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Wind power forecast based on cloud model

机译：基于云模型的风力电力预测

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This paper presents a wind power forecast model based on cloud model, aiming at the randomness of the output power of wind turbine system. This model can solve the uncertainty of the output power of the wind power generator effectively through forming a transition model between its qualitative concepts and its ration expressions showed by numerical characteristics used specific algorithm. To make the predictions more accurate, firstly, the data is divided into an upper data and a waist data. Then these two kinds of data are analyzed separately. Secondly, the parameters of the upper data and the waist data are gotten by using known and unknown membership backward cloud generator. Finally, forward cloud generator and X conditions cloud generator are compiled separately and the Matlab program of the power cloud droplets are generated. The predictive power values can be generated after importing wind speed data. The prediction results show that the cloud model in this paper is adapted for total power prediction and the prediction results is better than other models and the accuracy of the upper data is better than the waist data by using this model.
机译：本文介绍了基于云模型的风力预测模型，旨在瞄准风力涡轮机系统输出功率的随机性。该模型可以通过在其定性概念之间形成转换模型及其对数值特定算法的数值特征而显示的转换模型来解决风力发电机输出功率的不确定性。为了使预测更准确，首先，将数据分成上部数据和腰部数据。然后分别分别分析这两种数据。其次，通过使用已知和未知的隶属蒙太云生成器来获得上部数据和腰部数据的参数。最后，转发云生成器和X条件云发生器分别编译，并生成电源云液滴的MATLAB程序。在导入风速数据之后可以生成预测功率值。预测结果表明，本文中的云模型适用于总功率预测，并且预测结果比其他模型更好，并且通过使用该模型优于腰部数据更好。

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