Chaotic adaptive particle swarm optimisation using logistics and gauss map for solving cubic cost economic dispatch problem

C Rani; E Petkov; K Busawon; M Farrag

doi:10.1109/EFEA.2014.7059939

Chaotic adaptive particle swarm optimisation using logistics and gauss map for solving cubic cost economic dispatch problem

C Rani, E Petkov, K Busawon, M Farrag

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

3 Citations (Scopus)

Abstract

This paper proposes Chaotic Adaptive Particle Swarm Optimisation (CAPSO) algorithm to solve Cubic Cost Economic Dispatch (CCED) problem. A Chaotic Local Search operator (CLS) is introduced in the proposed algorithm to avoid premature convergence. The basic strategy of the proposed algorithm is combining PSO with Adaptive Inertia Weight Factor (AIWF) and CLS, in which PSO with AIWF is applied to perform global exploration and CLS is used to perform exploitation to find the optimal solution. Logistics and Gauss map technique is used in performing CLS and the results are compared. The applicability and high feasibility of the proposed method is validated on a standard 5-generator test system. The simulation results confirm that this algorithm is capable of giving higher quality solutions with fast convergence characteristics.

Original language	English
Title of host publication	3rd International Symposium on Environment Friendly Energies and Applications, EFEA 2014
Publisher	IEEE
Number of pages	5
ISBN (Electronic)	9781479975174
ISBN (Print)	9781479975181
DOIs	https://doi.org/10.1109/EFEA.2014.7059939
Publication status	Published - 16 Mar 2015

Keywords

adaptive particle swarm
optimisation
economic dispatch
cubic cost economic dispatch
chaotic adaptive particle swarm optimisation
adaptive inertia weight factor
Economic dispatch
chaotic local search

Documents and Links

10.1109/EFEA.2014.7059939

http://soe.northumbria.ac.uk/efea2014/documents/ProgramEFEA%202014.pdf

3 Citations
1 Article

An improved optimization technique for estimation of solar photovoltaic parameters
Derick, M., Rani, C., Rajesh, M., Farrag, M. E., Wang, Y. & Busawon, K., 15 Nov 2017, In: Solar Energy. 157, p. 116–124 9 p.
Research output: Contribution to journal › Article › peer-review

Open Access
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98 Citations (Scopus)

261 Downloads (Pure)

Cite this

@inproceedings{9ee191c6f70b4c9bb60a6a61bc639ce7,

title = "Chaotic adaptive particle swarm optimisation using logistics and gauss map for solving cubic cost economic dispatch problem",

abstract = "This paper proposes Chaotic Adaptive Particle Swarm Optimisation (CAPSO) algorithm to solve Cubic Cost Economic Dispatch (CCED) problem. A Chaotic Local Search operator (CLS) is introduced in the proposed algorithm to avoid premature convergence. The basic strategy of the proposed algorithm is combining PSO with Adaptive Inertia Weight Factor (AIWF) and CLS, in which PSO with AIWF is applied to perform global exploration and CLS is used to perform exploitation to find the optimal solution. Logistics and Gauss map technique is used in performing CLS and the results are compared. The applicability and high feasibility of the proposed method is validated on a standard 5-generator test system. The simulation results confirm that this algorithm is capable of giving higher quality solutions with fast convergence characteristics.",

keywords = "adaptive particle swarm , optimisation, economic dispatch, cubic cost economic dispatch, chaotic adaptive particle swarm optimisation, adaptive inertia weight factor, Economic dispatch, chaotic local search",

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

year = "2015",

month = mar,

day = "16",

doi = "10.1109/EFEA.2014.7059939",

language = "English",

isbn = "9781479975181",

booktitle = "3rd International Symposium on Environment Friendly Energies and Applications, EFEA 2014",

publisher = "IEEE",

address = "United States",

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TY - GEN

T1 - Chaotic adaptive particle swarm optimisation using logistics and gauss map for solving cubic cost 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 proposes Chaotic Adaptive Particle Swarm Optimisation (CAPSO) algorithm to solve Cubic Cost Economic Dispatch (CCED) problem. A Chaotic Local Search operator (CLS) is introduced in the proposed algorithm to avoid premature convergence. The basic strategy of the proposed algorithm is combining PSO with Adaptive Inertia Weight Factor (AIWF) and CLS, in which PSO with AIWF is applied to perform global exploration and CLS is used to perform exploitation to find the optimal solution. Logistics and Gauss map technique is used in performing CLS and the results are compared. The applicability and high feasibility of the proposed method is validated on a standard 5-generator test system. The simulation results confirm that this algorithm is capable of giving higher quality solutions with fast convergence characteristics.

AB - This paper proposes Chaotic Adaptive Particle Swarm Optimisation (CAPSO) algorithm to solve Cubic Cost Economic Dispatch (CCED) problem. A Chaotic Local Search operator (CLS) is introduced in the proposed algorithm to avoid premature convergence. The basic strategy of the proposed algorithm is combining PSO with Adaptive Inertia Weight Factor (AIWF) and CLS, in which PSO with AIWF is applied to perform global exploration and CLS is used to perform exploitation to find the optimal solution. Logistics and Gauss map technique is used in performing CLS and the results are compared. The applicability and high feasibility of the proposed method is validated on a standard 5-generator test system. The simulation results confirm that this algorithm is capable of giving higher quality solutions with fast convergence characteristics.

KW - adaptive particle swarm

KW - optimisation

KW - economic dispatch

KW - cubic cost economic dispatch

KW - chaotic adaptive particle swarm optimisation

KW - adaptive inertia weight factor

KW - Economic dispatch

KW - chaotic local search

U2 - 10.1109/EFEA.2014.7059939

DO - 10.1109/EFEA.2014.7059939

M3 - Conference contribution

SN - 9781479975181

BT - 3rd International Symposium on Environment Friendly Energies and Applications, EFEA 2014

PB - IEEE

ER -

Chaotic adaptive particle swarm optimisation using logistics and gauss map for solving cubic cost economic dispatch problem

Abstract

Keywords

Documents and Links

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Research output

An improved optimization technique for estimation of solar photovoltaic parameters

Cite this