Zhou Qiang

TL;DR: In this article, a photovoltaic super-short-term generated power forecasting method based on cloud cover simulation is proposed, which has the greater advantages on the aspect of capturing the cloud cover shading information than a cloudless sky working condition photiovoltaic power super short-term forecasting model.

TL;DR: In this article, an ultra-short period wind power prediction method based on a wind speed factor control model was proposed, which includes performing an ultra short period prediction according to an ARIMA (autoregressive integrated moving average) model; performing the ultra short-period power prediction using a BP (back propagation) neutral network model; and completing the ultrashort period power prediction based on the wind speed-factor control model.

TL;DR: In this paper, a regional ground surface irradiance distribution prediction method is proposed for determining minute-level ground surface radiance regional distribution prediction within future 1 hour, which is free from the dependence from a traditional method to the observation of the cloud base height, and improves calculation accuracy of cloud position and size at the absence of a ceilometer and the water level total irradiance prediction accuracy of a photovoltaic power station.

TL;DR: In this article, the authors proposed a prediction method of total wind electricity power facing to an area based on a radial basis function neural network (RBFNN) and estimated the output power predicted value of each represented wind power station.