Monthly forecasting of electric energy consumption is important for planning the generation and distribution of power … waves were modeled separately by a grey model and radio basis function neural networks. Adding the forecasting values of … each model can yield the forecasting results for monthly electricity consumption. The grey model has a good capability for …

) network for forecasting LMPs in a day-ahead market. The PCA network extracts essential features from periodic information in … the market. These features serve as inputs to the MLF network for forecasting LMPs. The historical LMPs in the PJM market … are employed to test the proposed method. It is found that the proposed method is capable of forecasting day-ahead LMP …

-based energy demand forecasting model is proposed and appliedto forecast China's energy consumption until 2020. The energy demand …

Short-term solar irradiance forecasting (STSIF) is of great significance for the optimal operation and power …

This article analyzes the demand for electricity and provides out-of-sample forecasting at the sectoral level using a … one would expect if the forecasting relationship is stationary. The long-run parameter estimates are then used to conduct … ex-ante forecasting under plausible assumptions for policy making. …

A<b> </b>new short-term probabilistic forecasting method is proposed to predict the probability density function of the … effectiveness and advantages of the proposed forecasting method. …