Multi-fidelity modelling of offshore wind energy systems including mesoscale variability at wind turbine scale: an application to wind farm control for grid balancing
How to deeply integrate offshore wind farms into the electricity market? Constraints like grid balance and frequency control will become more and more problematic as the number of GW of offshore wind energy is growing. To improve wind farm profits, it is necessary to have a better understanding of the weather transients impacts.
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To deeply integrate offshore wind farms into the electricity market, constrains like grid balance and frequency control will become more and more problematic as the number of GW of wind energy is growing. Also, over the last decade, the size and the number of offshore wind turbines and wind farms are constantly increasing, and ongoing projects show that this will continue. With tip height often above 200 meters, currently installed wind turbines are interacting and impacting massively the atmospheric boundary layer. Most of the low computational cost models are steady state and thus not capable of capturing weather transients.
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One of the topics that should be improved is the accuracy of wind forecast and its transients effects on wind farms. This implies an improved coupling between weather forecasting models and wind farm models.
For this purpose, a new dynamic wake model has been developed and validated against high-fidelity simulations with promising results. This will lead, first, to lower fees from the transmission system operator and then to an improved production of electricity.
To improve wind farm profits, it is necessary to have a better understanding of the weather transients impacts.