Research On Prediction Model Of Energy Supply-Demand In China And Electric Energy Substitution Strategy

Energy is a key material basis for economic development and social progress and an important factor affecting human living environment.Energy sustainable development is an important issue that concerns the overall situation of national economic and social development in China.In China,energy resources are abundant,but per capita share is low,coal holds dominant position for long time,proportion of oil and gas and other high quality resources and clean energy is low,electrification level is not high,environmental pollution problem is increasingly serious,and degree of dependence upon importation of petroleum continues to rise.With the future of China's economic and social sustainable development,energy demand continues to go up,energy environment constraints and contradictions in China become increasingly prominent.Therefore,it is of great significance to scientifically and rationally predict energy supply in China for the formulation of energy policy and promotion of energy strategy in China.Energy system is a kind of nonlinear complex system.Traditional prediction methods such as scenario analysis(e.g.sector analysis,input-output method,etc.)and operational programming method(e.g.non-linear programming,multi-objective programming,mixed integer programming,etc.)are the common methods for government sector planning,but due to huge and complex model difficulty to obtain data.Others such as elastic coefficient method,trend analysis method,time series method,regression analysis method,etc.are all based on the linear prediction,with simple calculation method and clear economic meaning,but it may not consider multifactorial non-linear influence.Grey theory,artificial neural network method,genetic algorithm are emerging prediction methods,which are very suitable for non-linear,time-varying and uncertainty of the complex system of prediction;but because of economic and social data in the field with the ever-increasing trend,so the future value will exceed the maximum value of learning samples,resulting in long-term prediction accuracy is not enough.The system dynamic model is good at dealing with high-order,nonlinear and time-varying complex problems.The system dynamics model is a causal mechanism model,which makes its advantages in medium and long term energy forecasting increasingly apparent.However,the input parameters of the system dynamics model depend on the subjective judgment of the user,which often vary from person to person.Therefore,this paper uses the gray prediction optimization model to calculate the basic parameters required by the system dynamics model to overcome its shortcomings.In addition,the model also introduces the factors such as technological progress factor,energy saving and emission reduction as the constraint target,setting the benchmark and high-tech progress to explore the impact of technological progress on future energy demand,and analyze the key of China's energy transformation.In this paper,the gray theory and system dynamics are combined to establish the system dynamics model of China's energy supply and demand.The Vensim PLE software is used to simulate the energy demand in China from 2016 to 2035 focusing the impact of technology on the system,and provide a reference for the government to develop relevant policies.