Study On Modeling And Controlling Of The Superheated Steam Temperature Of A 300 MW Circulating Fluidized Bed Boiler

Circulating Fluidized Bed (CFB) technology is a kind of highly active and low pollution combustion technology which is developing rapidly and favored by kinds of industrial fields. CFB boiler technology has been widely used in power generation, industrial boilers and waste treatment and utilization. Its capacity leads to enlarge and its parameters get high. However, due to the relatively complex structure of the CFB boiler, the thermal inertia of its superheated steam temperature system is large. In order to ensure the stable operation and rapid response of the superheated steam temperature system, higher control requirements are needed. So, the paper has studied on building models and controlling rules of a 300MW CFB boiler superheated steam temperature system in detail.In order to research the dynamic performance of the CFB boiler superheated steam temperature overall, a mechanism model and a test model have been established. The mechanism model is built on APROS simulation platform which contains low temperature superheater, mid-temperature superheater and high temperature superheater. While the test model is built on Matlab software under the load of 285MW,225MW and 150MW, the transfer functions between the inlet and outlet steam temperature of the high temperature superheater and desuperheating water flow are identified respectively by particle swarm optimization (PSO) algorithm. The results show that both the models are good at accuracy.The models show that the superheated steam temperature system of CFB boiler has large inertia and high degree of nonlinear. It is difficult to achieve the ideal control goal only by the conventional cascade PID control. So for the sake of improving the dynamic characteristic of the superheated steam temperature control system, the fuzzy logic controller is used to tune PID parameters. The proportional factor and quantization factor of fuzzy-PID controller is optimized by differential evolution and local unimodal sampling (DE-LUS) algorithm. This optimization algorithm is good at global search and has high computational efficiency. The optimized fuzzy-PID controller and conventional PID controller are applied to control superheated steam temperature system respectively, and the simulation results show that fuzzy-PID controller is superior to conventional PID controller on the aspects of the response speed and anti-interference. However, the control precision of the fuzzy-PID controller is not satisfied when the system error is reduced. Therefore, a variable universe theory is introduced. The scaling factor can adjust the fuzzy rules dynamically to make up for the deficiency of the fuzzy-PID controller. The quantization factor, proportional factor and scaling factor of the variable universe fuzzy-PID controller are optimized by the DE-LUS optimization algorithm, and the optimized controller is used for controlling superheated steam temperature system. The simulation results show that compared with the fuzzy-PID controller, the variable universe fuzzy-PID controller can reduce the overshoot of the superheated steam temperature. It's helpful to greatly improve the control performance of the fuzzy-PID controller and also significant to the stable operation of actual power plant superheated steam temperature system.