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MEWA

Objective:
MEWA is a pilot-research project funded by the Ministry of Foreign Affairs of Denmark and administered by Danida Fellowship Centre. Project partners are DTU Wind Energy (Denmark), Instituto Nacional de Electricidad y Energías Limpias (Mexico),  Instituto Tecnológico y de Estudios Superiores de Monterrey (Mexico), and Centro de Investigación Científica y de Educación Superior de Ensenada (México).

MEWA has two main research-specific objectives: a) to investigate how to best couple meso- and micro-scale models for improving predictions of wind resources and b) to investigate the impact of climate variability and changes in surface characteristics and land cover on wind resources.

Expected outcome:
MEWA aims at establishing a verified methodology for the coupling of meso- and micro-scale models that provides accurate and precise estimates of wind resources over complex topographies and climatographies. Further, MEWA aims, for the first time, at estimating the impact of climate variability on wind resources using multi-scale modelling. The results of MEWA will be implemented in tools for wind resource mapping that are used and developed by DTU Wind Energy for wind turbine siting all over the world. Lastly, MEWA aims at strengthening the relations between research centers in Denmark and Mexico, and their research capacity.

The project began on  01.04.2018 and  and finished on 31.12.2021.

Total project budget: 4.98 mio. DKK.

Master theses associated with the project:
  1. Johansson E. E. (2019) The future of wind power resources in Denmark predicted by downscaling global circulation models. DTU Wind Energy-M-0255
  2. Villanueva J. (2019) Evaluation of the wind atlas method to predict wind resources from numerical wind simulations. DTU Wind Energy-M-0305
  3. García Santiago O. M. (2020) Cambios en la circulación de los vientos de bajos niveles en México ante escenarios de cambio climático. Master thesis. Centro de Investigación Científica y de Educación superior de Ensenada, Baja California, xii, 77 pp.
  4. Quiroga Novoa P. F. (2020) Wind resource assessment using mesoscale and microscale coupling techniques. Master thesis. Tecnologico de Monterrey
Presentations at conferences:
  1. Peña A., Floors R. and Hahmann A.N. (2019) Is WRF-LES worth or worthless? Wind Energy Science conference, Cork, Ireland
  2. Peña A., Floors R. and Hahmann A.N. (2019) WRF-LES evaluation of turbulence measures using observations from a 250-m tower. International Conference on Energy & Meteorology, Lyngby, Denmark
  3. Peña A. and Hahmann A.N. (2019) An evaluation of WRF-LES using measurements from a 250-m tower. European Meteorological Society Annual Meeting, Lyngby, Denmark
  4. Floors, R., Peña A. and Hahmann (2019) A. Statistical coupling of mesoscale and microscale simulations: combining WRF and WAsP for wind resource assessments, European Meteorological Society Annual Meeting, Lyngby, Denmark
  5. Magar V., Gross M. and Cruz-Rico J.E. (2019) Evaluación de cobertura de vegetación y altura del dosel de vegetación a través de imágenes satelitales y datos lidar, con aplicaciones a caracterización de recursos de energía eólica. Reunión Anual de la Unión Geofísica Mexicana, Puerto Vallarta, Mexico
  6. Gross M. and Magar V. (2019) Evaluación de recurso de energía eólica con datos de torres anemométricas: efecto de la frecuencia de muestreo, de la técnica de promediado de datos, y de la longitud de la serie de tiempo. Reunión Anual de la Unión Geofísica Mexicana, Puerto Vallarta, Mexico
  7. García O. and Cavazos T. (2019) Present and future changes in low-level wind circulation in Mexico. Paper-Writing Workshop on the Analysis of CORDEX-CORE Climate Projections. ICTP, Trieste, Italy. May 2019. 
  8. García O. and Cavazos T. (2019) Cambio en la circulación de los vientos de bajos niveles en México ante escenarios de cambio climático. Reunión Anual de la Unión Geofísica Mexicana, Puerto Vallarta, Mexico
  9. Cavazos, T., Luna-Niño R.B., Cerezo-Mota R, Colorado-Ruiz G., García Santiago O.M., Torres-Alavez J.A., Hidalgo H., and Salinas J.A. (2019) Regional Modeling Studies in the CORDEX-CAM (Central America, Mexico and Caribbean) Domain. Invited Talk; American Geophysical Union, Fall Meeting, San Francisco, US. http://agu.confex.com/agu/fm19/meetingapp.cgi/Paper/512081
  10. Peña A. and Hahmann A.N. (2020) Evaluating planetary boundary layer schemes and large-eddy simulations with measurements from a 250-m meteorological mast. The Science of Making Torque from Wind, Delft, Netherlands
  11. Hahmann A. N., Peña A. and Pryor S. (2020) Future wind resources in the North Sea as predicted by CMIP6 models. European Geophysical Union Annual Meeting, Viena, Austria https://meetingorganizer.copernicus.org/EGU2020/EGU2020-9093.html
  12. Floors R., Peña A., and Hahmann A.N. (2020) Statistical coupling of mesoscale and microscale simulations: combining WRF and WAsP for wind resource assessments. Vindkraftnet meeting, Kolding, Denmark
  13. Soria A., Magar V., Gross M., and Peña A. (2020) Caracterización de recursos de energía eólica en La Rumorosa, Baja California basada en mediciones de torres anemométricas y modelos numéricos, Reunión Anual de la Unión Geofísica Mexicana, Guadalajara, México
  14. Peña A. and Hahmann, A.N. (2020)  Evaluación de esquemas de PBL y large-eddy simulations con mediciones de un mástil de 250 m, Reunión Anual de la Unión Geofísica Mexicana, Guadalajara, México
  15. Peña A. (2021) How turbulent is the atmospheric hydraulic jump at Alaiz? Wind Energy Science conference, virtual
  16. Rogier, F., Hahmann, A.N., Cavar, D., Olsen, B.T., Davis, N., Peña, A., Mortensen, N.G., Bechmann, A., Hansen, J.C., Lennard, C., and Badger, J. (2021) Integrated wind resource modeling with WRF and PyWAsP, Wind Energy Science conference, virtual
  17. Hahmann A., Arguello R.L., Olsen, B.T., Cavar D., Floors R., and Peña A. (2021). Optimising the WRF model configuration for the Mexican Wind Atlas. Wind Energy Science conference, virtual
  18. Peña A. and Mirocha J.D. (2021) Comparison of LES of wakes with wind farm parametrizations using the WRF model, Wake conference, virtual
  19. Peña A. and Mirocha J.D. (2021) Evaluation of the wind farm parametrization with LESs of wakes in WRF, European Meteorological Society Annual Meeting, solicited talked, virtual
  20. Magar, V., Gross, M. S., Peña, A., Hahmann, A.N., and García-Santiago, L.S. (2021) Energía Eólica y Transición Energética: Estado actual y retos y oportunidades desde la perspectiva del desarrollo sostenible y sostenido. Reunión Anual de la Unión Geofísica Mexicana, Guadalajara, México
  21. Peña A., Mirocha J.D., and Hahmann A.N. (2022) A one-year long turbulence simulation using a WRF-LES based modeling system at Østerild, The Science of Making Torque from Wind, Delft, Netherlands
  22. Peña A. and Mirocha J.D. (2022) Intercomparing WRF-LES based turbulence simulations with measurements from a 250-m tall meteorological mast, European Geophysical Union Annual Meeting, Viena, Austria
  23. Hahmann A.N., Peña A., García-Santiago O., and Pryor S.C. (2022) Evaluation of the assumptions used in the assessment of future wind resources - A case for CMIP6 in Northern Europe, European Geophysical Union Annual Meeting, Viena, Austria
Sessions organized in conferences:
  1. Gross M. and Magar V. (2019) SE05: Modelación numérica para energías renovables (eólica y mar). Reunión Anual de la Unión Geofísica Mexicana, Puerto Vallarta , México
  2. Gross M., Magar V., Rodríguez O. and Peña A. (2020) SE03: Avances Recientes en Modelación Numérica, Experimental o Estadística para Energía Eólica y Energías Renovables Marinas. Reunión Anual de la Unión Geofísica Mexicana, Guadalajara, México
  3. Magar V. and Gross M. (2020) Recent advances in micro and mesoscale models, and meso-micro model coupling, for Wind Energy resource characterization. Global environmental change, Annual Unionl Meeting, San Francisco, US
  4. Gross M., Magar V., Rodríguez O. and Peña A. (2021) SE02: Avances Recientes en Modelación Numérica, Experimental o Estadística para Energía Eólica y Energías Renovables Marinas. Reunión Anual de la Unión Geofísica Mexicana, Guadalajara, México
Chapters in books:
  1. Magar V., Gross M., García Hernández L.S., Peña A. and Hahmann A.N. (2019) La energía eólica en México, desafíos y oportunidades. In:  Prospectiva del sector energético de México. Submitted to the Mexican Senate editorial services
International journal papers: 
  1. Peña A. (2019) Østerild: a natural laboratory for atmospheric turbulence. Journal of Sustainable and Renewable Energy 11, 063302 
  2. Gross M., Magar V., and Peña A. (2020) The effect of averaging, sampling and time series length on wind power density estimations, Sustainability, 12, 3431
  3. Hahmann A.N., Sile T., Witha B., Davis N.N., Dörenkämper M., Ezber Y., García-Bustamante E., González-Rouco J.F., Navarro J., Olsen B.T., and Södeberg S. (2020) The making of the new European Wind Atlas, Part 1: model sensitivity. Geoscientific Model Development, 13, 5053—5078
  4. Peña A. and Hahmann A.N. (2020) Evaluating planetary boundary layer schemes and large-eddy simulations with measurements from a 250-m meteorological mast. Journal of Physics: Conference Series, 1618, 062001
  5. Peña A. and Rosas P. (2021) Lidar observations and numerical simulations of an atmospheric hydraulic jump and mountain waves, Journal of Geophysical Research – Atmospheres, 126, e2020JD033744
  6. Peña A., Kosović B., and Mirocha J.D. (2021) Evaluation of idealized large-eddy simulations performed with the Weather Research and Forecasting model using turbulence measurements from a 250-m meteorological mast, Wind Energy Science, 6, 645—661
  7. Peña A. and Mirocha A.N. (2021) Comparison of large-eddy simulations of wakes with wind farm wake parametrizations using the Weather Research and Forecasting model. Journal of Physics: Conference Series, 1934, 012010
  8. Rosas P., Peña A., and Mann J. (2021) Departure from flux-gradient relation in the planetary boundary layer. Atmosphere, 12, 672
  9. Quiroga-Nova P, Cuevas-Figueroa G, Preciado J. L., Floors, R., Peña A., and Probst, O. (2021) Towards better wind resource modeling in complex terrain: a k-nearest neighbors approach. Energies, 14, 4364
  10. Floors R, Badger M, Troen I., Grogan K., and Permien F.-H. (2021) Satellite-based estimation of roughness lengths and displacement heights for wind resource modelling, Wind Energy Science, 6, 1379—1400
  11. Peña A., Mirocha J.D, and Hahmann A.N. (2022) A one-year long turbulence simulation using a WRF-LES based modeling system at Østerild. Journal of Physics: Conference Series, 2265, 022011
  12. Gross M., Magar V., and Peña A. (2022) Evaluation of model hierarchies and deep neural network regression for wind speed forecasts and resource assessment, Wind Energy, in review
  13. Peña A., Mirocha J.D., and van der Laan M.P. (2021) Evaluation of a wind farm wake parameterization with large-eddy simulations of wakes using the Weather Research and Forecasting model. Monthly Weather Review, in review
  14. Magar, V., Peña, A., Hahmann, A. N., Pacheco-Rojas, D. A., García-Hernández, L. S., and Gross, M. S. (2022) Wind energy and the energy transition: Challenges and opportunities for Mexico, Sustainability, in review
  15. Hahmann A. H., Garcia-Santiago O.M., and Peña, A., (2022) Current and future wind energy resources in the North Sea according to CMIP6, Wind Energy Science, in review
Technical reports:
  1. Saldaña R., Lira R. and Miranda U. (2019) Inventory of datasets of atmospheric flow simulations and observations
  2. Caetano E., Pereyra K and Rojas S. (2019) Inventory of models employed for the simulation of mean wind patterns and their variability

Contact

Alfredo Peña Díaz
Senior Scientist
DTU Wind
+45 46 77 50 55