查看文章

Energy consumption is an international issue and plays an important role in the national energy security, especially for China of which the energy market is in transition. Accuracy and trustable forecasting of future energy consumption trends with nonlinear data sequences is very important for the decision makers of governments and energy companies. In this paper, a novel nonlinear grey Bernoulli model with fractional order accumulation, abbreviated as FANGBM(1,1) model, is proposed to forecast short-term renewable energy consumption of China during the 13th Five-Year Plan (2016–2020). The new model is discussed in details with the fractional accumulated generating matrix and the Bernoulli equation. Further, the Particle Swarm Optimization algorithm is used to search optimal system parameters. Based on the updated real-world data sets from 2011 to 2015, the FANGBM(1,1) model is established to …