The Research Of Dynamic Balance Adjustment In District Heating System Based On Heating Load Forecasting

Central heating energy-saving offers the highest potential of any energy-saving among our country building.In order to meet the heating demand of heat consumers as well as to make central heating system run in an efficient way,as the operating and control method has a direct impact on the overall operation of the pipe network.Therefore,making the operating and control strategies of pipe network system plays an important role in achieving economic operation of heating system.The control strategy of heating pipe network operation includes the method of forecasting the heat load of the heating pipe network,the adjustment method of the first-level pipeline network’ dynamic balance based on the change of the heat load of the secondary pipe network.This paper focuses on the design of heating pipe network control management platform,and completes the following research contents.In the aspect of thermal load forecasting,the current thermal load forecasting method is studied,and the method of predicting the heat load of pipe network is made by combining genetic algorithm and BP neural network method.In the forecasting process the average outdoor wind speed,the daily average outdoor temperature,date type,sunshine time,heat load in the early three days are used as input variables,the heat load of the testing day as the output variable.Through the prediction of specific examples,it is found that the result error of combining genetic algorithm and BP neural network is smaller than that of BP neural network method alone,and the thermal load can be predicted by the combined method in the allowable range.Which can guide the regulation and control of heating engineering.In the aspect of balace adjustment of the first-level pipeline network to meet the needs of the secondary pipe network,the control platform to change the "step" method,according to the basic principles of hydraulic pipe network,to achieve rapid adjustment of the whole network.Therefore,to study the lag of the hydraulic impact in the pipe network,the research object comes from the indirect connection heating network.A small secondary circuit heating network is built in the laboratory.The secondary pipe network heat exchanger inlet is installed with temperature,flow,pressure sensor,electric control valve.Regulating and data monitoring is executed by computer control platform.By adjusting the frequency of the pump,the valve opening to change the hydraulic parameters,while recording the inlet pressure and flow,the purpose is to study the dynamic response rule of the pressure and flow.The results showed that when the heat source pressure and flow changes,the pressure and the flow of each branch is not changed at the same time,lagging exist;when alternating valve opening of one branch,the other branch pressure does not change,lagging exist;the flow of other branch change simultaneously,there is no lagging.Through the analysis of the pressure and flow data collected by the actual heat pipe network,the pressure of each branch does not change at the same time if the pressure of the heat source variate,lagging is real.The lag time is related to the distance from the heat source.It is the same conclusion as the test network.Although the lag time has been obtained,the quantitative relationship between lag time and distance is not found.This paper gives guidance on heating supply by combining genetic algorithm and BP neural network to do load forecasting;in order to meet the regulation need of secondary circuit pipe,the passive regulation of primary heating pipe network is carried out by using GUI visual function in MATLAB software,the heating control management platform is also designed out,the main interface,active control interface,passive control interface are devised,and the button function are introduced.