Proceedings of the 2018 International Conference on Information Technology and Management Engineering (ICITME 2018)

Quantum-behaved Particle Swarm Optimization for Multiple-fuel-constrained Generation Scheduling of Power System

Authors
Chao-Lung Chiang
Corresponding Author
Chao-Lung Chiang
Available Online August 2018.
DOI
10.2991/icitme-18.2018.37How to use a DOI?
Keywords
quantum-behaved particle swarm optimization; generation scheduling; multiple-fuel-constrained; power system
Abstract

This research proposes a quantum-behaved particle swarm optimization with a multiplier updating technique (QPSO-MU) for the multiple-fuel-constrained generation scheduling of power system. The quantum-behaved particle swarm optimization (QPSO) equips with a migration can efficiently search and actively explore solutions. The multiplier updating (MU) is introduced to avoid deforming the augmented Lagrange function and resulting in difficulty of solution searching. The proposed algorithm integrates the QPSO and the MU that has merits of automatically adjusting the randomly given penalty to a proper value and requiring only a small-size population for the power economic dispatch problem of the multiple-fuel-constrained generation scheduling. Numerical results of two test systems indicate that the proposed algorithm is more suitable than previous approaches in the practical economic dispatch for the multiple-fuel-constrained generation scheduling of power system.

Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Proceedings of the 2018 International Conference on Information Technology and Management Engineering (ICITME 2018)
Series
Advances in Intelligent Systems Research
Publication Date
August 2018
ISBN
978-94-6252-607-5
ISSN
1951-6851
DOI
10.2991/icitme-18.2018.37How to use a DOI?
Copyright
© 2018, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

TY  - CONF
AU  - Chao-Lung Chiang
PY  - 2018/08
DA  - 2018/08
TI  - Quantum-behaved Particle Swarm Optimization for Multiple-fuel-constrained Generation Scheduling of Power System
BT  - Proceedings of the 2018 International Conference on Information Technology and Management Engineering (ICITME 2018)
PB  - Atlantis Press
SP  - 185
EP  - 188
SN  - 1951-6851
UR  - https://doi.org/10.2991/icitme-18.2018.37
DO  - 10.2991/icitme-18.2018.37
ID  - Chiang2018/08
ER  -