Particle swarm optimization with Exponentially Varying Inertia Weight Factor for solving Multi-Area Economic Dispatch problem

Rani Chinnappa Naidu; Emil Petkov; Krishna Busawon; Mohamed Farrag

doi:10.1109/EFEA.2014.7059938

Particle swarm optimization with Exponentially Varying Inertia Weight Factor for solving Multi-Area Economic Dispatch problem

Rani Chinnappa Naidu, Emil Petkov, Krishna Busawon, Mohamed Farrag

Research output: Contribution to conference › Paper

4 Citations (Scopus)

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
DOIs	https://doi.org/10.1109/EFEA.2014.7059938
Publication status	Published - Nov 2014
Event	EFEA 2014: 3rd International Symposium on Environmental Friendly Energies and Applications - Paris, France Duration: 1 Nov 2014 → …

Conference

Conference	EFEA 2014: 3rd International Symposium on Environmental Friendly Energies and Applications
Period	1/11/14 → …

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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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.",

keywords = "Economic dispatch, Multi area economic dispatch, particle swarm optimisation, exponentially varying inertia weight factor",

author = "{Chinnappa Naidu}, Rani and Emil Petkov and Krishna Busawon and Mohamed Farrag",

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AU - Chinnappa Naidu, Rani

AU - Petkov, Emil

AU - Busawon, Krishna

AU - Farrag, Mohamed

PY - 2014/11

Y1 - 2014/11

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

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DO - 10.1109/EFEA.2014.7059938

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Y2 - 1 November 2014

ER -

Particle swarm optimization with Exponentially Varying Inertia Weight Factor for solving Multi-Area Economic Dispatch problem

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