Applicability research and integrated application of various correction methods for wind speed forecast in a wind farm
Received date: 2021-11-18
Revised date: 2022-01-12
Online published: 2022-08-11
The method used for evaluating the correction effect of a model is very important for improving the short-term wind speed forecast. At present, the comparison of the correlation coefficient and error between the corrected and forecasted wind speeds in the research period is generally adopted. This evaluation method often ignores the limited correction ability of most statistical correction methods in low and high wind speed sections. Taking a wind farm in central Inner Mongolia, China as the experimental site, this study uses the three methods of random forest (RF), analog correction of errors (ACE), and probability density function matching method (PDF) to correct the wind speed forecast in the experimental wind farm. A correlation coefficient and error analysis of the whole research period is performed. Wind speed is classified into cut-in wind speed, low, high, and full generating wind speeds, and cut-out wind speed. The applicability study of the three models in each grade is then conducted. The results show that the three methods have different degrees of correction effects on the weather research forecast (WRF) of wind speed in each season. The average absolute error promotion rates in sequence are 6.7%-36.7%, 11.1%-34.7%, and 3.7%-20.6% after correction via the RF, ACE, and PDF methods, respectively, in the model validation period. The RF method can effectively improve the large error problem of the WRF, but it also has the error overamplification problem. Although the ACE and PDF methods have less ability for improving the large error compared with the RF method, they can better control the error overamplification problem. For the small wind speed section of less than 5 m·s-1, the correction effect of the three methods is not ideal. The original WRF forecast and PDF method are better than the RF and ACE methods. With the wind speed increase, the WRF forecast error significantly increases, and the correction ability of the three methods gradually increases. The RF and ACE methods are better than the PDF methods in the wind speed level of [5,16). The correction ability of the ACE method begins to decline, whereas that of the PDF method begins to improve in the wind speed level of [16,+∞). According to the respective advantages of the forecast models, the integrated application of various forecast models considering the wind speed forecast level is attempted to improve the WRF forecast under different wind speed levels.
Li’na XU , Yanbo SHEN , Zhen FENG , Hu YE . Applicability research and integrated application of various correction methods for wind speed forecast in a wind farm[J]. Arid Land Geography, 2022 , 45(4) : 1114 -1124 . DOI: 10.12118/j.issn.1000-6060.2021.547
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