Research On Parameter Identification Of Variable Pitch Wind Turbine System Based On Particle Swarm Optimization With Least Squares Optimization

Great changes have taken place in global energy development in recent years.Clean energy also needs to accelerate its own pace of development.The development of renewable energy is the main way to achieve sustainable access to clean energy.Wind power generation is an important form of the renewable energy.Wind power generator is an indispensable equipment in the process of wind energy conversion.Therefore,it is of great significance to study the wind turbines.In the development of wind power technology,variable pitch wind turbines have been widely used in the field of wind turbines with the advantages of system stability,convenient shutdown,safety and efficiency.In order to study the variable pitch wind turbine with constant power control,it is particularly important to identify the parameters of the variable pitch wind turbine and obtain the model parameters with high accuracy.Based on the simulation platform of MATLAB,this thesis focuses on the parameter identification of three subsystems of the variable pitch wind turbine.Firstly,according to the integral structure and working performance of each component of the variable pitch wind turbine,the mathematical model of the subsystems to which the parameters to be identified belong is established.In the wind energy conversion module,according to the principle of aerodynamics,the energy conversion mode of the variable pitch wind turbine system is analyzed,and the mathematical model is established.In the process of establishing the transmission system,two mass blocks and dynamic resistance torque model are used,and the relationship between the system and the generator is analyzed.The control module adopts hydraulic propeller actuator based on valve-controlled cylinder.Because of the strong nonlinearity of the system,the feedback linearization of the system is carried out,and the whole model is verified by simulation.Then,the identification strategy and algorithm of variable pitch wind turbines are studied in this thesis.Due to the complexity of the variable pitch wind turbine system,the large number of parameters and the high order of parameters,it is difficult to identify the overall parameters with high accuracy.In order to solve this problem,the whole identification strategy based on particle swarm optimization and subsystem as the basic unit is determined in this thesis.Because of the large identification error of particle swarmoptimization,quantum particle swarm optimization is used to identify the parameters.However,there are still some problems of large error in parameter identification,so the least square method is used to roughly estimate the identified parameters to solve the problem of too large particle swarm search boundary.In order to verify the identification accuracy of the algorithm,the performance of the algorithm is tested,and then the parameters are identified based on the variable pitch wind turbine.Finally,in order to verify the identification effect,the whole model is reconstructed by combining the identification results of each subsystem.Then the reconstructed model is compared with the original model in the same external environment to verify the overall rationality of the reconstructed model based on the identification results.Then the environment of the model is replaced,and the reconstructed model based on the identification results of particle swarm optimization and its derivatives is used as a reference to compare the simulation results.The effectiveness of the algorithm is verified as a whole.