Forecasting annual electricity consumption in China by employing a conformable fractional grey model in opposite direction. (1st July 2020) - Xie, Wanli; Wu, Wen-Ze; Liu, Chong; Zhao, Jingjie
Abstract: Electric power makes a significant contribution to economic development. Predicting annual electricity consumption is becoming increasingly crucial for electric power utility planning and economic development. To address this problem, a novel conformable fractional grey model in opposite direction is presented to predict annual electricity consumption in China. Firstly, the computational formulas for the novel model are deduced by grey modelling method and the effectiveness of the novel model is proved by matrix perturbation theory. Secondly, the optimal parameters are determined by quantum inspired evolutionary algorithm. Thirdly, two empirical examples are taken to validate the prediction accuracy of the novel model. Finally, the proposed model is applied to predict electricity consumption of Beijing, Fujian and Shandong. The results show that the novel model is superior to other six competitive models. Besides, electricity consumption of these regions in next five years are predicted, which can well serve a benchmark research and provide a relatively reliable reference for economic and electric sectors. Highlights: A novel conformable fractional grey model in opposite direction is proposed. The optimal paramters of the novel model are determined by QIEA. The novel model is applied to predict electricity consumption in China.