Research On Optimization Of Energy Consumption Structure Of Sichuan Province Under Carbon Reduction

With the economic new normal,the energy revolution is becoming green and low-carbon which promoted the establishment of a clean,efficient and safe energy modernization system.As an energy-consuming province in Sichuan Province,the objective facts of coal as a major energy-consumption product have not yet been changed,and the resulting pollution gas produced poses greater pressure on energy conservation and emission reduction.In order to achieve the target of reducing emission in the "13th Five-Year" energy development planning of Sichuan Province,it is necessary to adjust energy consumption structure according to local conditions,introduce clean energy technology and formulate relevant measures to reduce environmental pollution.Therefore,the optimization of regional energy consumption structure is of great significance to the development of low carbon economy in Sichuan.This paper first analyzes the basic situation of energy consumption structure and energy carbon emission in Sichuan Province,and expounds ten factors affecting energy consumption.Through the establishment of BP neural network model of principal component analysis,the energy consumption,total energy consumption and total carbon discharge are predicted for 2017-2020 years.Secondly,carbon dioxide emissions are discharged.Secondly,the external environmental cost of carbon dioxide emission,energy consumption cost and environmental pollution control cost are used as the objective function of energy consumption structure optimization.The total energy consumption and carbon emissions in 2020 are considered as constraints of energy consumption structure optimization,and the multi-objective optimization model of the energy of carbon emission reduction consumption structure in Sichuan province is established.Finally,based on the design of the optimization model,three different schemes are planned,and the energy consumption structure of three different schemes in 2020 in Sichuan province is tested by particle swarm optimization,and some countermeasures and suggestions are put forward in the future.including structural transformation?energy saving technology?policy making and organization protection.The main conclusions of this study are as follows:(1)according to the current situation analysis,the current energy development trend in Sichuan can not meet the established energy conservation and emission reduction targets,its main performance is that coal resources consumption still accounts for 1/2 of total energy consumption and the highest carbon emissions from coal consumption in all kinds of energy in all kinds of energy.The overall industrial structure shows "231" pattern,Energy consumption is mainly distributed in industry and construction industry,and the low energy efficiency of industrial energy will have a great impact on the environment.Therefore,solving the problem of carbon emission reduction according to local conditions is an important measure to optimize and upgrade the regional energy consumption structure.(2)Through the principal component analysis,two important factors of economic growth and industrial structure are obtained,and the neural network prediction model with high fitting degree is set up.The detailed data of total energy consumption,energy consumption structure and total carbon emission of Sichuan province for 2017-2020 years are successfully predicted.According to the prediction results of energy consumption in 2017-2020 years,we can konw that the proportion of coal consumption in energy consumption structure continues to decline,and the proportion of oil,natural gas and electricity consumption is increasing gradually,which shows that the energy consumption structure in Sichuan is still changing.(3)the forecast results of Sichuan's energy consumption structure and total amount in 2020 were in line with the expected requirements of the 13 th Five-Year plan.Therefore,the prediction samples of the total energy consumption in 2020 are 187 million 16 thousand and 900 tons of standard coal and the total amount of carbon emission is 80 million 501 thousand tons as the constraint conditions for the multi-objective optimization and do the preparatory work for the following optimization.(4)The optimization results of energy consumption structure show that the proportion of clean energy still has much room for improvement.This paper establishes an optimization model of energy consumption structure in Sichuan province.Through particle swarm optimization(PSO),the results of energy saving priority,emission reduction priority and energy saving and emission reduction are obtained with three different weights.In the comprehensive optimization scheme of energy saving and emission reduction,the proportion of electric power consumption is 35%,which is 10.58% higher than the forecast value,and the optimization result of the comprehensive energy saving and emission reduction scheme C is better than the energy saving scheme and the emission reduction scheme.Therefore,the energy saving and emission reduction plan of the three optimization schemes is more suitable for the development of energy and low carbon economy in Sichuan.