Research On Control And Simulink Based PID Neural Network To District Heating Networks Running

At present, China’s District heating enterprise network adjustment method commonly used in thermal regulation for the quality, but the quality of the individual energy greater regulation can not quickly satisfy user requirements with heat. Numerous studies have found that the quality of regulation can not meet the quality requirements of the current heating [1-2]. As the quality of the thermal transfer mode network and enables effective control of thermal equilibrium heating network, to heating needs to be widely used in the userd. However, the heat transfer station heating process quality and volume control to adjust coupling exists between the impact of control. Therefore, how to research and development of efficient control algorithm to optimize heat transfer stations moderating effect is already heating enterprises need to solve the problem. Paper to construct a particle swarm optimization (Particle Swarm Optimization, PSO) of PID Neural Network decoupling controller, to be apply to the heat exchanger stations and adjust the heating process quality control, decoupling,thus improving the heat supply network thermal quality control. Adjust heat exchanger stations establish mathematic model of the process of adjusting the amount of quality adjustment.Firstly, the mechanism modeling method to determine transfer stations heating process quality, quantity and adjust the form and order of the system model. Then, through the identification step response curve and the least squares method of heating process model parameters heat transfer stations, the ascertainment of a static part of the heating process model. Heat stations of process quality, quantity and tune the system model includes a main channel and a dynamic model coupled channel model. Then, Construction of PID Neural Network decoupling controller for achieving quality heat transfer stations, provoke the volume of process control.Designed on the basis of a mathematical model of decoupling controller, we use PID Neural Network decoupling controller, and the use of intelligent PSO arithmetic PID Neural Network were optimized. Matlab platform were validated PID Neural Network decoupling controller, PSO optimized PID controller neural network decoupling effect on the thermal heating process heat transfer station network. Co-simulation FlowmasterV7with Matlab/Simulink. On FlowmasterV7fluid software simulation to build a network close to the actual operating conditions of the heat exchanger station heating process model, the above PSO majorization PID neural network decoupling controller simulation, closer to the actual system conditions control effect.The simulation results verify heat exchange station the process of quality adjustment, volume regulation of the mathematics model and PSO optimization PID neural network controller is effective to the qualitative regulation, volume control adjustment of heating process of heat supply network, the hydraulic condition and thermal condition regulation has certain guiding significance.