Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.13091/160
Title: A Jaya-based approach to wind turbine placement problem
Authors: Aslan, Murat
Gündüz, Mesut
Kıran, Mustafa Servet
Keywords: Clean Energy
Jaya
Renewable Energy
Wind Energy
Wind Turbine Replacement
Layout Optimization
Renewable Energy
Algorithm
Farm
Methodology
Number
Issue Date: 2023
Publisher: TAYLOR & FRANCIS INC
Abstract: Renewable energy resources are natural, clean, economical, and never-ending energy resources. Wind energy is an important clean, cheap, and easy applicable energy sources. On account of this, generation of the energy from wind technology has been raised day by day because of the competition with fossil-fuel power production methods. By depending on increases the number of turbines located in the wind farm, the average power obtains from each wind turbine appreciable reduces due to the existence of wake effects within the wind farm. Therefore, the optimal placement of turbines in a wind farm provides to get optimum wind energy from the wind farm. When the place where the wind turbines are located is considered as NxN grid, a wind turbine can be established to each cell of this grid. Whether a wind turbine is replaced to each cell of the grid or not can be modeled as a binary-based optimization problem. In this study, a Jaya-based binary optimization algorithm is proposed to determine which cells are used for wind turbine replacement. In order to justify the efficiency of the proposed approach, two different test cases are considered, and the solutions produced by the proposed approach are compared with the solutions of the swarm intelligence or evolutionary computation methods. According to the experiments and comparisons the Jaya-based binary approach shows a superior performance than compared approaches in terms of cost and power effectiveness. While the efficiency of the Jaya-based approach is 92.2% with 30 turbines replacement on 10 x 10 grid, the efficiency of the Jaya-based binary method is 95.7% with 43 turbines replacement on 20 x 20 grid.
URI: https://doi.org/10.1080/15567036.2020.1805528
https://hdl.handle.net/20.500.13091/160
ISSN: 1556-7036
1556-7230
Appears in Collections:Mühendislik ve Doğa Bilimleri Fakültesi Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

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