With the development of wind power research, the factors considered in the simulation model are gradually increasing. The demand for wind turbine models that take into account both electrical and mechanical characteristics is increasing, thus promoting the development and application of co-simulation technology. However, the detailed electrical model has strict requirements on the simulation time step, which reduces the efficiency of co-simulation. Some scholars have properly simplified the electrical model to improve the simulation speed when carrying out co-simulation. But, improper selection of simulation time step has a negative impact on simulation accuracy. Therefore, this paper studies the model optimization and step size selection to solve the problem of the contradiction between simulation accuracy and speed.
First, the complex electrical model is optimized by ignoring the power electronic switching model and reducing the order of the higher-order model, so that the computational complexity is reduced and the application range of the simulation step size is increased. GH Bladed and Matlab/Simulink are selected to build the co-simulation platform. Then, a comprehensive evaluation method based on residual similarity and feature selection verification is proposed, which takes into account simulation accuracy and speed. The evaluation of simulation accuracy is divided into two aspects: global and transient difference. The comprehensive evaluation index is formed by combining the evaluation index of simulation accuracy and simulation speed in a weighted way to guide the selection of simulation time step. Finally, the co-simulation is carried out to verify the effect of the optimization model on the simulation efficiency under the conditions of wind speed disturbance, frequency disturbance and fault crossing disturbance. According to the simulation results and the comprehensive evaluation method, the reference suggestions for the selection of simulation step size are put forward.
Through simulation results and analysis, the following conclusions are drawn: (1) Through the optimized model, the co-simulation model can be run at a larger simulation time step, and the co-simulation efficiency is improved. (2) According to the proposed comprehensive evaluation method, the simulation results are evaluated from two dimensions of simulation accuracy and speed, which solves the problem of quantitative evaluation of the accuracy and speed of the model simulation results. (3) Through the co-simulation of various working conditions and the quantitative evaluation of simulation accuracy and speed, the following conclusions are drawn: Under the background of the simulation in this paper, under the condition of wind speed fluctuation, the simulation time step of co-simulation is chosen to be around 0.05 s; under the condition of frequency disturbance, the simulation time step of co-simulation is chosen to be around 0.01 s; under the condition of fault ride-through disturbance, the simulation time step of co-simulation is chosen to be around 0.005 s. (4) Based on the evaluation results of multi-condition simulation, the factors such as time scale of simulation condition and mutation characteristics of observed parameters should be fully considered in the selection of simulation time step. When the time scale is large and the observed parameters do not have mutation characteristics, the larger simulation time step can be selected. When the time scale is small and the observed parameters have mutation characteristics, the selection of simulation time step should be reduced appropriately.