Blind Source Separation for Forecast of Solar Irradiance
The application of blind source separate (BSS) for forecasting the solar irradiance is presented. First, we used BSS method to separate the initial time sequence, and then we designed the best neural network topology. In consideration of the complex behavior of solar irradiance, either periodic or random, a kind of dynamic neural network, RBFN, was used for such case. After that the separating results were supplied to the input layer and were trained through adjusting the number of neurons in different layers and the weights and biases of the network. until the errors reached the stop conditions. Finally the forecasting model mentioned in this paper was tested through a practical sample, which indicates that the accuracy of the model is more satisfactory than without blind source separation. Thus the method proposed in this paper could also be applicable to other relating fields.
forecast solar energy blind source separation
Gu Yanling Chen Changzheng Zhou Bo
Institute of Vibration and Noise, Shenyang University of Technology, Shenyang , Liaoning ,110870, China
国际会议
三亚
英文
1392-1395
2012-01-06（万方平台首次上网日期，不代表论文的发表时间）