Solving the economic dispatch problem with a modified quantum-behaved particle swarm optimization method

In this paper, a modified quantum-behaved particle swarm optimization (QPSO) method is proposed to solve the economic dispatch (ED) problem in power systems, whose objective is to simultaneously minimize the generation cost rate while satisfying various equality and inequality constraints. The propo...

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Vydáno v:	Energy conversion and management Ročník 50; číslo 12; s. 2967 - 2975
Hlavní autoři:	Sun, Jun, Fang, Wei, Wang, Daojun, Xu, Wenbo
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Kidlington Elsevier Ltd 01.12.2009 Elsevier
Témata:	Applied sciences Constrained optimization Differential mutation operation Economic data Economic dispatch Electric energy Energy Energy economics Exact sciences and technology General, economic and professional studies Heuristics Methodology. Modelling Particle swarm optimization Power generation Economic dispatch Differential mutation operation Particle swarm optimization Heuristics Power generation Constrained optimization Performance evaluation Cost minimization Case study Optimal strategy Production cost Mutation Electric power production Differential method
ISSN:	0196-8904, 1879-2227
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Abstract	In this paper, a modified quantum-behaved particle swarm optimization (QPSO) method is proposed to solve the economic dispatch (ED) problem in power systems, whose objective is to simultaneously minimize the generation cost rate while satisfying various equality and inequality constraints. The proposed method, denoted as QPSO-DM, combines the QPSO algorithm with differential mutation operation to enhance the global search ability of the algorithm. Many nonlinear characteristics of the generator, such as ramp rate limits, prohibited operating zones, and nonsmooth cost functions are considered when the proposed method is used in practical generator operation. The feasibility of the QPSO–DM method is demonstrated by three different power systems. It is compared with the QPSO, the differential evolution (DE), the particle swarm optimization (PSO), and the genetic algorithm (GA) in terms of the solution quality, robustness and convergence property. The simulation results show that the proposed QPSO–DM method is able to obtain higher quality solutions stably and efficiently in the ED problem than any other tested optimization algorithm.
AbstractList	In this paper, a modified quantum-behaved particle swarm optimization (QPSO) method is proposed to solve the economic dispatch (ED) problem in power systems, whose objective is to simultaneously minimize the generation cost rate while satisfying various equality and inequality constraints. The proposed method, denoted as QPSO-DM, combines the QPSO algorithm with differential mutation operation to enhance the global search ability of the algorithm. Many nonlinear characteristics of the generator, such as ramp rate limits, prohibited operating zones, and nonsmooth cost functions are considered when the proposed method is used in practical generator operation. The feasibility of the QPSO-DM method is demonstrated by three different power systems. It is compared with the QPSO, the differential evolution (DE), the particle swarm optimization (PSO), and the genetic algorithm (GA) in terms of the solution quality, robustness and convergence property. The simulation results show that the proposed QPSO-DM method is able to obtain higher quality solutions stably and efficiently in the ED problem than any other tested optimization algorithm.
Author	Sun, Jun Xu, Wenbo Wang, Daojun Fang, Wei
Author_xml	– sequence: 1 givenname: Jun surname: Sun fullname: Sun, Jun email: sunjun_wx@hotmail.com – sequence: 2 givenname: Wei surname: Fang fullname: Fang, Wei – sequence: 3 givenname: Daojun surname: Wang fullname: Wang, Daojun – sequence: 4 givenname: Wenbo surname: Xu fullname: Xu, Wenbo
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Snippet	In this paper, a modified quantum-behaved particle swarm optimization (QPSO) method is proposed to solve the economic dispatch (ED) problem in power systems,...
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SubjectTerms	Applied sciences Constrained optimization Differential mutation operation Economic data Economic dispatch Electric energy Energy Energy economics Exact sciences and technology General, economic and professional studies Heuristics Methodology. Modelling Particle swarm optimization Power generation
Title	Solving the economic dispatch problem with a modified quantum-behaved particle swarm optimization method
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