Abstract
We use theWind Farm Parameterization (WFP) scheme coupled with theWeather Research and Forecasting model under multiple resolution regimes to simulate turbulent wake dynamics generated by a real onshore wind farm and their influence at the local meteorological scale. The model outputs are compared with earlier modeling and observation studies. It is found that higher vertical and horizontal resolutions have great impacts on the simulated wake flow dynamics. The corresponding wind speed deficit and turbulent kinetic energy results match well with previous studies. In addition, the effect of horizontal resolution on near-surface meteorology is significantly higher than that of vertical resolution. The wake flow field extends from the start of the wind farm to downstream within 10 km, where the wind speed deficit may exceed 4%. For a height of 150 m or at a distance of about 25 km downstream, the wind speed deficit is around 2%. This indicates that, at a distance of more than 25 km downstream, the impact of the wind turbines can be ignored. Analysis of near-surface meteorology indicates a night and early morning warming near the surface, and increase in near-surface water vapor mixing ratio with decreasing surface sensible and latent heat fluxes. During daytime, a slight cooling near the surface and decrease in the near-surface water vapor mixing ratio with increasing surface sensible and latent heat fluxes is noticed over the wind farm area.
摘 要
利用耦合了风电场拖曳参数化(WFP)方案的WRF模式, 探究不同水平与垂直分辨率下模式对昌邑风电场湍流尾流动力过程的模拟表现, 以及对局地天气尺度系统的影响. 结果表明: 空间分辨率对尾流模拟效果影响较大, 其中水平分辨率对近地面气象要素的影响显著高于垂直分辨率, 高分辨率模拟得到的风速损耗和湍流动能与前人研究更为吻合; 沿风传播方向, 距风机组不同距离风速损耗不同, 其中10 km内尾流造成的总损耗可超过4%, 25km内总损耗降至2%, 说明风机尾流效应的影响范围在25km以内; 70 m风机的尾流影响高度在150m以下; 尾流动力过程导致夜晚至次日凌晨近地面气温升高, 地表感热通量和潜热通量减小, 水汽混合比增加; 白天, 随着地表感热通量和潜热通量的增大, 近地面温度略微下降, 水汽混合比减小.
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References
Abkar, M., and F. Porté-Agel, 2015: A new wind-farm parameterization for large-scale Atmospheric models. Journal of Renewable and Sustainable Energy, 7, 013121, https://doi.org/10.1063/1.4907600.
Adams, A. S., and D. W. Keith, 2007: Wind energy and climate: Modeling the atmospheric impacts of wind energy turbines. American Geophysical Union, Fall Meeting 2007, American Geophysical Union, B44B-08.
Aitken, M. L., B. Kosovic, J. D. Mirocha, and J. K. Lundquist, 2014: Large eddy simulation of wind turbine wake dynamics in the stable boundary layer using the Weather Research and Forecasting Model. Journal of Renewable and Sustainable Energy, 6, 033137, https://doi.org/10.1063/1.4885111.
Baidya Roy, S., 2011: Simulating impacts of wind farms on local hydrometeorology. Journal of Wind Engineering and Industrial Aerodynamics, 99, 491–498, https://doi.org/10.1016/j.jweia.2010.12.013.
Baidya Roy, S., and J. J. Traiteur, 2010: Impacts of wind farms on surface air temperatures. Proceedings of the National Academy of Sciences of the United States of America, 107(42), 17 899–17 904, https://doi.org/10.1073/pnas. 1000493107.
Baidya Roy, S., S. W. Pacala, and R. L. Walko, 2004: Can large wind farms affect local meteorology? J. Geophys. Res., 109, D19101, https://doi.org/10.1029/2004JD004763.
Banks, R. F., J. Tiana-Alsina, J. M. Baldasano, F. Rocadenbosch, A. Papayannis, S. Solomos, and C. G. Tzanis, 2016: Sensitivity of boundary-layer variables to PBL schemes in the WRF model based on surface meteorological observations, lidar, and radiosondes during the HygrA-CD campaign. Atmos. Res., 176–177, 185–201, https://doi.org/10.1016/j.atmosres. 2016.02.024.
Blahak, U., B. Goretzki, and J. Meis, 2010: A simple parameterization of drag forces induced by large wind farms for numerical weather prediction models. Proc. European Wind Energy Conf. and Exhibition, PO ID 445, Warsaw, Poland, EWEC, 186–189.
Bowden, J. H., T. L. Otte, C. G. Nolte, and M. J. Otte, 2012: Examining interior grid nudging techniques using two-way nesting in the WRF model for regional climate modeling. J. Climate, 25, 2805–2823, https://doi.org/10.1175/JCLI-D-11-00167.1.
Calaf, M., M. B. Parlange, and C. Meneveau, 2011: Large eddy simulation study of scalar transport in fully developed windturbine array boundary layers. Physics of Fluids, 23, 126603, https://doi.org/10.1063/1.3663376.
Cervarich, M. C., S. Baidya Roy, and L. M. Zhou, 2013: Spatiotemporal structure of wind farm-atmospheric boundary layer interactions. Energy Procedia, 40, 530–536, https://doi.org/10.1016/j.egypro.2013.08.061.
Chen, F., and J. Dudhia, 2001: Coupling an advanced land surfacehydrology model with the Penn state-NCAR MM5 modeling system. Part II: Preliminary model validation. Mon. Wea. Rev., 129, 569–585, https://doi.org/10.1175/1520-0493 (2001)129<0587:CAALSH>2.0.CO;2.
Christiansen, M. B., and C. B. Hasager, 2005: Wake effects of large offshore wind farms identified from satellite SAR. Remote Sensing of Environment, 98, 251–268, https://doi.org/10.1016/j.rse.2005.07.009.
Churchfield, M., S. Lee, P. Moriarty, L. Martinez, S. Leonardi, G. Vijayakumar, and J. Brasseur, 2012: A Large-eddy simulation of wind-plant aerodynamics. 50th AIAA Aerospace Sciences Meeting Including the New Horizons Forum and Aerospace Exposition, Nashville, Tennessee, AIAA.
de Andrade Campos, D., S. C. Chou, C. Spyrou, J. C. S. Chagas, and M. J. Bottino, 2017: Eta model simulations using two radiation schemes in clear-sky conditions. Meteor. Atmos. Phys., 130, 39–48, https://doi.org/10.1007/s00703-017-0500-6.
Dudhia, J., 1989: Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model. J. Atmos. Sci., 46(20), 3077–3107, https://doi.org/10.1175/1520-0469(1989)046<3077: NSOCOD>2.0.CO;2.
Ek, M. B., K. E. Mitchell, Y. Lin, E. Rogers, P. Grunmann, V. Koren, G. Gayno, and J. D. Tarpley, 2003: Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model. J. Geophys. Res., 108(D22), 8851, https://doi.org/10.1029/2002JD003296.
Eriksson, O., J. Lindvall, S. P. Breton, and S. Ivanell, 2015: Wake downstream of the Lillgrund wind farm-A Comparison between LES using the actuator disc method and a wind farm parametrization in WRF. Journal of Physics: Conference Series, 625, 012028, https://doi.org/10.1088/1742-6596/625/1/012028.
Fitch, A. C., J. K. Lundquist, and J. B. Olson, 2013a: Mesoscale influences of wind farms throughout a diurnal cycle. Mon. Wea. Rev., 141, 2173–2198, https://doi.org/10.1175/MWR-D-12-00185.1.
Fitch, A. C., J. B. Olson, and J. K. Lundquist, 2013b: Parameterization of wind farms in climate models. J. Climate, 26, 6439–6458, https://doi.org/10.1175/JCLI-D-12-00376.1.
Fitch, A. C., J. B. Olson, J. K. Lundquist, J. Dudhia, A. K. Gupta, J. Michalakes, and I. Barstad, 2012: Local and mesoscale impacts of wind farms as parameterized in a mesoscale NWP model. Mon. Wea. Rev., 140, 3017–3038, https://doi.org/10.1175/MWR-D-11-00352.1.
Gao, M., J. C. Ning, and X. Q. Wu, 2015: Normal and extreme wind conditions for power at coastal locations in China. PLoS One, 10(8), e013876, https://doi.org/10.1371/journal.pone. 0136876.
Global Wind Energy Council, 2018: Global wind statistics 2017. Global Wind Energy Council Rep., 4 pp.
Grell, G. A., and D. Dévényi, 2002: A generalized approach to parametrizing convection combining ensemble and data assimilation techniques. Geophys. Res. Lett., 29(14), 1693, https://doi.org/10.1029/2002GL015311.
Gutierrez, W., G. Araya, S. Basu, A. Ruiz-Columbie, and L. Castillo, 2014: Toward understanding low level jet climatology over west Texas and its impact on wind energy. Journal of Physics: Conference Series, 524, 012008, https://doi.org/10.1088/1742-6596/524/1/012008.
Hainbucher, D., W. Hao, T. Pohlmann, J. Sündermann, and S. Z. Feng, 2004: Variability of the Bohai Sea circulation based on model calculations. J. Mar. Syst., 44, 153–174, https://doi.org/10.1016/j.jmarsys.2003.09.008.
Iacono, M. J., J. S. Delamere, E. J. Mlawer, M.W. Shephard, S. A. Clough, and W. D. Collins, 2008: Radiative forcing by longlived greenhouse gases: Calculations with the AER radiative transfer models. J. Geophys. Res., 113, D13103, https://doi.org/10.1029/2008JD009944.
IEA, 2011: Technological roadmap: China wind energy roadmap development 2050. OECD/IEA/ERI Rep., 56 pp.
IEA, 2013: Technology roadmap: Wind energy. OECD/IEA, Rep., 63 pp.
Ivanova, L. A., and E. D. Nadyozhina, 2000: Numerical simulation of wind farm influence on wind flow. Wind Engineering, 24, 257–269, https://doi.org/10.1260/0309524001495620.
Jacobson, M. Z., and C. L. Archer, 2012: Saturation wind power potential and its implications for wind energy. Proceedings of the National Academy of Sciences of the United States of America, 109, 15679–15 684, https://doi.org/10.1073/pnas. 1208993109.
Jiménez, A., A. Crespo, E. Migoya, and J. Garcia, 2007: Advances in large-eddy simulation of a wind turbine wake. Journal of Physics: Conference Series, 75, 012041, https://doi.org/10.1088/1742-6596/75/1/012041.
Jiménez, P. A., J. Navarro, A. M. Palomares, and J. Dudhia, 2015: Mesoscale modeling of offshore wind turbine wakes at the wind farm resolving scale: A composite-based analysis with theWeather Research and Forecasting Model over Horns Rev. Wind Energy, 18, 559–566, https://doi.org/10.1002/we.1708.
Kirk-Davidoff, D. B., and D. W. Keith, 2008: On the climate impact of surface roughness anomalies. J. Atmos. Sci., 65, 2215–2234, https://doi.org/10.1175/2007JAS2509.1.
Lee, J. C. Y., and J. K. Lundquist, 2017: Evaluation of the wind farm parameterization in the Weather Research and Forecasting model (version 3.8.1) with meteorological and turbine power data. Geoscientific Model Development, 10, 4229–4244, https://doi.org/10.5194/gmd-10-4229-2017.
Li, D. L., H. Von Storch, B. S. Yin, Z. H. Xu, J. F. Qi, W. Wei, and D. L. Guo, 2018: Low-level jets over the Bohai Sea and Yellow Sea: Climatology, variability, and the relationship with regional atmospheric circulations. J. Geophys. Res., 123, 5240–5260, https://doi.org/10.1029/2017JD027949.
Liu, P., A. P. Tsimpidi, Y. Hu, B. Stone, A. G. Russell, and A. Nenes, 2012: Differences between downscaling with spectral and grid nudging using WRF. Atmos. Chem. Phys., 12(8), 3601–3610, https://doi.org/10.5194/acp-12-3601-2012.
Lu, H., and F. Porté-Agel, 2011: Large-eddy simulation of a very large wind farm in a stable atmospheric boundary layer. Physics of Fluids, 23, 065101, https://doi.org/1063/1.3589857.
Ma, Y. Y., Y. Yang, X. P. Mai, C. J. Qiu, X. Long, and C. H. Wang, 2016: Comparison of analysis and spectral nudging techniques for dynamical downscaling with the WRF model over China. Advances in Meteorology, 2016, 4761513, https://doi.org/10.1155/2016/4761513.
Manwell, J. F., J. G. McGowan, and A. L. Rogers, 2002: Wind Energy Explained: Theory, Design and Application. Willey, 46–47.
Mirocha, J. D., B. Kosovic, M. L. Aitken, and J. K. Lundquist, 2014: Implementation of a generalized actuator disk wind turbine model into the weather research and forecasting model for large-eddy simulation applications. Journal of Renewable and Sustainable Energy, 6, 013104, https://doi.org/10.1063/1.4861061.
Nakanishi, M., and H. Niino, 2009: Development of an improved turbulence closure model for the atmospheric boundary layer. J. Meteor. Soc. Japan, 87(5), 895–912, https://doi.org/10.2151/jmsj.87.895.
Porté-Agel, F., Y. T. Wu, H. Lu, and R. J. Conzemius, 2011: Largeeddy simulation of atmospheric boundary layer flow through wind turbines and wind farms. Journal of Wind Engineering and Industrial Aerodynamics, 99, 154–168, https://doi.org/10.1016/j.jweia.2011.01.011.
Rajewski, D. A., E. S. Takle, J. K. Lundquist, J. H. Prueger, R. L. Pfeiffer, J. L. Hatfield, K. K. Spoth, and R. K. Doorenbos, 2014: Changes in fluxes of heat, H2O, and CO2 caused by a large wind farm. Agricultural and Forest Meteorology, 194, 175–187, https://doi.org/10.1016/j.agrformet.2014.03.023.
Skamarock, W. C., and Coauthors, 2008: A description of the Advanced Research WRF Version 3. NCAR Technical Note NCAR/TN 475+STR, https://doi.org/10.5065/D68S4MVH.
Smith, R. B., 2009: Gravity wave effects on wind farm efficiency. Wind Energ, 13, 449–458, https://doi.org/10.1002/we.366.
Telford, P. J., P. Braesicke, O. Morgenstern, and J. A. Pyle, 2008: Technical Note: Description and assessment of a nudged version of the new dynamics Unified Model. Atmos. Chem. Phys., 8, 1701–1712, https://doi.org/10.5194/acp-8-1701-2008.
Thompson, G., and T. Eidhammer, 2014: A study of aerosol impacts on clouds and precipitation development in a large winter cyclone. J. Atmos. Sci., 71(10), 3636–3658, https://doi.org/10.1175/JAS-D-13-0305.1.
Uhe, P., and M. Thatcher, 2015: A spectral nudging method for the ACCESS1.3 atmospheric model. Geoscientific Model Development, 8, 1645–1658, https://doi.org/10.5194/gmd-8-1645-2015.
Vanderwende, B. J., B. Kosovic, J. K. Lundquist, and J. D. Mirocha, 2016: Simulating effects of a wind-turbine array using LES and RANS. Journal of Advances in Modeling Earth Systems, 8, 1376–1390, https://doi.org/10.1002/2016 MS000652.
Volker, P. J. H., J. Badger, A. N. Hahmann, and S. Ott, 2015: The explicit wake parametrisation V1.0: A wind farm parametrisation in the mesoscale model WRF. Geoscientific Model Development, 8, 3715–3731, https://doi.org/10.5194/gmd-8-3715-2015.
Von Storch, H., H. Langenberg, and F. Feser, 2000: A spectral nudging technique for dynamical downscaling purposes. Mon. Wea. Rev., 128(10), 3664–3673, https://doi.org/10.1175/1520-0493(2000)128<3664:ASNTFD>2.0.CO;2.
Wang, C., and R. G. Prinn, 2010: Potential climatic impacts and reliability of very large-scale wind farms. Atmos. Chem. Phys., 10, 2053–2061, https://doi.org/10.5194/acp-10-2053-2010.
Wang, C., and R. G. Prinn, 2011: Potential climatic impacts and reliability of large-scale offshore wind farms. Environmental Research Letters, 6, 025101, https://doi.org/10.1088/1748-9326/6/2/025101.
Wang, Q., X. Y. Guo, and H. Takeoka, 2008: Seasonal variations of the Yellow River plume in the Bohai Sea: A model study. J. Geophys. Res., 113, C08046, https://doi.org/10.1029/2007 JC004555.
Wu, Y. T., and F. Porté-Agel, 2013: Simulation of turbulent flow inside and above wind farms: Model validation and layout effects. Bound.-Layer Meteor., 146, 181–205, https://doi.org/10.1007/s10546-012-9757-y.
Zhou, L. M., Y. H. Tian, S. Baidya Roy, C. Thorncroft, F. L. Bosart, and Y. L. Hu, 2012: Impacts of wind farms on land surface temperature. Nat. Clim. Change, 2(7), 539–543, https://doi.org/10.1038/NCLIMATE1505.
Acknowledgements
We are grateful to Dr. Xia XIAO, Dr. Jing ZHAO, Mr. Katchele F. OGOU, and all the members of our research group who are not listed as coauthors, for their helpful contributions. We thank the National Key Research and Development Program of China (Grant No. 2017YFA0604501) and the National Natural Science Foundation of China (Grant No. 41475013) for the funding support. R. J MANGARA expresses his appreciation to the CAS-TWAS President’s Fellowship and UCAS for their international PhD student sponsorship.
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Mangara, R.J., Guo, Z. & Li, S. Performance of the Wind Farm Parameterization Scheme Coupled with the Weather Research and Forecasting Model under Multiple Resolution Regimes for Simulating an Onshore Wind Farm. Adv. Atmos. Sci. 36, 119–132 (2019). https://doi.org/10.1007/s00376-018-8028-3
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DOI: https://doi.org/10.1007/s00376-018-8028-3