Research On Statistical Monitoring And Prediction Model Of Regional Transportation Energy Consumption

In recent years,environmental protection,energy conservation and emission reduction have gradually become a hot issue of concern.As a key industry of energy consumption,transportation industry has many characteristics such as energy sources and large scale.Chinese governments have also vigorously carried out green transportation work,and gradually put energy consumption verification into the key works of government.The traditional energy consumption statistical methods start from the energy caliber,does not take the actual consumption of transport vehicles into account,and there is a widespread distortion of energy consumption data.Based on this situation,this paper studies the statistical monitoring and prediction model of regional transportation energy consumption.Liaoning Province was taken as an example to carry out the research.The regional water and land transportation energy consumption statistical and monitoring scheme was put forward in this paper.After field investigation,the energy consumption statistics table was drawn up,the method and frequency of energy consumption statistical monitoring were determined,5888 statistical samples are selected for statistical analysis,and 339 of them are monitored in real time.Statistical and monitoring results show that the monitoring data in the field of bus and freighter are 8.43% and 10.87% lower than the statistical data,and the monitoring data in the field of truck and coach are 5.93% and 4.43% higher than the statistical data.Further analysis shows that the monitoring data of total energy consumption is 1.97% higher than the statistical data,and the statistical data of energy consumption should be revised.In addition,a prediction model of regional transportation energy consumption has been put forward based on the seven factors affecting energy consumption,such as permanent resident population,per capita GDP,urbanization rate,car ownership,net load weight of ship,transportation turnover and energy utilization efficiency coefficient,and the sensitivity coefficients of these seven indicators were proposed as 1.213,0.036,0.535,0.065,0.075,0.044 and-0.036,respectively.Verification results of the prediction model show that the maximum error of the prediction model is 5.8%,and the average error is only 2.59%,which means the model is highly correlated with datas.Besises,a correction coefficient was proposed to modify the prediction model,and the regional transportation energy consumption prediction model based on monitoring data were obtained,compared with the original model,the revised model can reflect the real energy consumption of transportation industry.Finally,the fitting data of seven energy consumption factors from 2018 to 2030 was carried to forecast the energy consumption of transportation industry in Liaoning Province.The results show that the total energy consumption increases first and then decreases,and reaches its peak in 2020,the main reason is the population change and the improvement of energy utilization efficiency.Overall,through the analysis of the existing energy consumption statistical methods and actual monitoring results,a regional transportation energy consumption prediction model based on statistical data was established,a correction coefficient was proposed to modify the energy consumption prediction model,which is helpful to obtain the energy consumption prediction model based on monitoring data.The total energy consumption of Liaoning transportation industry in 2018-2030 has been forecasted as well.The research findings can provide guidance and reference for energy consumption statistics and prediction of transportation industry in other areas.