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Article

Generation Expansion Planning in the Presence of Wind Power Plants Using a Genetic Algorithm Model

1
Khorasan Regional Electricity Company, Birjand 91843, Iran
2
Faculty of Electrical and Computer Engineering, University of Birjand, Birjand 9717434765, Iran
3
Faculty of Computer and Industries, Birjand University of Technology, Birjand 9719866981, Iran
4
Faculty of Civil Engineering, Technische Universität Dresden, 01069 Dresden, Germany
5
Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam
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Department of Informatics, J. Selye University, 94501 Komarno, Slovakia
7
School of the Built Environment and Architecture, London South Bank University, London SE1 0AA, UK
*
Author to whom correspondence should be addressed.
Electronics 2020, 9(7), 1143; https://doi.org/10.3390/electronics9071143
Received: 25 May 2020 / Revised: 6 July 2020 / Accepted: 7 July 2020 / Published: 14 July 2020
(This article belongs to the Special Issue Emerging Technologies in Power Systems)
One of the essential aspects of power system planning is generation expansion planning (GEP). The purpose of GEP is to enhance construction planning and reduce the costs of installing different types of power plants. This paper proposes a method based on a genetic algorithm (GA) for GEP in the presence of wind power plants. Since it is desirable to integrate the maximum possible wind power production in GEP, the constraints for incorporating different levels of wind energy in power generation are investigated comprehensively. This will allow the maximum reasonable amount of wind penetration in the network to be obtained. Besides, due to the existence of different wind regimes, the penetration of strong and weak wind on GEP is assessed. The results show that the maximum utilization of wind power generation capacity could increase the exploitation of more robust wind regimes. Considering the growth of the wind farm industry and the cost reduction for building wind power plants, the sensitivity of GEP to the variations of this cost is investigated. The results further indicate that for a 10% reduction in the initial investment cost of wind power plants, the proposed model estimates that the overall cost will be minimized. View Full-Text
Keywords: generation expansion planning; wind power; genetic algorithm; least-cost generation expansion planning; machine learning; soft computing; mathematical programming; renewable energies; artificial intelligence; electronics; power plant; power station generation expansion planning; wind power; genetic algorithm; least-cost generation expansion planning; machine learning; soft computing; mathematical programming; renewable energies; artificial intelligence; electronics; power plant; power station
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MDPI and ACS Style

Sahragard, A.; Falaghi, H.; Farhadi, M.; Mosavi, A.; Estebsari, A. Generation Expansion Planning in the Presence of Wind Power Plants Using a Genetic Algorithm Model. Electronics 2020, 9, 1143. https://doi.org/10.3390/electronics9071143

AMA Style

Sahragard A, Falaghi H, Farhadi M, Mosavi A, Estebsari A. Generation Expansion Planning in the Presence of Wind Power Plants Using a Genetic Algorithm Model. Electronics. 2020; 9(7):1143. https://doi.org/10.3390/electronics9071143

Chicago/Turabian Style

Sahragard, Ali, Hamid Falaghi, Mahdi Farhadi, Amir Mosavi, and Abouzar Estebsari. 2020. "Generation Expansion Planning in the Presence of Wind Power Plants Using a Genetic Algorithm Model" Electronics 9, no. 7: 1143. https://doi.org/10.3390/electronics9071143

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