Research Of Heating Boiler Centralized Control System

The boiler concentrated optimization control system is mostly used for keeping the heating effect good, and changing the way that single boiler independently operating mode. This system makes several boilers centralized controlled by computer, and optimizes the load ratio according to the real-time to reduce the waste of energy consumption. Comparing with the tradicional coal boilers and fuel boilers, electrothermal boilers are more beneficial to the environment and the economy. So building a boiler concentrated optimization control system has significant social benefits and economic benefits.In this paper, based on the in-depth analysis and research on the working principle, the process characteristics and the technical requirements, we design a concentrated optimization control system which contains three sets of electrothermal boilers by using PLC and frequency conversion technology. This system uses a running method which devides the outdoor tempreture into several stages. When the outdoor tempreture is high, the system reduces the flow. And when the outdoor tempreture is low, the system increases the flow. When the outdoor tempreture stays in the same stage, the system keeps the flow unchanged, and adjusts the water tempreture. This method not only suits the needs of the users, and also saves the energy.We do research on the controlling the water tempreture on the boiler concentrated optimization control system experimental platform in the lab. According to the data of the output sequence of the water temperture under the step response, we can get a mathematical model by using the least square offline system identification method. Then based on the in-depth research on the BP (Back propagation) neural network PID control algorithm, we improve this algorithm because of the weakness that Easy generation oscillation and slow convergence speed. And then apply this algorithm to the water temperature control of the boiler concentrated optimization control system. The simulation results prove that the control accuracy is high, the system response is fast and the stability is good by using this algorithm.