Forecast error mitigation for the ramp-constrained operation of wind farms
Jenna Iori (TU Delft - Aerospace Engineering)
Michiel Zaaijer (TU Delft - Aerospace Engineering)
Dominic von Terzi (TU Delft - Aerospace Engineering)
Simon Watson (TU Delft - Aerospace Engineering)
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Abstract
Power ramp events represent an important challenge to grid stability, motivating the enforcement of ramp limits. For wind farm operation, decisions to respect these limits are based on imperfect forecast data, where errors can lead to deviations from the prescribed limit. In this study, we propose two different methods to mitigate the impact of forecast uncertainties on the operation of ramp-constrained wind farms: the use of a pessimistic forecast, where ramp events are worsened artificially, and the use of a storage system. The two methods are assessed by solving an online dispatch optimization problem for one year of operation. Forecast data are generated from numerical weather prediction models of the ECMWF. The dependence of power production on wind speed and direction changes is captured by an engineering wake deficit model. Results for 20 different offshore sites in Europe show that using a pessimistic forecast reduces the number of ramp events exceeding the limit by one third but increases curtailment by 0.2 percentage points on average. Instead, adding a storage system to the wind farm is more effective at reducing curtailment, proportionally to its size. The impact of forecast errors is mitigated most effectively by combining the two methods.
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