Study On Simulation And Optimization Of Peak Shaving Scenarios For Gas Pipeline

As a kind of clean energy,natural gas has obtained the rapid growth in recent years.Although China's natural gas supply capacity continues to rise,but due to the consumption demand is growing fast,it is inevitably that there is imbalance problem.How to ensure smooth use of downstream users,is the focus of natural gas pipeline operations.This study is in this context put forward.In this paper,a single gray prediction model and artificial neural network prediction model are used to predict and analyze by using MATLAB programming.Based on the advantages of the two models,a combinated load forecasting method based on gray model and neural network is proposed,which is a residual correction type combination forecasting model.It is proved that the load pre measurement of the combined model is closest to the actual value.In addition,the basic data of the CD pipeline system has been collected,which used transient hydraulic simulation software SPS to construct the CD pipeline simulation,and the model ran successfully after the validity test and pressure check.Based on the results of gas load forecasting,this paper analyzes the gas consumption law of I city located in the downstream of CD pipeline gas reservoir,and obtains the lack of gas volume in the city of peak month and peak day,so as to simulate the peak shaving scenarios of gas pipelone.In view of whether the gas storage project is put into operation,the CD pipeline shall undertake the peaking operation for 72 hours on peak day of peak month of gas users at city I,than selected the scheme of the whole compressor opening scheme and the gas production scheme of the gas storage reservoir.As for the peak shaving scenarios for gas storage operation,putting forward two production principles of" gas production at the peak time " and " gas production stablely ",based on these two principles,three gas storage schemes for gas reserves are formulated respectively,each of them also developed two different boot programs.And then use SPS software to simulate each case,conducted a preliminary analysis.Three methods were used to evaluate the peak shaving scenarios separately including the gray correlation analysis method,the topsis method and the rank sum ratio method.The single method is combined by the combination method.In order to test whether a single evaluation model is rational,the spearman rank correlation coefficient method is used to test the model before and after integration,The top five peak shaving scenarios reflect the reliability of the combination evaluation.Finally,on the basis of the analysis,the optimization proposal of peak shaving is put forward.