Print Email Facebook Twitter Mesoscale modeling of a “Dunkelflaute” event Title Mesoscale modeling of a “Dunkelflaute” event Author Li, B. (TU Delft Atmospheric Remote Sensing) Basu, S. (TU Delft Atmospheric Remote Sensing) Watson, S.J. (TU Delft Wind Energy) Russchenberg, H.W.J. (TU Delft Geoscience and Remote Sensing) Department Geoscience and Remote Sensing Date 2021 Abstract In the near future, wind and solar generation are projected to play an increasingly important role in Europe's energy sector. With such fast-growing renewable energy development, the presence of simultaneous calm wind and overcast conditions could cause significant shortfalls in production with potentially serious consequences for system operators. Such events are sometimes dubbed “Dunkelflaute” events and have occurred several times in recent history. The capabilities of contemporary mesoscale models to reliably simulate and/or forecast a Dunkelflaute event are not known in the literature. In this paper, a Dunkelflaute event near the coast of Belgium is simulated utilizing the Weather Research and Forecasting (WRF) model. Comprehensive validation using measured power production data and diverse sets of meteorological data (e.g., floating lidars, radiosondes, and weather stations) indicates the potential of WRF to reproduce and forecast the boundary layer evolution during the event. Extensive sensitivity experiments with respect to grid-size, wind farm parameterization, and forcing datasets provide further insights on the reliability of the WRF model in capturing the Dunkelflaute event. Subject North Seapower reliabilitysolar energywake parameterizationwind energy To reference this document use: http://resolver.tudelft.nl/uuid:b1252ff0-c828-4cde-8c63-affbc9a7783b DOI https://doi.org/10.1002/we.2554 ISSN 1095-4244 Source Wind Energy, 24 (1), 5-23 Part of collection Institutional Repository Document type journal article Rights © 2021 B. Li, S. Basu, S.J. Watson, H.W.J. Russchenberg Files PDF we.2554.pdf 48.82 MB Close viewer /islandora/object/uuid:b1252ff0-c828-4cde-8c63-affbc9a7783b/datastream/OBJ/view