Wind Technologies for Wake Effect Performance in Windfarm Layout Based on Population-Based Optimization Algorithm

Yi-Zeng Hsieh, Shih-Syun Lin, En-Yu Chang, Kwong-Kau Tiong, Shih-Wei Tan, Chiou-Yi Hor, Shyi-Chy Cheng, Yu-Shiuan Tsai and Chao-Rong Chen
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Yi-Zeng Hsieh: Department of Electrical Engineering, National Taiwan Ocean University, Keelung City 202301, Taiwan
Shih-Syun Lin: Department of Computer Science and Engineering, National Taiwan Ocean University, Keelung City 202301, Taiwan
En-Yu Chang: Department of Electrical Engineering, National Taiwan Ocean University, Keelung City 202301, Taiwan
Kwong-Kau Tiong: Department of Electrical Engineering, National Taiwan Ocean University, Keelung City 202301, Taiwan
Shih-Wei Tan: Department of Electrical Engineering, National Taiwan Ocean University, Keelung City 202301, Taiwan
Chiou-Yi Hor: Green Energy and System Integration R&D Department, China Steel Corporation, Kaohsiung 81233, Taiwan
Shyi-Chy Cheng: Department of Computer Science and Engineering, National Taiwan Ocean University, Keelung City 202301, Taiwan
Yu-Shiuan Tsai: Department of Computer Science and Engineering, National Taiwan Ocean University, Keelung City 202301, Taiwan
Chao-Rong Chen: Department of Electrical Engineering, National Taipei University of Technology, Taipei 10608, Taiwan

Energies, 2021, vol. 14, issue 14, 1-17

Abstract: The focus of this study is under the auspices of China Steel Corporation, Taiwan, in carrying out the national energy policy of 2025 Non-Nuclear Home. Under this policy, an estimated 600 offshore wind turbines will be installed by 2025. In order to carry out the wind energy project effectively, a preliminary study must be conducted. In this article, we investigated the influence of the wake effect on the efficiency of the turbines’ layout in a windfarm. A distributed genetic algorithm is deployed to study the wind turbines’ layout in order to alleviate the detrimental wake effect. In the current stage of this research, the historical weather data of weather stations near the site of the 29th windfarm, Taiwan, were collected by Academia Sinica. Our wake effect resilient optimized windfarm showed superior performance over that of the conventional windfarm. Additionally, an operation cost minimization process is also demonstrated and implemented using an ant colony optimization algorithm to optimize the total length of the power-carrying interconnecting cables for the turbines inside the optimized windfarm.

Keywords: wake effects; optimization algorithm; turbines layout; wind distribution (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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