Research On Intelligent Identification Method Of Model Parameters Of Direct Drive Power Generation System

As the scale of wind power grid-connected increases year by year,the direct-drive power generation system is increasingly used in wind farms due to its high system efficiency and low maintenance costs,whether the model and parameters of direct drive power generation system are accurate or not is related to the reliability of power system simulation calculation,and then affects the planning and design of wind farm,dispatching operation,power grid security and other links.Therefore,accurate direct-drive power generation system model and parameter intelligent identification research has important theoretical and practical value for the large-scale connection of direct-drive wind turbines to the power system.The methods of intelligent parameter identification of the steady-state model of direct drive power generation system and the low-voltage ride through model of direct drive power generation system considering transient recovery are proposed,which can identify the model parameters stably and accurately.The effectiveness of the proposed method is verified by simulation.Firstly,aiming at the adverse effect of the random characteristics of wind farm on the steady-state model parameter identification accuracy of direct drive power generation system,this paper proposes a model parameter identification method of direct drive power generation system considering the influence of wind speed characteristics,which effectively solves the problems of low identification accuracy and poor identification stability caused by the random fluctuation of wind speed.Specifically,the mathematical model is established through the dynamic characteristics of the direct drive power generation system.According to the influence of the random characteristics of the wind farm on the sensitivity value of the steady-state model parameters of the direct drive power generation system,the variation law of the random characteristics of the wind farm on the sensitivity value of the model parameters of the direct drive power generation system is constructed,and the mapping relationship between the control parameters and the random characteristics of the wind farm is established,On this basis,the high-precision identification results of the direct drive power generation system model under each wind speed model are obtained by using the wind speed characteristic identification method,so as to improve the comprehensiveness of the algorithm.Secondly,aiming at the coupling problem between Low Voltage Ride Through（LVRT）parameters and steady-state model parameters,a decoupling identification method for Low Voltage Ride Through（LVRT）model parameters of direct drive power generation system considering recovery of transient process was proposed.This method can effectively improve the identification accuracy of low voltage ride through model parameters of direct-drive generation system.Taking the direct drive power generation system as the research object,this paper establishes the steady-state model of the direct drive power generation system and the low-voltage ride through model of the direct drive power generation system with transient recovery process,and puts forward the intelligent identification method of the steady-state model of the direct drive power generation system and the low-voltage ride through model parameters of the direct drive power generation system considering transient recovery,which can identify the model parameters more stably and accurately.The effectiveness of the method proposed in this paper is verified by simulation.Finally,aiming at the problems of heavy tasks and lack of visual simulation tools in the process of model parameter identification of direct drive power generation system,this paper uses Matlab GUI to build a visual platform for model parameter identification of direct drive power generation system.The corresponding callback function is written to realize the corresponding functions and create a graphical interface.It can identify the model parameters only by importing the input and output data and calling the direct drive power generation system model,so as to effectively improve the efficiency of model parameter identification of direct drive power generation system.