Remote Monitoring And Load Forecasting System For Heat Pipe Network

Centralized heat supply system is an important urban infrastructure,which has the characteristics of complex pipeline network,numerous heat exchange stations and scattered heating areas.In order to ensure its stable and economic operation,heat pipe network monitoring is required,and the heat load is predicted in real time based on the monitored heat supply data,so that the heat supply can be adjusted in time.However,the current heat pipe network monitoring schemes are generally complicated in wiring,poor in expandability,easy to lose data from remotenodes,and low in accuracy of heat load prediction methods.The following research is conducted in this paper to address the above problems:(1)To address the problems of complicated wiring for heat pipe network monitoring,poor expandability and easy loss of data from remote nodes,a wireless monitoring terminal for heat pipe network,a wireless monitoring router for heat pipe network and a ZigBee-4G wireless gateway are designed.The terminal and router are used to set up a ZigBee wireless sensor network for data collection at the heat exchange stations in the heat pipe network,which can avoid wiring,reduce cost,improve real-time and facilitate the expansion of nodes and management.The use of gateways for remote node data forwarding can effectively solve the problem of data loss caused by poor signals from remote nodes such as heat inlets and key nodes of the pipe network at the user end.(2)In order to effectively manage the heat supply data monitored by the heat pipe network,a remote monitoring and load forecasting system with good human-computer interaction is designed as the upper computer software of the heat pipe network,referred to as the intelligent heat network data management system.The system is designed based on QT platform and uses MySQL for data management,which can realize many functions such as real-time monitoring of heat pipe network data,historical data viewing,data report exporting,historical curve drawing,fault warning,heat load prediction,heat load prediction model evaluation,and providing heat supply regulation suggestions and fault investigation reference.(3)In order to improve the accuracy of heat load prediction,a combined heat load prediction model based on GRU-ARIMA is constructed.The model not only has the advantages of the GRU model to handle multidimensional nonlinear time-series data and cope with sudden parameter changes,but also can effectively extract time-series features using the ARIMA model,which can greatly improve the prediction accuracy compared with the traditional single time-series analysis method and neural network model,and can achieve accurate heat load prediction and provide important references for heat supply regulation.(4)In order to verify the performance and communication reliability of the data acquisition device,the hardware test and multi-scene data acquisition test of the wireless monitoring device for heat pipe network were conducted.The multi-scenario data acquisition test includes point-topoint transmission test at the heat exchange station site,network acquisition test at the heat exchange station site,and data acquisition test at the remote terminal combined with the gateway.The data delay and packet loss rate obtained from the test can meet the demand for real-time and effective monitoring of heat pipe network,which has a large engineering application value.