有哪些信誉好的足球投注网站an improved quantum-behaved particle swarm optimization method for economic dispatch problems with multiple fuel options and valve-points effects一种改进研究经济调度问题的粒子群优化方法与多个燃料选项和随机性的影响.pdfVIP
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an improved quantum-behaved particle swarm optimization method for economic dispatch problems with multiple fuel options and valve-points effects一种改进研究经济调度问题的粒子群优化方法与多个燃料选项和随机性的影响
Energies 2012, 5, 3655-3673; doi:10.3390/en5093655
OPEN ACCESS
energies
ISSN 1996-1073
/journal/energies
Article
An Improved Quantum-Behaved Particle Swarm Optimization
Method for Economic Dispatch Problems with Multiple Fuel
Options and Valve-Points Effects
Qun Niu 1,*, Zhuo Zhou 1, Hong-Yun Zhang 1 and Jing Deng 2
1 Shanghai Key Laboratory of Power Automation Technology, School of Mechatronics Engineering
and Automation, Shanghai University, Shanghai 200072, China;
E-Mails: zhouzhuo1101@ (Z.Z.); zhanghongyun@ (H.-Y.Z.)
2 Intelligent Systems and Control Group, School of Electronics, Electrical Engineering and Computer
Science, Queen’s University of Belfast, Belfast BT9 5AH, UK; E-Mail: jdeng01@qub.ac.uk
* Author to whom correspondence should be addressed; E-Mail: comelycc@;
Tel./Fax: +86-21
Received: 2 July 2012; in revised form: 10 August 2012 / Accepted: 22 August 2012 /
Published: 19 September 2012
Abstract: 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,
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