Solving unit commitment problem using hybrid particle swarm optimization
This paper presents a Hybrid Particle Swarm Optimization (HPSO) to solve the Unit Commitment (UC) problem. Problem formulation of the unit commitment takes into consideration the minimum up and down time constraints, start up cost and spinning reserve, which is defined as the minimization of the tot...
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my.um.eprints.51962013-03-21T02:01:56Z http://eprints.um.edu.my/5196/ Solving unit commitment problem using hybrid particle swarm optimization Ting, T.O. Rao, M.V.C. Loo, C.K. Ngu, S.S. T Technology (General) This paper presents a Hybrid Particle Swarm Optimization (HPSO) to solve the Unit Commitment (UC) problem. Problem formulation of the unit commitment takes into consideration the minimum up and down time constraints, start up cost and spinning reserve, which is defined as the minimization of the total objective function while satisfying all the associated constraints. Problem formulation, representation and the simulation results for a 10 generator-scheduling problem are presented. Results shown are acceptable at this early stage. 2003 Article PeerReviewed Ting, T.O. and Rao, M.V.C. and Loo, C.K. and Ngu, S.S. (2003) Solving unit commitment problem using hybrid particle swarm optimization. Journal of Heuristics, 9 (6). pp. 507-520. ISSN 1381-1231 http://download.springer.com/static/pdf/769/art%253A10.1023%252FB%253AHEUR.0000012449.84567.1a.pdf?auth66=1352708429_418c3f367323dc9a4a18b7004c421aed&ext=.pdf |
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T Technology (General) Ting, T.O. Rao, M.V.C. Loo, C.K. Ngu, S.S. Solving unit commitment problem using hybrid particle swarm optimization |
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This paper presents a Hybrid Particle Swarm Optimization (HPSO) to solve the Unit Commitment (UC) problem. Problem formulation of the unit commitment takes into consideration the minimum up and down time constraints, start up cost and spinning reserve, which is defined as the minimization of the total objective function while satisfying all the associated constraints. Problem formulation, representation and the simulation results for a 10 generator-scheduling problem are presented. Results shown are acceptable at this early stage. |
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Article |
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Ting, T.O. Rao, M.V.C. Loo, C.K. Ngu, S.S. |
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Ting, T.O. Rao, M.V.C. Loo, C.K. Ngu, S.S. |
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Ting, T.O. |
title |
Solving unit commitment problem using hybrid particle swarm optimization |
title_short |
Solving unit commitment problem using hybrid particle swarm optimization |
title_full |
Solving unit commitment problem using hybrid particle swarm optimization |
title_fullStr |
Solving unit commitment problem using hybrid particle swarm optimization |
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Solving unit commitment problem using hybrid particle swarm optimization |
title_sort |
solving unit commitment problem using hybrid particle swarm optimization |
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2003 |
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http://eprints.um.edu.my/5196/ http://download.springer.com/static/pdf/769/art%253A10.1023%252FB%253AHEUR.0000012449.84567.1a.pdf?auth66=1352708429_418c3f367323dc9a4a18b7004c421aed&ext=.pdf |
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