Parameter estimation of drive system in a fixed-speed wind turbine by utilising turbulence excitations

• Published in: IET generation, transmission & distribution Vol. 7; no. 7; pp. 665 - 673
• Main Authors: Pan, Xue-Ping, Ju, Ping, Wu, Feng, Jin, Yu-Qing
• Format: Journal Article
• Language: English
• Published: Stevenage The Institution of Engineering and Technology 01.07.2013; The Institution of Engineering & Technology
• Subjects: asynchronous generators; drive system parameter estimation; Dynamical systems; Dynamics; fixed speed wind turbine; Fluid dynamics; Fluid flow; induction generator dynamics; induction motor drives; Levenberg–Marquardt parameter estimation method; Parameter estimation; power system parameter estimation; sensitivity; sensitivity index; spectral content; Turbulence; turbulence excitation; Turbulent flow; turbulent wind; wind turbine generator; Wind turbines; fixed speed wind turbine; drive system parameter estimation; power system parameter estimation; asynchronous generators; induction motor drives; turbulence excitation; spectral content; Levenberg–Marquardt parameter estimation method; turbulence; turbulent wind; Levenberg–Marquardt parameter estimation method; induction generator dynamics; wind turbine generator; sensitivity; wind turbines; sensitivity index
• ISSN: 1751-8687; 1751-8695; 1751-8695
• DOI: 10.1049/iet-gtd.2012.0336

Wind speed varies continuously. The turbulent winds act as a constant low-level excitation to wind turbines. Assuming turbulence is stationary over an analysis window, the parameters of drive system in a fixed-speed wind turbine are estimated in this study. First, simulations are performed when the wind turbine generator is under turbulence excitations and the spectral contents of the response data show that the induction generator dynamics, which are much faster than the drive system transients, can be neglected in the estimation of drive system parameters. Second, the parameter identifiability of drive system is studied and a new sensitivity index is proposed to qualify the effects of individual parameter on the dynamics of the drive system. Finally, the Levenberg–Marquardt parameter estimation method is applied to identify drive system parameters. Estimation results show that most parameters estimated agree well with the actual values and the effectiveness of this parameter estimation method is validated.