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U-SPARC M2M & OWL

Conducting an effective offshore wind resource assessment is challenging in the Mid-Atlantic region due to the lack of sufficient hub-height wind observations. Extrapolations of the measurements from the few existing towers and buoys do not provide sufficiently reliable estimations of the wind resource within the designated wind energy areas. Therefore, the use of models to help evaluate the wind resource is standard industry practice. Numerical weather prediction (NWP) models have advanced considerably in recent years; however, they remain imperfect, and frequently are unable to capture the true wind characteristics observed by instrumentation. The mesoscale models commonly used are also strongly dependent on the model configuration parameters, local physiography of the selected region, and the choice of data used for initial and boundary conditions. Therefore, it is imperative to perform model validation using observations, such as those obtained during U-SPARC R2O, in order to establish a baseline of model accuracy which will allow for improved interpretation of results during time periods lacking in observations. Furthermore, these observational campaigns can be used as additional model input, helping to improve model performance over the standard configurations and input datasets. These model improvements can both improve wind resource assessment pre-construction, and improve operational wind prediction for future wind farms. Finally, the improved model will be used for Optimizing Wind farm Layouts (OWL) research efforts, to assess different wind farm array configurations for the Maryland Wind Energy Area, and examine regional impacts from multiple nearby offshore wind farms.

An overview of the U-SPARC M2M & OWL efforts can be found here.