Empirical Study On China's Energy Consumption Forecasting Model

Energy which is an important material resources related to the national economy and national security,is any form of economic activity and energy consumption of technological progress necessities,plays an important role in the modernization construction.With the rapid development of national economy,many challenges facing the energy sector,changed its consumption and production structure.That energy demand will continue to grow,the scientific analysis the status quo of China's energy consumption,grasp of China's total energy consumption trends,analysis of the current policy and formulate proper energy development planning,implementation and strategy to promote the rapid development of China's national economy,plays an important role in the construction of a conservation oriented society.Forecasting is important for the effective implementation of energy policies.Forecasting plays an important role in the Department of Energy's ability to guide energy policy in taking the necessary actions.The combined model based on vector autoregressive model and neural network model proposed in this paper can effectively predict the total energy consumption in China.The combined model based on vector autoregressive model and neural network model proposed in the article can effectively predict China's total energy consumption.The energy consumption model is based on the historical data of energy consumption,economic level,population size,energy intensity,energy structure,and industrial structure from 1980 to 2016,and forecasts China's total energy consumption from 2017 to 2020.By comparing the models,the relative error of the predicted energy consumption of the combined model and the RMSE are less than the results of two single forecasting models.This model can be used as a reliable tool for forecasting energy consumption in China in the next few decades.Finally,the model is used to forecast China's energy consumption.The total energy consumption in 2020 will reach 52.7 billion tons of standard coal.