearity of the present problems makes conventional mathematic methods unable to propose a fast and robust solution, especially when the power system contains high number of generation units. In the present paper, an evolutionary modified Particle Swarm Optimization (PSO) is used to find fast and efficient solutions for different power systems with different generation unit numbers. The proposed algorithm is capable of solving the constraint ED problem, determining the exact output power of all the generation units. In such a way, proposed algorithm minimizes the total cost function of the generation units. To model the fuel costs of generation units, a piecewise quadratic function is used and B coefficient method is used to represent the transmission losses. The acceleration coefficients are adjusted intelligently and a novel algorithm is proposed for allocating the initial power values to the generation units. The feasibility of the proposed PSO based algorithm is demonstrated for four power system test cases consisting of 3, 6, 15, and 40 generation units. The obtained results are compared to existing results based on previous PSO implementing and Genetic Algorithm (GA). The results reveal that the proposed algorithm is capable of reaching a higher quality solution including mathematical simplicity, fast convergence, and robustness to cope with the non-linearities of economic load dispatch problem. 2012 Article PeerReviewed Rahmani, R. and Othman, Mohd. Fauzi and Khalid, Noor Khafifah (2012) Solving economic dispatch problem using particle swarm optimization by an evolutionary technique for initializing particles. Journal of Theoretical and Applied Information Technology, 46 (2). pp. 526-536. ISSN 1992-8645
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
topic T Technology
spellingShingle T Technology
Rahmani, R.
Othman, Mohd. Fauzi
Khalid, Noor Khafifah
Solving economic dispatch problem using particle swarm optimization by an evolutionary technique for initializing particles
description One of the important optimization problems regarding power system issues is to determine and provide an economic condition for generation units based on the generation and transmission constraints, which is called Economic Dispatch (ED). The nonlinearity of the present problems makes conventional mathematic methods unable to propose a fast and robust solution, especially when the power system contains high number of generation units. In the present paper, an evolutionary modified Particle Swarm Optimization (PSO) is used to find fast and efficient solutions for different power systems with different generation unit numbers. The proposed algorithm is capable of solving the constraint ED problem, determining the exact output power of all the generation units. In such a way, proposed algorithm minimizes the total cost function of the generation units. To model the fuel costs of generation units, a piecewise quadratic function is used and B coefficient method is used to represent the transmission losses. The acceleration coefficients are adjusted intelligently and a novel algorithm is proposed for allocating the initial power values to the generation units. The feasibility of the proposed PSO based algorithm is demonstrated for four power system test cases consisting of 3, 6, 15, and 40 generation units. The obtained results are compared to existing results based on previous PSO implementing and Genetic Algorithm (GA). The results reveal that the proposed algorithm is capable of reaching a higher quality solution including mathematical simplicity, fast convergence, and robustness to cope with the non-linearities of economic load dispatch problem.
format Article
author Rahmani, R.
Othman, Mohd. Fauzi
Khalid, Noor Khafifah
author_facet Rahmani, R.
Othman, Mohd. Fauzi
Khalid, Noor Khafifah
author_sort Rahmani, R.
title Solving economic dispatch problem using particle swarm optimization by an evolutionary technique for initializing particles
title_short Solving economic dispatch problem using particle swarm optimization by an evolutionary technique for initializing particles
title_full Solving economic dispatch problem using particle swarm optimization by an evolutionary technique for initializing particles
title_fullStr Solving economic dispatch problem using particle swarm optimization by an evolutionary technique for initializing particles
title_full_unstemmed Solving economic dispatch problem using particle swarm optimization by an evolutionary technique for initializing particles
title_sort solving economic dispatch problem using particle swarm optimization by an evolutionary technique for initializing particles
publishDate 2012
url http://eprints.utm.my/id/eprint/47520/
_version_ 1643652335317024768