Multi-model predictive control for wind turbine operation under meandering wake of upstream turbines |
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| Affiliation: | 1. EXA Corporation, Livonia, MI, USA;2. Department of Mechanical Engineering, University of Texas at Dallas, Richardson, TX, USA;3. High Altitude Trading, Inc., Jackson, WY, USA;1. College of IOT Engineering, Hohai University, Changzhou 213022, China;2. College of Energy and Electrical Engineering, Hohai University, Nanjing 210098, China;1. Geophysical Institute, University of Bergen and Bjerknes Center for Climate Research, Allegaten 70, N-5007 Bergen, Norway;2. Finnish Meteorological Institute, Helsinki, Finland;3. Energy Research Center of the Netherlands (ECN), Westerduinweg 3 1755 LE Petten, The Netherlands;4. Statoil ASA, Bergen, Norway;1. Department of Mechanical and Process Engineering, ETH Zurich, Switzerland;2. Model Predictive Control Laboratory, University of California Berkeley, USA;3. ABB Switzerland Ltd., Corporate Research, Baden-Daettwil, Switzerland;4. Automatic Control Laboratory, ETH Zurich, Switzerland |
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| Abstract: | In wind farm operation, the performance and loads of downstream turbines are heavily influenced by the wake of the upstream turbines. Furthermore, the actual wake is more challenging due to the dynamic phenomenon of wake meandering, i.e. the turbine wake often demonstrates dynamic shift over time. To deal with the time-varying characteristics of wake meandering, a multiple model predictive control (MMPC) scheme is applied to the individual pitch control (IPC) based load reduction. The coherence function in the spectral method is used to generate the stochastic wind profile including wake meandering at upstream turbine, and a simplified wake meandering model is developed to emulate the trajectory of the wake center at downstream turbine. The Larsen wake model and Gaussian distribution of wake deficit are applied for composing wind profiles across the rotor of downstream turbines. A set of MMPC controllers are designed based on different linearized state-space models, and are applied in a smooth switching manner. Simulation results show significant reduction in the variation of both rotor speed and blade-root flapwise bending moment using the MMPC based IPC by including the wake meandering, as compared to a benchmark PI controller designed by NREL. |
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| Keywords: | Wind turbine control Wake meandering Multi-model predictive control Individual pitch control Load reduction |
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