A novel evolutionary algorithm for dynamic economic dispatch with energy saving and emission reduction in power system integrated wind power

An optimization algorithm is proposed in this paper to solve the economic dispatch problem that includes wind farm using the Chaotic Quantum Genetic Algorithm (CQGA). In addition to the detailed models of economic dispatch introduction and their associated constraints, the wind power effect is also...

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Published inEnergy (Oxford) Vol. 36; no. 2; pp. 1018 - 1029
Main Author Liao, Gwo-Ching
Format Journal Article
LanguageEnglish
Published Kidlington Elsevier Ltd 01.02.2011
Elsevier
Subjects
Algorithms
Applied sciences
Chaos theory
Chaotic quantum genetic algorithm
Dynamic economic dispatch
Dynamical systems
Dynamics
econometric models
Economic data
Economics
Electric energy
Emission reduction
Energy
energy conservation
Energy economics
Energy saving
Exact sciences and technology
General, economic and professional studies
Genetic algorithms
Methodology. Modelling
Natural energy
Optimization
power generation
Power system integrated wind power
wind power
Wind power generation
Emission reduction
Chaotic quantum genetic algorithm
Power system integrated wind power
Energy saving
Dynamic economic dispatch
Cost minimization
Optimal strategy
Energy cost
Wind energy
Genetic algorithm
Evolutionary algorithm
Economic optimization
Electric power production
Constrained optimization
Online AccessGet full text
ISSN0360-5442
DOI10.1016/j.energy.2010.12.006

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Abstract An optimization algorithm is proposed in this paper to solve the economic dispatch problem that includes wind farm using the Chaotic Quantum Genetic Algorithm (CQGA). In addition to the detailed models of economic dispatch introduction and their associated constraints, the wind power effect is also included in this paper. The chaotic quantum genetic algorithm used to solve the economic dispatch process and discussed with real scenarios used for the simulation tests. After comparing the proposed algorithm with several other algorithms commonly used to solve optimization problems, the results show that the proposed algorithm is able to find the optimal solution quickly and accurately (i.e. to obtain the minimum cost for power generation in the shortest time). At the end, the impact to the total cost savings for power generation after adding (or not adding) wind power generation is also discussed. The actual implementation results prove that the proposed algorithm is economical, fast and practical. They are quite valuable for further research. ► Quantum Genetic Algorithm can effectively improve the global search ability. ► It can achieve the real objective of the global optimal solutions. ► The CPU computation time is less than that other algorithms adopted in this paper.
AbstractList An optimization algorithm is proposed in this paper to solve the economic dispatch problem that includes wind farm using the Chaotic Quantum Genetic Algorithm (CQGA). In addition to the detailed models of economic dispatch introduction and their associated constraints, the wind power effect is also included in this paper. The chaotic quantum genetic algorithm used to solve the economic dispatch process and discussed with real scenarios used for the simulation tests. After comparing the proposed algorithm with several other algorithms commonly used to solve optimization problems, the results show that the proposed algorithm is able to find the optimal solution quickly and accurately (i.e. to obtain the minimum cost for power generation in the shortest time). At the end, the impact to the total cost savings for power generation after adding (or not adding) wind power generation is also discussed. The actual implementation results prove that the proposed algorithm is economical, fast and practical. They are quite valuable for further research.
An optimization algorithm is proposed in this paper to solve the economic dispatch problem that includes wind farm using the Chaotic Quantum Genetic Algorithm (CQGA). In addition to the detailed models of economic dispatch introduction and their associated constraints, the wind power effect is also included in this paper. The chaotic quantum genetic algorithm used to solve the economic dispatch process and discussed with real scenarios used for the simulation tests. After comparing the proposed algorithm with several other algorithms commonly used to solve optimization problems, the results show that the proposed algorithm is able to find the optimal solution quickly and accurately (i.e. to obtain the minimum cost for power generation in the shortest time). At the end, the impact to the total cost savings for power generation after adding (or not adding) wind power generation is also discussed. The actual implementation results prove that the proposed algorithm is economical, fast and practical. They are quite valuable for further research. ► Quantum Genetic Algorithm can effectively improve the global search ability. ► It can achieve the real objective of the global optimal solutions. ► The CPU computation time is less than that other algorithms adopted in this paper.
Author Liao, Gwo-Ching
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  organization: Fortune Institute of Technology, Department of Electrical Engineering, No. 1-10, Nwongchang Rd, Lyouciyou Village, Daliao Township, Kaohsiung 831, Taiwan
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Issue 2
Keywords Emission reduction
Chaotic quantum genetic algorithm
Power system integrated wind power
Energy saving
Dynamic economic dispatch
Cost minimization
Optimal strategy
Energy cost
Wind energy
Genetic algorithm
Evolutionary algorithm
Economic optimization
Electric power production
Constrained optimization
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Snippet An optimization algorithm is proposed in this paper to solve the economic dispatch problem that includes wind farm using the Chaotic Quantum Genetic Algorithm...
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SubjectTerms Algorithms
Applied sciences
Chaos theory
Chaotic quantum genetic algorithm
Dynamic economic dispatch
Dynamical systems
Dynamics
econometric models
Economic data
Economics
Electric energy
Emission reduction
Energy
energy conservation
Energy economics
Energy saving
Exact sciences and technology
General, economic and professional studies
Genetic algorithms
Methodology. Modelling
Natural energy
Optimization
power generation
Power system integrated wind power
wind power
Wind power generation
Title A novel evolutionary algorithm for dynamic economic dispatch with energy saving and emission reduction in power system integrated wind power
URI https://dx.doi.org/10.1016/j.energy.2010.12.006
https://www.proquest.com/docview/1663551595
https://www.proquest.com/docview/1777113878
https://www.proquest.com/docview/864404569
Volume 36
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