The Research About Heat Load Forecasting And Control Strategy

In this paper, the overall structure of the heating system is analyzed in detail. Inthe heating control system, heat source and heating central played different roles, sogiven them different control strategies.The heat source, is responsible for the provision of heat, heat givenwhether reasonable determines the heating quality of whole heating system, but alsocan decide whether the system is energy saving system, in order to eliminate thesystem time delay, the difference between predict time and the current time is greaterthan the lag time of the system; The heat supply side, is responsible for heatdistribution to the heat users, the goal is ensure the quality of each user heating arethe same, make flow distribution more reasonable and make heat user heatingquality reaches equilibrium through the adjustment of valve. Cooperate with thebetter, given the more reasonable, the system will more energy-saving.Based on BP neural network algorithm, predict the outdoor temperature changesof Yingkou, find out the reasonable heat index, and then to predict thermal load.According to the analysis on the prediction results, this algorithm can achieve betterprediction effect. On the basis of the knowledge of fluid mechanics to establish flowand valve opening relationship model, traffic is influenced by many factors, such asthe diameter, length.In this paper, based on the control idea and the model, write the centralizedscheduling software control software. To monitor the whole network controlcenter in Yingkou, acquisition and monitoring data on the basis of the control thoughtrealized the load forecasting and the heating balance, in the actual application hasachieved good control effect, and achieved the energy saving.