Wind power forecast based on cloud model
Mao Yang, QiongQiong Yang · 2016
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.