Forecasting Russian renewable, nuclear, and total energy consumption using improved nonlinear grey Bernoulli model

Forecasts of renewable, nuclear, and total primary energy consumption are essential for a green energy system and the understanding of climate change in a rapidly growing market such as Russia. In this paper, nonlinear grey Bernoulli with power j model (NGBMj) is applied to predict these three different types of energy consumption. A numerical iterative method to optimize the powers of NGBM using mathematical software is also proposed. The NGBM with optimal power model is named NGBMop. The forecasting ability of NGBMop has remarkably improved, comparing with the grey model. For each time series, the best NGBMop provides an accurate and reliable multi-step prediction with a MAPE value of less than 2.90 during the out-of-sample period of 2004-2009. The prediction results show that Russias compound annual renewable, nuclear, and total energy consumption growth rates are set respectively at 1.95%, 2.44%, and 0.88% between 2010 and 2015.