A hybrid statistical method to predict wind speed and wind power

Hui Liu, Hong-Qi Tian, Chao Chen and Yan-fei Li

Renewable Energy, 2010, vol. 35, issue 8, 1857-1861

Abstract: Accurate forecasting of wind speed and wind power is important for the safety of renewable energy utilization. Compared with physical methods, statistical methods are usually simpler and more suitable for small farms. Based on the methods of wavelet and classical time series analysis, a new short-term forecasting method is proposed. Simulation upon actual time data shows that: (1) the mean relative error in multi-step forecasting based on the proposed method is small, which is better than classical time series method and BP network method; (2) the proposed method is robust in dealing with jumping data; and (3) the proposed method is applicable to both wind speed and wind power forecasting.

Keywords: Wind power; Wind speed; Wind farms; Optimization algorithm; Forecasting (search for similar items in EconPapers)
Date: 2010
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Citations: View citations in EconPapers (53)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:35:y:2010:i:8:p:1857-1861

DOI: 10.1016/j.renene.2009.12.011

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