CAJ | 학술논문

以风电功率预测为背景，将小波理论与神经网络结合，在BP神经网络模型的结构基础上构造了小波神经网络，并提出了基于附加动量法改进的小波神经网络。利用附加动量的小波神经网络建立天气预报数据与发电功率的映射模型，并进行实际预测。利用MATLAB进行仿真，验证了设计预测模型的实际可行性，并且预测精度满足相关要求。
이풍전공솔예측위배경，장소파이론여신경망락결합，재BP신경망락모형적결구기출상구조료소파신경망락，병제출료기우부가동량법개진적소파신경망락。이용부가동량적소파신경망락건립천기예보수거여발전공솔적영사모형，병진행실제예측。이용MATLAB진행방진，험증료설계예측모형적실제가행성，병차예측정도만족상관요구。
Against the background of the wind power forecasting,the wavelet theory and neural network were com-bined to set up the WNN model based on the BPNN structure,and the WNN was put forward based on the additional momentum method in this paper. A model was set up with the method based on the numerical weather prediction data and wind power data from a wind farm in Inner Mongolia Autonomous Region. The MATLAB was used to simulate and verify the feasibility of this prediction model. Simulation had shown the precision of the model can meet the re-quirements.