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Analysis Of Coordinated Control System For Supercritical Power Generator Set And Research On Predictive Control Strategy

Posted on:2016-01-03Degree:MasterType:Thesis
Country:ChinaCandidate:W ZhuangFull Text:PDF
GTID:2272330464951081Subject:Power Engineering and Engineering Thermophysics
Abstract/Summary:PDF Full Text Request
In the 21st century, China’s new thermal power unit control engineering has entered the stage of ultra (ultra) critical parameters, large units. And the boiler-turbine coordinated control strategy of generator unit is about to become tougher. The design of PID control which boiler and turbine are adjusted respectively has gradually shown its limitation, so it is necessary to design a kind of new control strategy that can overcome the differences of response speed between the boiler and steam turbine effectively, and can also handle multi input multiple output, nonlinear controlled objects. At first, this paper analyzes the characteristics of the coordinated control system of power plant in general, and proposes a three input-three output model based on the coordinated control system, and then obtain specific parameters of the transfer function mode based on the coordinated control system by collecting the historical data of the running power plant combined with identification toolbox of MATLAB. Finally, we design the strategy of generalized predictive control of the nonlinear coupling system based on the boiler-turbine control system of supercritical power generator set. And then conduct system modeling and Simulation of control system in Matlab/Simulink and MPC toolbox, compare the control effect of GPC with the traditional PID control algorithm. The simulation results show that the main steam pressure and intermediate point temperature’s overshoot is less than the PID control, and the response time is faster than the traditional coordination control system based on PID, when the unit changes its load.
Keywords/Search Tags:Supercritical Power Generator Set, PID control, model identification, model predictive control
PDF Full Text Request
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