Study On Dynamic Model And Parameter Identification Of Photovoltaic Grid-connected Inverter

In recent years,the international community attaches great importance to the problem of environmental pollution.Many countries are energetically developing photovoltaic(PV)power projects.Due to the randomness,intermittency and periodicity of the light resource,the input of the PV power station brings many problems to the grid-connected technology and the development plan of the grid.As the bridge connecting the PV system with the grid,the accuracy of PV grid-connected inverter model is directly related to the reliability of grid operation analysis of PV power stations.Based on the theory of identification modeling,this paper studies the problem about equivalent modeling and parameter identification of PV grid-connected inverter.Firstly,the mathematical model of each component of the PV system is introduced.We analysis how to obtain the inverter equivalent model and parameter values by system identification method,and decide to identify the PV grid-connected inverter model from two modeling ideas of "grey box" and "black box".Aiming at the "grey box" method,this paper identifies the internal and external loop parameters of the control system based on the traditional mathematical model of PV grid inverter system.According to the structural parameters of the actual PV power station,a simulation model of PV system is established through Simulink software.A PV grid-connected inverter identification method based on GPSO(Genetic Particle Swarm Optimization)algorithm is proposed.The parameters are identified synchronously by the "code-model" parameter transfer mode.Compared with GA and PSO algorithm,GPSO parameter optimization model has obvious superiority in the recognition precision and the convergence speed.Finally,the generalization ability of the model is evaluated.Simulation and test curves under three different disturbances are compared to verify the applicability and accuracy of the model.Aiming at the "black box" method,this paper reconstructs the equivalent model of PV grid inverter system,and proposes a dynamic model identification method for PV inverter based on recursive least squares(RLS).Without consideration of the topology structure of three phase PV inverter and its control system,their whole is regarded as a "black box",which can be equivalent to a dual input and multi output system through the analysis of the input and output,and then RLS method is used to identify the dynamic model and parameters on line.Based on the data sets of different typical weathers in summer and winter,the equivalent dynamic models of PV inverter are established.The error between the model output and the test data is small,which verifies the accuracy and applicability of the identification method.In addition,the low optimal order of the model also reduces the amount of memory occupying,and improves the speed of identification.