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This study presents a methodology for wind farm set point optimization, which allows including both loads and power output as optimization criteria. The primary control strategy investigated involves de-rating of individual turbines in the wind farm. The optimal de-rating level of each individual turbine is determined by using accurate and computationally efficient surrogate models, mapping the dependency between the choice of de-rating strategy for a given turbine and the load and power outputs of downwind turbines. A case study based on the Lillgrund offshore wind farm shows that for specific wind directions with strong wake interactions, it may be possible to achieve a net gain in power output in the order of 5% at specific mean wind speeds. Alternatively, maintaining nominal power output but optimizing the load distribution could lead to substantial fatigue load reductions.

Wind farm set point optimization with surrogate models for load and power output targets