Particle swarm optimization with exponentially varying inertia weight factor for solving multi- area economic dispatch problem

C. Rani; E. Petkov; K. Busawon; M. Farrag

doi:10.1109/EFEA.2014.7059938

Particle swarm optimization with exponentially varying inertia weight factor for solving multi- area economic dispatch problem

C. Rani, E. Petkov, K. Busawon, M. Farrag

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This paper aimed at exploring the performance of Particle Swarm Optimisation with Exponentially Varying Inertia Weight Factor (PSO-EVIWF) for solving Multi-Area Economic Dispatch (MAED) problem with tie line constraints considering valve-point loading in each area. The effectiveness of the proposed algorithm has been verified on 4 interconnected areas with 16 generators standard test system. The paper presents the search capability and convergence behavior of the proposed method. Simulation results show that the PSO-EVIWF achieved quality solutions and smooth convergence characteristics and it is an alternative method for solving MAED problem.

Original language	English
Title of host publication	3rd International Symposium on Environmental Friendly Energies and Applications (EFEA)
Publisher	IEEE
Number of pages	6
ISBN (Electronic)	9781479975174
DOIs	https://doi.org/10.1109/EFEA.2014.7059938
Publication status	Published - 16 Mar 2015

Keywords

economic dispatch
multi- area economic dispatch
particle swarm optimisation
exponentially varying inertia weight factor

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10.1109/EFEA.2014.7059938

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Mohamed Emad Farrag
- mfa1@gcu.ac.uk
- Electrical Power Engineering - Professor
Person

Cite this

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title = "Particle swarm optimization with exponentially varying inertia weight factor for solving multi- area economic dispatch problem",

abstract = "This paper aimed at exploring the performance of Particle Swarm Optimisation with Exponentially Varying Inertia Weight Factor (PSO-EVIWF) for solving Multi-Area Economic Dispatch (MAED) problem with tie line constraints considering valve-point loading in each area. The effectiveness of the proposed algorithm has been verified on 4 interconnected areas with 16 generators standard test system. The paper presents the search capability and convergence behavior of the proposed method. Simulation results show that the PSO-EVIWF achieved quality solutions and smooth convergence characteristics and it is an alternative method for solving MAED problem.",

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author = "C. Rani and E. Petkov and K. Busawon and M. Farrag",

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T1 - Particle swarm optimization with exponentially varying inertia weight factor for solving multi- area economic dispatch problem

AU - Rani, C.

AU - Petkov, E.

AU - Busawon, K.

AU - Farrag , M.

PY - 2015/3/16

Y1 - 2015/3/16

N2 - This paper aimed at exploring the performance of Particle Swarm Optimisation with Exponentially Varying Inertia Weight Factor (PSO-EVIWF) for solving Multi-Area Economic Dispatch (MAED) problem with tie line constraints considering valve-point loading in each area. The effectiveness of the proposed algorithm has been verified on 4 interconnected areas with 16 generators standard test system. The paper presents the search capability and convergence behavior of the proposed method. Simulation results show that the PSO-EVIWF achieved quality solutions and smooth convergence characteristics and it is an alternative method for solving MAED problem.

AB - This paper aimed at exploring the performance of Particle Swarm Optimisation with Exponentially Varying Inertia Weight Factor (PSO-EVIWF) for solving Multi-Area Economic Dispatch (MAED) problem with tie line constraints considering valve-point loading in each area. The effectiveness of the proposed algorithm has been verified on 4 interconnected areas with 16 generators standard test system. The paper presents the search capability and convergence behavior of the proposed method. Simulation results show that the PSO-EVIWF achieved quality solutions and smooth convergence characteristics and it is an alternative method for solving MAED problem.

KW - economic dispatch

KW - multi- area economic dispatch

KW - particle swarm optimisation

KW - exponentially varying inertia weight factor

U2 - 10.1109/EFEA.2014.7059938

DO - 10.1109/EFEA.2014.7059938

M3 - Conference contribution

BT - 3rd International Symposium on Environmental Friendly Energies and Applications (EFEA)

PB - IEEE

ER -

Particle swarm optimization with exponentially varying inertia weight factor for solving multi- area economic dispatch problem

Abstract

Keywords

Documents and Links

Mohamed Emad Farrag

Cite this