An Improved Quantum-Behaved Particle Swarm Optimization Method for Economic Dispatch Problems with Multiple Fuel Options and Valve-Points Effects
Quantum-behaved particle swarm optimization (QPSO) is an efficient and powerful population-based optimization technique, which is inspired by the conventional particle swarm optimization (PSO) and quantum mechanics theories. In this paper, an improved QPSO named SQPSO is proposed, which combines QPS...
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2012-09-01
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doaj-6914c72928d54e758921305845cdb1ee2020-11-24T23:05:00ZengMDPI AGEnergies1996-10732012-09-01593655367310.3390/en5093655An Improved Quantum-Behaved Particle Swarm Optimization Method for Economic Dispatch Problems with Multiple Fuel Options and Valve-Points EffectsHong-Yun ZhangJing DengZhuo ZhouQun NiuQuantum-behaved particle swarm optimization (QPSO) is an efficient and powerful population-based optimization technique, which is inspired by the conventional particle swarm optimization (PSO) and quantum mechanics theories. In this paper, an improved QPSO named SQPSO is proposed, which combines QPSO with a selective probability operator to solve the economic dispatch (ED) problems with valve-point effects and multiple fuel options. To show the performance of the proposed SQPSO, it is tested on five standard benchmark functions and two ED benchmark problems, including a 40-unit ED problem with valve-point effects and a 10-unit ED problem with multiple fuel options. The results are compared with differential evolution (DE), particle swarm optimization (PSO) and basic QPSO, as well as a number of other methods reported in the literature in terms of solution quality, convergence speed and robustness. The simulation results confirm that the proposed SQPSO is effective and reliable for both function optimization and ED problems.http://www.mdpi.com/1996-1073/5/9/3655economic dispatchquantum-behaved particle swarm optimizationvalve-point effectsmultiple fuel options |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Hong-Yun Zhang Jing Deng Zhuo Zhou Qun Niu |
spellingShingle |
Hong-Yun Zhang Jing Deng Zhuo Zhou Qun Niu An Improved Quantum-Behaved Particle Swarm Optimization Method for Economic Dispatch Problems with Multiple Fuel Options and Valve-Points Effects Energies economic dispatch quantum-behaved particle swarm optimization valve-point effects multiple fuel options |
author_facet |
Hong-Yun Zhang Jing Deng Zhuo Zhou Qun Niu |
author_sort |
Hong-Yun Zhang |
title |
An Improved Quantum-Behaved Particle Swarm Optimization Method for Economic Dispatch Problems with Multiple Fuel Options and Valve-Points Effects |
title_short |
An Improved Quantum-Behaved Particle Swarm Optimization Method for Economic Dispatch Problems with Multiple Fuel Options and Valve-Points Effects |
title_full |
An Improved Quantum-Behaved Particle Swarm Optimization Method for Economic Dispatch Problems with Multiple Fuel Options and Valve-Points Effects |
title_fullStr |
An Improved Quantum-Behaved Particle Swarm Optimization Method for Economic Dispatch Problems with Multiple Fuel Options and Valve-Points Effects |
title_full_unstemmed |
An Improved Quantum-Behaved Particle Swarm Optimization Method for Economic Dispatch Problems with Multiple Fuel Options and Valve-Points Effects |
title_sort |
improved quantum-behaved particle swarm optimization method for economic dispatch problems with multiple fuel options and valve-points effects |
publisher |
MDPI AG |
series |
Energies |
issn |
1996-1073 |
publishDate |
2012-09-01 |
description |
Quantum-behaved particle swarm optimization (QPSO) is an efficient and powerful population-based optimization technique, which is inspired by the conventional particle swarm optimization (PSO) and quantum mechanics theories. In this paper, an improved QPSO named SQPSO is proposed, which combines QPSO with a selective probability operator to solve the economic dispatch (ED) problems with valve-point effects and multiple fuel options. To show the performance of the proposed SQPSO, it is tested on five standard benchmark functions and two ED benchmark problems, including a 40-unit ED problem with valve-point effects and a 10-unit ED problem with multiple fuel options. The results are compared with differential evolution (DE), particle swarm optimization (PSO) and basic QPSO, as well as a number of other methods reported in the literature in terms of solution quality, convergence speed and robustness. The simulation results confirm that the proposed SQPSO is effective and reliable for both function optimization and ED problems. |
topic |
economic dispatch quantum-behaved particle swarm optimization valve-point effects multiple fuel options |
url |
http://www.mdpi.com/1996-1073/5/9/3655 |
work_keys_str_mv |
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