Control System In Urban Central Heating

Central heating,as the main way of heating in China,has been developed for many years,but there are still many problems:(1)due to the lag of heat change,the heating effect is unsatisfactory,and at the same time,energy waste is caused;(2)in the heating industry,although the determination of the heat supply refers to real-time weather conditions,the lack of reference variables and the lack of scientific adjustment methods make the adjustment of the heat supply not ideal;(3)at present,the automation degree and control precision of heating industry in China are relatively low,and the adjustment of heat supply mainly depends on manual experience.How to make the central heating system in the northern part of the country economic and environmental protection has become the primary goal of China’s heating industry.The research on short-term heat load forecasting can improve the control precision of heating system,optimize the control scheme of heating system,and realize the economic and environmental protection operation of the system.Since the indoor temperature of the hot user is greatly affected by the external environment temperature,the neural network modeling of the short-term heating load combined with the weather factor will make the prediction more accurate.The control of the flow in the heating network is the key link of the central heating system,which is directly related to the heat distribution and temperature regulation of the entire heating system.Different from the traditional heating system’s control method of adjusting the temperature of the primary network water supply and the temperature of the secondary network return water,the control method using flow as the control variable can achieve the heating network on-demand heating target and ensure the precise regulation and control of heat.Therefore,the article proposes a PSO-BP-PID controller to achieve precise control of heating system.Figure31,Table5,Reference 61...