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Characteristics of Wind Resources and Post-Project Evaluation of Wind Farms in Coastal Areas of Zhejiang

Guangyu Fan, Yanru Wang, Bo Yang, Chuanxiong Zhang, Bin Fu and Qianqian Qi
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Guangyu Fan: School of Civil Engineering and Architecture, Zhejiang SCI-TECH University, Hangzhou 310018, China
Yanru Wang: School of Civil Engineering, Taizhou University, Jiaojiang 318000, China
Bo Yang: School of Civil Engineering and Architecture, Zhejiang SCI-TECH University, Hangzhou 310018, China
Chuanxiong Zhang: Key Laboratory of Intelligent Lifeline Protection and Emergency Technology for Resident ATY, Wenzhou University of Technology, Wenzhou 150080, China
Bin Fu: School of Civil Engineering, Taizhou University, Jiaojiang 318000, China
Qianqian Qi: State Key Laboratory of Mountain Bridge and Tunnel Engineering, Chongqing Jiaotong University, Chongqing 400074, China

Energies, 2022, vol. 15, issue 9, 1-18

Abstract: As the onshore wind farm technology matures, offshore wind energy has attracted increasing attention. Zhejiang has coastal areas with massive potential for wind resources because of its geographical location. Therefore, understanding the wind resources in these areas can lay a foundation for future development and utilization. On this basis, this study used the measured wind field data of a wind farm along the coast of Zhejiang from March 2014 to February 2015 and from March 2016 to February 2018 to investigate and compare the characteristics of wind energy resources, including average wind speed, Weibull shape and scale factors, wind direction variation, and wind energy density. Then, the capacity coefficient of a wind turbine predicted using the wind farm data was compared with the actual capacity coefficients of two wind turbines in the wind farm in 2019. Results revealed the following observations: The overall variations in the evaluation indicators followed clear patterns over the 3 years. For example, the main wind direction in the same season was the same, and the variations in the monthly average wind speed, the monthly wind power density, and the theoretical capacity factors were highly similar. The time-series data indicated that the difference in the indicators between summer and autumn was significantly larger than that between other seasons, with the maximum difference in monthly average wind speed of 1.46 times and the maximum difference in monthly wind power density of 1.5 times. The comparison results of the capacity coefficient showed that the theoretical and actual capacity coefficients were extremely close when the monthly average wind speed was less than 6 m/s, with the average difference being less than 9%. When the monthly average wind speed was greater than 6 m/s, the proximity between the theoretical and actual capacity coefficients was reduced, with an average difference of more than 9% and a maximum value of 28%. In general, the overall characteristics of wind resources in coastal areas of Zhejiang exhibited similar trends but fluctuated considerably in some months. Wind energy forecasts had significant discrepancies from the actual operation indicators of the wind farm when the wind speed was high.

Keywords: wind energy characteristics; Weibull distribution; wind power density; wind farm; capacity factor; post-project evaluation (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: 2022
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