A novel Hausdorff fractional NGMC(p,n) prediction model and its applications in forecasting energy production and conversion of China

Abstract This work proposes a novel Hausdorff fractional NGMC(p,n) prediction model based on the NGMC(1,n) model. The new model combines the Hausdorff fractional accumulation operator and the Grunwald-Letnikov fractional derivative with more freedom and simpler in calculations; the time response function and recurrence expressions of the new model are deduced by using forward difference; the recurrence relation of the binomial in the discrete solution to avoid calculating the Gamma function and simplifies the calculation; the Grey Wolf Optimizer (GWO) is introduced to optimize parameters of the new model for improving adaptability. To verify the efficiency of the new model, nine existing grey models are used to predict the total renewable energy production, the energy conversion efficiency and the total electricity production of China. The experimental results show that the fitting accuracy and prediction accuracy of the new model are better than those of the other nine existing models.