Variable Flow Distributed Control System For City Central Heating

Central heating is one of the main infrastructures of modern cities. The installation of calorimeter, achieving household measurement, has become an inevitable trend of development for our urban central heating. Using computer technology and advanced control method, monitoring and controlling heating system, implementing variable flow operation, can overcome the shortcomings of poor quality, hot and cold inhomogeneous, wasted energy, unreasonable fees and management level backward in fixed flow heating system in past. Against(consider) the characteristics, of coupling, and lagging of variable flow heating system, secondary network temperature control programs and constant pressure point pressure control program are designed, and decoupling control is realized by using neural network.Although the static decoupling method is simple, easy to realize, the decoupling can not be made thoroughly which can make the system unsteady. According to the coupling relationship of temperature of water supply and return, a decoupling method that static decoupling combines with PID decoupling based on diagonal recurrent neural network (DRNN) is proposed. In the method, the intensity of coupling is reduced by using static decoupling and dynamic decoupling is realized by using PID decoupling based on DRNN, to overcome coupling of temperature of secondary water supply and return. Meanwhile, consider the defect of that parameter regulation is difficult and bad adaptive capacity for conventional PID controller, neural network PID controller based on DRNN is designed. DRNN network is regarded as online identification and can be adjusted the right value of the network automatically, to realize PID controller parameter adjustment online. Based on analysis of theories above, adopting the methods of static decoupling, conventional PID decoupling and neural network PID decoupling, MATLAB simulations are carried for mathematical model of heat exchanger established. MATLAB simulation results shows that using neural network PID decoupling control programs with static decoupling has performed dynamic approximate decoupled and static completely decoupled, with the quality of fast response and small overshoot. Furthermore, Using PCS-B process control system experimental device, experimental study has been done. The results show that neural network PID controller can improve quality of dynamic process and reduce static error in practical application. And the satisfactory effect can be reached.According to "centralized management, decentralized control" thought, urban central heating system adopts three-tier structure. And the program of heating station monitoring control system is designed, IPC is upper computer and PLC is subordinate computer based on MCGS configuration software platform in this program. In MCGS environment, main screen, neural network PID control screen, operation panel screen and data curve are designed for monitoring center in heating system. The application of this program would improve remarkably management level and economy benefit for heating enterprise.