Research Of Intelligent Building Heat Supply Energy-saving Control Systerm

Building is one of the most important areas of reducing greenhouse gasemissions by conserving energy and dealing with climate change. With large powerconsuming and low efficiency, in order to implement national policies ofenergy-saving and carbon emission depressed, it is very important to study theenergy-saving in heating supply system. As we know, the key to carry outenergy-saving is load forecasting, so heat load forecasting methods were researchedand monitor and control system to save energy was developed in this paper.Based on the analysis of the heat supply energy-saving actuality in domesticand overseas, control scheme for heat supply energy-saving was presented,including the selection of control strategy, development platform, and finallyoverall plan was determined.The field running database acquisition is the foundation of heat loadforecasting, so we first collected raw data related to heat load forecasting in heatsupply system, and then we made data processing. Based on the characteristics ofnonlinearity, nonlinear methods including Artificial Neural Network and SupportVector Machine were applied to heat load forecasting in order to obtain effectivemethod.On the basis of the determined control scheme, the energy-saving monitoringdevice and the central monitoring software were designed. In particular, theenergy-saving monitoring device was designed, including the control partimplemented by PLC hardware configuration and software design, theman-computer interaction part implemented by touch screen hardware configurationand software design, the communication part implemented by the GPRS hardwareand software configuration and network integration. For the design of centralmonitoring software, including functions analysis and planning, softwaredevelopment platform were determined, respectively. Finally, according to thefunctions plan, central monitoring software was designed by using configurationsoftware.