Study On Parameter Identification And Control Method Of Hydraulic Turbine Governing System

Hydraulic turbine governing system plays an important role in regulating frequency and maintaining the balance between output power and the load power of hydroelectric units,and its regulating performance has a significant impact on the stable and efficient operation of hydroelectric units.However,the hydraulic turbine governing system is a complex control system.The system contains a large number of nonlinear factors,and its accurate model is difficult to describe,especially for the hydraulic turbine internal water flow field,whose model can not be established due to the complexness.most of the related researches adopt simplified linear model,which is difficult to reflect the real operation characteristics of the hydraulic turbine governing system,and also the use of the simplified linear model limits the research on its control methods.Therefore,it is necessary to study the identification method of hydraulic turbine Governing system,establish an accurate system model,and further study the advanced control method.In this paper,on the basis of the in-depth study of the nonlinear modeling and analysis of the hydraulic turbine governing system,the idea of parameter identification is adopted,and the system parameters of the hydraulic turbine governing system are identified by using the multi-population genetic algorithm.Taking PID parameter optimization as the key control parameters,the MaxLIPO+TR parameter optimization algorithm is introduced to improve the control performance of hydraulic turbine Governing system.The main research contents of this paper are as follows:(1)According to the model requirements of parameter identification and control method research of hydraulic turbine governing system,the principle of the hydraulic turbine governing system is analyzed,and the modelling analysis of the hydraulic turbine governing,electro-hydraulic servo system,pressure water diversion system,hydraulic turbine and generator and load modules are carried out.In order to solve the problem that it is difficult to describe the hydraulic turbine model,a neural network model is used to describe the characteristics of unit torque and unit flow,and a nonlinear model of hydraulic turbine is established by combining the related mechanism.Finally,the comprehensive model of hydraulic turbine Governing system is established,and the corresponding simulation model is established on Simulink.(2)Aiming at parameter identification of nonlinear model of hydraulic turbine governing system,multi-population genetic algorithm are adopted to build parameter identification structure based on multi-population genetic algorithm.By building fitness function,parameter identification problem is transformed into optimization problem aiming at fitness function.Through simulation experiments and optimization process analysis,the effectiveness of multi-population genetic algorithm in parameter identification of hydraulic turbine governing system is verified.(3)MaxLIPO+TR is introduced as the PID parameter optimization algorithm of hydraulic turbine governing system,and the PID parameter optimization structure based on MaxLIPO+TR is built.To solve the problem that the ITAE index could not fully reflect the PID parameter performance,the comprehensive ITAE index with penalty terms added is adopted as the objective function.Through simulation and comparison experiments,it is found that MaxLIPO+TR can complete PID parameter optimization in a relatively short time,and the optimization effect is good.