Methods for systematic tuning of wind turbine controllers

Methods for systematic tuning of wind turbine controllers Automated methods for wind turbine controller tuning can be useful to obtain a rst estimation of the controller gains. Furthermore, these techniques can be employed within a multidisciplinary design procedure allowing for concurrent aeroservoelastic design. This report presents two methods to systematically tune the gains of the PI pitch controller of the Basic DTU Wind Energy Controller. The rst method is based on pole-placement technique and the second on fatigue loads reduction. Both methods require linear models of a wind turbine that are obtained with HAWCStab2. These techniques are solved with numerical optimization. The frequency placement method shows improvements compared to the state-of-the-art method but only when the model complexity is low. Tuning with load based method shows that different compromises between tower loads and rotor speed regulations can be achieved.

[1]  Lars Christian Henriksen,et al.  Investigation of the dependency of wind turbine loads on the simulation time , 2014 .

[2]  Joaquim R. R. A. Martins,et al.  pyOpt: a Python-based object-oriented framework for nonlinear constrained optimization , 2011, Structural and Multidisciplinary Optimization.

[3]  Justin S. Gray,et al.  OpenMDAO: Framework for Flexible Multidisciplinary Design, Analysis and Optimization Methods , 2012 .

[4]  Poul Ejnar Sørensen,et al.  Control design for a pitch-regulated, variable speed wind turbine , 2005 .

[5]  Morten Hartvig Hansen,et al.  Aeroelastic properties of backward swept blades , 2011 .

[6]  Frederik Zahle,et al.  Aero-Elastic Optimization of a 10 MW Wind Turbine , 2015 .

[7]  Lars Christian Henriksen,et al.  Basic DTU Wind Energy controller , 2013 .

[8]  Anders Yde,et al.  Light Rotor: The 10-MW reference wind turbine , 2012 .

[9]  Morten Hartvig Hansen,et al.  Open-loop frequency response analysis of a wind turbine using a high-order linear aeroelastic model , 2014 .

[10]  Christian Bak,et al.  Wind turbine fatigue damage evaluation based on a linear model and a spectral method , 2016 .

[11]  Christian Bak,et al.  Effects of gain-scheduling methods in a classical wind turbine controller on wind turbine aeroservoelastic modes and loads , 2014 .

[12]  Frederik Zahle,et al.  Aeroelastic Optimization of MW Wind Turbines , 2011 .

[13]  Michael A. Saunders,et al.  SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization , 2002, SIAM J. Optim..

[14]  Kenneth T. Moore,et al.  The Development of an Open Source Framework for Multidisciplinary Analysis and Optimization , 2008 .

[15]  Kenneth T. Moore,et al.  OpenMDAO: An Open Source Framework for Multidisciplinary Analysis and Optimization , 2010 .

[16]  Morten Hartvig Hansen,et al.  Aeroelastic stability analysis of wind turbines using an eigenvalue approach , 2004 .

[17]  Niels Kjølstad Poulsen,et al.  A simplified dynamic inflow model and its effect on the performance of free mean wind speed estimation , 2012 .