Short-term wind speed forecasting is crucial to enhance the operational efficiency and increase the economic benefit of wind power generation systems. A substantial number of studies were conducted to enhance wind speed forecasting. Combined models are increasingly being preferred, as they always yield better results. However, the current combined models either do not fully consider the different characteristics hidden in the wind speed series or are restricted by the difficulties in modeling very unstable and irregular data, which leads to a limited forecasting enhancement. To overcome the limitation of the current combined models and provide a more reliable wind speed prediction, this study proposes an efficient combined forecasting system that innovatively adopts a more advanced multi-layer cooperative combined strategy, which inherits the strengths of the conventional combined strategies while simultaneously avoiding some of their limitations. It successfully overcomes some drawbacks of some current models, for example, low accuracy and high instability, and significantly improve the forecasting performance. Experiments conducted in this study demonstrate that the proposed system is superior to other single or combined methods, as it can always obtain a higher forecasting accuracy and stability. It can offer a practical method to forecast wind speed.

短期风速预测对于提高运营效率和增加风力发电系统的经济效益至关重要。进行了大量研究以增强风速预报。组合模型越来越受欢迎，因为它们总是可以产生更好的结果。但是，当前的组合模型要么没有充分考虑风速序列中隐藏的不同特征，要么受到建模非常不稳定和不规则数据的困难的限制，这导致有限的预测增强。为了克服当前组合模型的局限性并提供更可靠的风速预测，本研究提出了一种有效的组合预测系统，该系统创新地采用了更高级的多层协作组合策略，它继承了传统组合策略的优势，同时避免了它们的某些局限性。它成功地克服了一些当前模型的一些缺点，例如，低准确性和高不稳定性，并显着提高了预测性能。在这项研究中进行的实验表明，所提出的系统优于其他单一或组合方法，因为它始终可以获得更高的预测准确性和稳定性。它可以提供一种预测风速的实用方法。在这项研究中进行的实验表明，所提出的系统优于其他单一或组合方法，因为它始终可以获得更高的预测准确性和稳定性。它可以提供一种预测风速的实用方法。在这项研究中进行的实验表明，所提出的系统优于其他单一或组合方法，因为它始终可以获得更高的预测准确性和稳定性。它可以提供一种预测风速的实用方法。