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Multiobjective model predictive control design for wind turbines and farms
Wind turbine arrays can be viewed as large coupled networks, wherein wake effects limit the available power extraction of turbines downstream. In this paper, we incorporate wake steering and time dependent wind estimation models into a multiobjective wind farm control problem for improving power extraction. We further aim to mitigate the effects of turbulence and power spikes caused by wind passing through upstream turbines. We expand upon a previous heuristic method for the far-field wake problem and apply the algorithm on a model predictive control framework. Simulation results are given, demonstrating improved power output as compared to algorithms that do not incorporate wake steering or wind estimation models.
Multiobjective model predictive control design for wind turbines and farms
Wind turbine arrays can be viewed as large coupled networks, wherein wake effects limit the available power extraction of turbines downstream. In this paper, we incorporate wake steering and time dependent wind estimation models into a multiobjective wind farm control problem for improving power extraction. We further aim to mitigate the effects of turbulence and power spikes caused by wind passing through upstream turbines. We expand upon a previous heuristic method for the far-field wake problem and apply the algorithm on a model predictive control framework. Simulation results are given, demonstrating improved power output as compared to algorithms that do not incorporate wake steering or wind estimation models.
Multiobjective model predictive control design for wind turbines and farms
Buccafusca, Lucas (Autor:in) / Beck, Carolyn (Autor:in)
01.05.2021
13 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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