Individual pitch controller based on fuzzy logic control for wind turbine load mitigation

With the increasing size of modern large wind turbine (WT), the effects of dynamic loading on the structures become an important influence factor. There are mitigation measures for WT control systems to reduce these imbalance structural loads and regulate power. It has motivated the development of blade individual pitch control (IPC) methodologies. This study focuses on the design of fuzzy logic controller (FLC) for IPC. The controllers are designed in order to optimise a trade-off among several control objectives such as blade root moment and generator torque. Three different FLC had been used in the controllers, the first one related to blade pitch angle and electromagnetic torque control variables to meet specified objectives for operation region, the second control model and the third model related to d-q axis blade moment in non-rotating frame of reference. Likewise, the optimisation criteria of FLC consider for each controller objective to mitigate fatigue loads and regulate output power. Finally, the effectiveness of proposed method is verified by simulation results for three-bladed NREL 2 MW WT. The results proved that the fatigue loads in the turbine are reduced obviously.

[1]  Hamidreza Jafarnejadsani,et al.  Adaptive Control of a Variable-Speed Variable-Pitch Wind Turbine Using Radial-Basis Function Neural Network , 2013, IEEE Transactions on Control Systems Technology.

[2]  Matthew A. Lackner An investigation of variable power collective pitch control for load mitigation of floating offshore wind turbines: Variable power collective pitch control , 2013 .

[3]  Hazim Namik,et al.  Individual Blade Pitch Control of a Spar-Buoy Floating Wind Turbine , 2014, IEEE Transactions on Control Systems Technology.

[4]  Francesco Grimaccia,et al.  Pitch angle control using hybrid controller for all operating regions of SCIG wind turbine system , 2014 .

[5]  Paul A. Fleming,et al.  Validation of Individual Pitch Control by Field Tests on Two- and Three-Bladed Wind Turbines , 2013, IEEE Transactions on Control Systems Technology.

[6]  David Schlipf,et al.  Advanced controller research for multi-MW wind turbines in the UPWIND project , 2012 .

[7]  Carlo L. Bottasso,et al.  Estimation of blade structural properties from experimental data , 2013 .

[8]  Peter Fogh Odgaard,et al.  Fault-Tolerant Control of Wind Turbines: A Benchmark Model , 2009, IEEE Transactions on Control Systems Technology.

[9]  Zhe Chen,et al.  Proportional resonant individual pitch control for mitigation of wind turbines loads , 2013 .

[10]  Karl Stol,et al.  Simulating Feedback Linearization control of wind turbines using high‐order models , 2009 .

[11]  Ervin Bossanyi,et al.  Wind Turbine Control for Load Reduction , 2003 .

[12]  Ionel Vechiu,et al.  Comparison of an island wind turbine collective and individual pitch LQG controllers designed to alleviate fatigue loads , 2012 .

[13]  Yuan-Kang Wu,et al.  Optimization of the Wind Turbine Layout and Transmission System Planning for a Large-Scale Offshore WindFarm by AI Technology , 2014 .

[14]  P.W. Lehn,et al.  Simulation Model of Wind Turbine 3p Torque Oscillations due to Wind Shear and Tower Shadow , 2006, 2006 IEEE PES Power Systems Conference and Exposition.

[15]  Mark J. Balas,et al.  Periodic Disturbance Accommodating Control for Blade Load Mitigation in Wind Turbines , 2003 .

[16]  Kathryn E. Johnson,et al.  FX-RLS-Based Feedforward Control for LIDAR-Enabled Wind Turbine Load Mitigation , 2012, IEEE Transactions on Control Systems Technology.

[17]  Xu Yang,et al.  Wind Speed and Rotor Position Sensorless Control for Direct-Drive PMG Wind Turbines , 2012 .

[18]  Ervin Bossanyi Un-freezing the turbulence: application to LiDAR-assisted wind turbine control , 2013 .

[19]  A. Piccolo,et al.  Designing an Adaptive Fuzzy Controller for Maximum Wind Energy Extraction , 2008, IEEE Transactions on Energy Conversion.

[20]  Ahmed M. Kassem,et al.  Load parameter waveforms improvement of a stand-alone wind-based energy storage system and Takagi–Sugeno fuzzy logic algorithm , 2014 .