Multi area economic dispatch using chaotic self-adaptive particle swarm approach

Rani Chinnappa Naidu; Emil Petkov; Krishna Busawon

Multi area economic dispatch using chaotic self-adaptive particle swarm approach

Rani Chinnappa Naidu, Emil Petkov, Krishna Busawon

Research output: Contribution to conference › Paper › peer-review

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 area with 16 generators standard test system. The paper presents the search capability and convergence behaviour 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
Publication status	Published - 20 Nov 2014
Event	3rd International Symposium On Environment Friendly Energies And Applications (EFEA 2014) - Paris Duration: 20 Nov 2014 → … http://soe.northumbria.ac.uk/efea2014/

Conference

Conference	3rd International Symposium On Environment Friendly Energies And Applications (EFEA 2014)
Period	20/11/14 → …
Internet address	http://soe.northumbria.ac.uk/efea2014/

Cite this

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title = "Multi area economic dispatch using chaotic self-adaptive particle swarm approach",

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 area with 16 generators standard test system. The paper presents the search capability and convergence behaviour 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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T1 - Multi area economic dispatch using chaotic self-adaptive particle swarm approach

AU - Chinnappa Naidu, Rani

AU - Petkov, Emil

AU - Busawon, Krishna

PY - 2014/11/20

Y1 - 2014/11/20

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 area with 16 generators standard test system. The paper presents the search capability and convergence behaviour 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 area with 16 generators standard test system. The paper presents the search capability and convergence behaviour 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.

M3 - Paper

T2 - 3rd International Symposium On Environment Friendly Energies And Applications (EFEA 2014)

Y2 - 20 November 2014

ER -

Multi area economic dispatch using chaotic self-adaptive particle swarm approach

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