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The Model Identification And Parameters Optimization Of Turbine Governing System Based On MATLAB

Posted on:2016-11-07Degree:MasterType:Thesis
Country:ChinaCandidate:K J YongFull Text:PDF
GTID:2272330482478144Subject:Power Engineering
Abstract/Summary:PDF Full Text Request
In today’s world, energy structure is changing, people’s increasing demand for energy. Load changes will directly lead to unstable system frequency and affect the quality of supply. The basic task of the turbine regulation system is adjusted according to changes in the load turbine speed, adjust the active power output in order to maintain the unit within the range of frequencies in the prescribed study laws governing the operation of turbine regulation system, improve the performance of its control, it has been in the field of hydropower extremely important issues.The first issue of this paper is to study turbine regulating system controlled object model identification. In this paper, based on the analysis and study of the structural characteristics of hydraulic turbine regulation system, build a turbine regulation system controlled object of the simulation model in MATLAB Simulink platform,and the transfer function of the controlled object model use MATLAB least square method Hydraulic Turbine Regulation System Identification Toolbox.In addition, to improve the control performance of the system, The model was subjected to the above-mentioned identification governor parameter optimization, through the preparation of PSO algorithm m documents. In electro-hydraulic servo system, water systems, generators and loads Governor PID parameter optimization as controlled object, Optimization of the system step response output before and after adjusting system parameters by comparing the turbine governor found that Control performance optimized turbine regulating system, such as overshoot, settling time and rise time have improved, Control performance turbine regulation system has been improved.
Keywords/Search Tags:turbine, least square method, PID control, particle swarm optimization
PDF Full Text Request
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