A Novel Riccati Equation Grey Model And Its Application In Forecasting Clean Energy. (15th August 2020) - Luo, Xilin; Duan, Huiming; He, Leiyuhang
Abstract: Objective: and accurate prediction of clean energy can supply an important reference for governments to formulate social and economic development policies. This paper begins with the logistic equation which is the whitening equation of the Verhulst model, introduces the Riccati equation with constant coefficients to optimize the whitening equation, and establishes a grey prediction model (CCRGM(1, 1)) based on the Riccati equation. This model organically combines the characteristics of the grey model, and flexibly improves the modelling precision. Furthermore, the nonlinear term is optimized by the simulated annealing algorithm. To illustrate the validation of the new model, two kinds of clean energy consumption in the actual area are selected as the research objects. Compared with six other grey prediction models, CCRGM(1, 1) model has the highest accuracy in simulation and prediction. Finally, this model is used to predict the nuclear and hydroelectricity energy consumption in North America from 2019 to 2028. The results predict that nuclear energy consumption will keep rising in the next decade, while hydroelectricity energy consumption will rise to a peak and subsequently fall back, which offers important information for the governments of North America to formulate energy measures. Highlights: The novel grey Verhulst model CCRGM(1, 1) is proposed. The optimal nonlinear terms of the novel model are determined by simulated annealing algorithm. The comparative studies show that the new model is superior to the other six benchmark models. The nuclear and hydroelectricity energy consumptions of North America from 2019 to 2028 are projected.