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Periodic Report Summary 1 - MESOWAKE (Unified mesoscale to wind turbine wake downscaling based on an open-source model chain)

MesoWake is a project sponsored by the European Commission's within an FP7 International Outgoing Marie Curie Fellowship granted to Javier Sanz Rodrigo, Senior Researcher at the National Renewable Energy Center of Spain (CENER). The outgoing phase of this fellowship, from August 2014 to July 2016, was hosted by the National Renewable Energy Laboratory (NREL) of the U.S. Department of Energy. The reintegration phase is back to CENER until July 2017. The project counts with the National Center for Atmospheric Research (NCAR) and the Barcelona Supercomputing Center (BSC) as scientific partners.

The objective is to contribute to the development of an open-source model chain that can bridge the gap between mesoscale meteorological processes and microscale wind farm models. The need for a multi-scale approach is the result of the evolution of wind turbine technology that, over the last decades, has been successful at exploiting wind turbine scaling designs with rotors already spanning more than 150 m diameter and hub heights above 100 m. The increasing range of scales is challenging traditional wind engineering models that consider the wind farm system as an idealized microscale system where surface-layer theories apply. This lack of appropriate physics often leads to wind farm underperformance and high project financing costs.

In MesoWake, special focus is given to the characterization of mesoscale forcing to drive atmospheric boundary layer models using realistic boundary conditions. Initial assessment of the meso-micro methodology around the GABLS3 diurnal cycle has shown good consistency of the methodology to couple mesoscale and microscale models asynchronously (Sanz Rodrigo et al., 2016a). The method is relatively straightforward to implement in existing microscale models. High-fidelity turbulence modeling is based on large-eddy simulation (LES) to resolve the turbulent scales that affect turbine and wind farm performance. The open-source unified model is based on SOWFA (OpenFOAM-LES coupled to FAST turbine aeroelastic code), developed at NREL, coupled asynchronously with mesoscale forcing generated with WRF, developed at NCAR. Assessment of the effectiveness of this coupling methodology is carried out by comparing with synchronous coupling through the WRF-LES model.

The codes are installed at the MareNostrum high performance computing facility managed by BSC, member of the Partnership for Advance Computing in Europe (PRACE). This will provide a virtual laboratory for high fidelity modeling of atmospheric physics applied to wind energy. This laboratory has effectively kicked-off in September 2017 with PRACE-MesoWake, a multi-year Project Access award with an initial allocation of 17 million cpu-hours for the first year. Scaling tests and a performance audit has been carried out, under the Performance Optimization and Productivity (POP) Centre of Excellence, to determine the suitability of the codes to run in high-performance computing systems.

The MesoWake project is timely at creating a European hub for the development of high-fidelity modeling capabilities based on an open-source framework. This unified model will support ongoing activities in Europe and the U.S. and strengthen the cooperation in this strategic interdisciplinary research area. The model evaluation strategy adopted in MesoWake follows the systematic verification and validation framework developed in the context of the International Energy Agency's IEA Task 31 Wakebench (Sanz Rodrigo et al., 2016b).


Sanz Rodrigo, J., Churchfield M., Kosovic B. (2016b) Atmospheric boundary layer modeling based on mesoscale tendencies and data assimilation at microscale. Wind Energy Science, submitted

Sanz Rodrigo, J., Chávez Arroyo, R.A., Moriarty, P., Churchfield, M., Kosovic, B., Réthoré, R.-E., Hansen, K.S., Hahmann, A., Mirocha, J.D. and Rife, D. (2016a) Mesoscale-to-Microscale Wind Farm Flow Modelling and Evaluation. WIREs Energy Environ. doi: 10.1002/wene.214

Javier Sanz Rodrigo,

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