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 (NGBM j ) 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 NGBM op . The forecasting ability of NGBM op has remarkably improved, comparing with the grey model. For each time series, the best NGBM op 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 Russia’s 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.