Journal of System Simulation ›› 2022, Vol. 34 ›› Issue (12): 2546-2556.doi: 10.16182/j.issn1004731x.joss.22-FZ0928

• Modeling Theory and Methodology • Previous Articles     Next Articles

Low Voltage Ride-through Modeling for Wind Turbines Based on Neural ODEs

Qiping Lai(), Tannan Xiao, Dongsheng Li, Chen Shen()   

  1. Department of Electrical Engineering, Tsinghua University, Beijing 100084, China
  • Received:2022-08-07 Revised:2022-09-21 Online:2022-12-31 Published:2022-12-21
  • Contact: Chen Shen E-mail:lqp22@mails.tsinghua.edu.cn;shenchen@mail.tsinghua.edu.cn

Abstract:

Considering the difficulty of equivalent modeling of low voltage ride-through(LVRT) characteristics of a wind farm, a neural ordinary differential equation(ODE)-based wind farm LVRT modeling methodis proposed. The input of the model is the voltage and wind speed of each wind turbine at the grid connection point of wind farm, and the output is the current at the grid connection point. The model can better characterize the strong nonlinear switching process and describe LVRT characteristics of wind farms under different wind speed scenarios. A simulation example of a wind farm including three doubly-fed induction generators(DFIGs) is established on CloudPSS simulation platform to test the proposed method. The test results verify the generalization ability and effectiveness of Neural ODEs model.

Key words: DFIGs(doubly-fed induction generators), CloudPSS simulation, LVRT(low voltage ride-through) characteristics, Neural ODEs(ordinary differential equation), data-driven modeling

CLC Number: