A high-altitude wind resource assessment method for decentralized wind power based on improved linear regression

Lei Zhang, Wenbin Song, Enhui Sun, Qiukai Zhang, Di Wu, Feng Chen and Yanfeng Liu

Renewable Energy, 2025, vol. 238, issue C

Abstract: As centralized wind power construction approaches saturation, the demand for decentralized wind power in cities, enterprises, and village is gradually increasing. Unlike the construction period of traditional large centralized wind farms, rapid, flexible, and low-cost wind resource assessment is key to the application of decentralized wind power. This paper proposes a method for assessing high-altitude wind resources, which can support the construction of decentralized wind power. The method includes unmanned aerial vehicle (UAV) and wind measuring points on the ground. The correlation is established between the intermittent short-term and high-altitude wind speed measured by UAV and the continuous long-term ground wind speed, obtaining the high-altitude and long-term wind resource situation. We build upon the original linear regression method to improve the correlation coefficient. Through gradual calculation, the correlation coefficient between the wind speed measured by UAV at and the wind speed measured by ground measuring points is increased from 0.5 to 0.7. The correlation of 5m can reach 0.85, 10m can reach 0.741 and 40m can reach 0.625. The strong correlation proves the effectiveness of this method, which can successfully use ground wind measuring point to restore wind speed at different heights in a wind field, effectively supporting the construction of decentralized wind power.

Keywords: Unmanned aerial vehicle; Wind resource; Decentralized wind power generation; Linear regression; Correlation analysis (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:238:y:2025:i:c:s0960148124020366

DOI: 10.1016/j.renene.2024.121968

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