Wind power curve model combining smoothed spline with first-order moments and density-adjusted wind speed strategy

Tianhao Liu, Kunye Lv, Fengjie Chen, Hui Hwang Goh, Tonni Agustiono Kurniawan, Ruifeng Hu, Meihui Jiang and Dongdong Zhang

Energy, 2024, vol. 313, issue C

Abstract: Given the variety of potential application scenarios, it is crucial to develop wind power curves that are more accurate, smoother, efficient, and applicable across a wider range of contexts. To this end, a wind power curve model combining smoothed spline with first-order moments (FOM) and density-adjusted wind speed (DAWS) strategy is proposed in this paper. First, the DAWS strategy is employed to consider the influence of meteorological factors on the wind power curve by adjusting wind speed. This strategy reduces the root mean square error (RMSE) by 5.81%–6.17 % and the mean absolute error (MAE) by 5.84%–6.44 % without adding complexity to the model. Secondly, FOM is proposed as a substitute for the original data during the modeling process. This approach reduces the number of operations on the similar data, resulting in a reduction of modeling time by 48.11%–99.89 %. Furthermore, the impact on model accuracy is minimal. Finally, a the wind power curve model based on smooth spline is constructed, which exhibits superior smoothness, a broader range of generalizability, enhanced model accuracy, and reductions in RMSE by 5.67%–23.87 % and MAE by 4.79%–22.35 % in comparison to the control method.

Keywords: Wind power curves; Density-adjusted wind speed; Meteorological factors; First-order moments; Smooth spline (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:313:y:2024:i:c:s0360544224034066

DOI: 10.1016/j.energy.2024.133628

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