Abstract
During a 3 year research project funded by the local government of Baden-Württemberg, Germany, the potential of wind-energy production was studied at the university campus of Tübingen, a town in the south-west of Germany. The 3D wind field was studied both experimentally and numerically in order to identify optimal locations for small wind turbine installation. Within the scope of this project, a full-scale field experiment and RANS (Reynolds Averaged Navier-Stokes) models were applied in order to yield a better understanding of the airflow around the buildings. We validate our CFD predictions of the flow field with wind-speed measurements using ultrasonic anemometers at several stations within the campus. The simulation results (in direct comparison with the measured data) improved greatly when trees were explicitly considered using a simple canopy model at the inflow boundary. This study is intended to support and guide the next steps of the wind resources assessment at similar sites. We gladly offer our site, instrumentation and (simulated and measured) data to other groups that perform urban wind energy studies.
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References
Ayachit, U.: The paraview guide: a parallel visualization application (2015)
Bailey, B.H., McDonald, S.L., Bernadett, D., Markus, M., Elsholz, K.: Wind resource assessment handbook: fundamentals for conducting a successful monitoring program. Tech. rep., National Renewable Energy Lab., Golden, CO (US); AWS Scientific, Inc., Albany, NY (US) (1997)
Blocken, B.: 50 years of computational wind engineering: past, present and future. J. Wind Energy Ind. Aerodyn. 129, 69–102 (2014)
Blocken, B., Gualtieri, C.: Ten iterative steps for mode development and evaluation applied to computational fluid dynamics for environmental fluid mechanics. Env. Model. Softw. 33, 1–22 (2012)
Cescatti, A., Marcolla, B.: Drag coefficient and turbulence intensity in conifer canopies. Agric. For. Meteorol. 121, 197–206 (2004)
Franke, J., Hellsten, A., Schlnzen, H., Carissimo, B.: The COST 732 best practice guideline for CFD simulation of flows in the urban environment: a summary. Int. J. Env. Pollut. 44, 419–427 (2011)
Greens, S., Grace, J., Hutchings, N.: Observations of turbulent air flow in three stands of widely spaced sitka spruce. Agric. For. Meteorol. 74, 205–225 (1996)
Landberg, L., Myllerup, L., Rathmann, O., Petersen, L., Hoffmann Jrgensen, B., Badger, J., Gylling Mortensen, N.: Wind resource estimation—an overview. Wind Energy 6, 261–271 (2003)
Launder, B.E., Spalding, D.: The numerical computation of turbulent flows. Comput. Meth. Appl. Mech. Eng. 3, 269–289 (1974)
Liu, J., Chen, J., Novak, M.: k-epsilon modelling of turbulent air flow downwind of a model forest edge. Bound.-Layer Meteorol. 77, 21–44 (1996)
Meier, I., Leuschner, C.: Leaf size and leaf area index in fagus sylvatica forests: competing effects of precipitation, temperature, and nitrogen availability. Ecosystems 11, 655–669 (2008)
Mochida, A., Tabata, Y., Iwata, T., Yoshino, H.: Examining tree canopy models for CFD predicyion of wind environment at pedestrian level. J. Wind Energy Ind. Aerodyn. 96, 1667–1677 (2008)
Rau, I.M., Bigalke, K.: Synthetische Windstatistiken Baden-Württemberg Hinweise für Anwender. Landesanstalt für Umwelt, Messungen und Naturschutz Baden-Württemberg (2007)
Richards, P., Hoxey, R.: Appropriate boundary conditions for computational wind engineering models using the k-epsilon turbulence models. J. Wind Energy Ind. Aerodyn. 46–47, 145–153 (1993)
Salim, M.H., Schlnzen, H.K., Grawe, D.: Including trees in the numerical simulations of the wind flow in urban areas: should we care? J. Wind Energy Ind. Aerodyn. 144, 84–95 (2015)
Thimonier, A., Sedivy, I., Schleppi, P.: Estimating leaf area index in different types of mature forest stands in switzerland: a comparison of methods. Eur. J. For. Res. 129, 543–562 (2010)
Tominaga, Y., Mochida, A., Yoshie, R., Kataoka, H., Nozu, T., Yoshikawa, M., Shirasawa, T.: AIJ guidelines for practical applications of CFD to pedestrian wind environment around buildings. J. Wind Energy Ind. Aerodyn. 96, 1749–1761 (2008)
Walker, S.: Building mounted wind turbines and their suitability for the urban scalea review of methods of estimating urban wind resource. J. Energy Build. 43, 1852–1862 (2013)
Wildmann, N., Hofsäß, M., Weimer, F., Joos, A., Bange, J.: MASC—a small remotely piloted aircraft (RPA) for wind energy research. Adv. Sci. Res. 11, 55–61 (2014)
Wildmann, N., Rau, G., Bange, J.: Observations of the early morning boundary-layer transition with small remotely-piloted aircraft. Bound.-Layer Meteorol. 157(3), 345–373 (2015)
Acknowledgements
The authors thank the Ministry of Science, Research and the Arts of the State of Baden-Württemberg for funding this study, the Geographical Institute of the University of Tübingen for providing terrain data, and the Technical Building Management (TBA) of the University of Tübingen for assisting the experimental part. The computational resources were provided by the bwGRiD Cluster at the University of Tübingen.
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El Bahlouli, A., Bange, J. (2018). Experimental and Numerical Wind-Resource Assessment of an University Campus Site. In: Battisti, L., Ricci, M. (eds) Wind Energy Exploitation in Urban Environment. TUrbWind 2017. Green Energy and Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-74944-0_1
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DOI: https://doi.org/10.1007/978-3-319-74944-0_1
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