1. 中国科学院 大气物理研究所,北京,100029
2. 中国科学院大学 地球与行星科学学院,北京,101408
程雪玲*(1971-),女,博士,研究员,研究方向:空气动力学、大气湍流. E-mail:chengxl@mail.iap.ac.cn
纸质出版:2023
移动端阅览
程雪玲. 风能模型的发展及CFD在风资源开发利用中的应用[J]. 空气动力学学报, 2023, 41(6): 1−15.
CHENG Xueling. Development of wind energy model and application of CFD in wind energy assessment[J]. 2023, 41(6): 1-15.
程雪玲. 风能模型的发展及CFD在风资源开发利用中的应用[J]. 空气动力学学报, 2023, 41(6): 1−15. DOI: 10.7638/kqdlxxb-2023.0011
CHENG Xueling. Development of wind energy model and application of CFD in wind energy assessment[J]. 2023, 41(6): 1-15. DOI: 10.7638/kqdlxxb-2023.0011.
风能科学的发展一个很重要的方面就是从大气运动到风力发电机尺度流场的不同时空尺度运动的研究。随着计算能力的发展,计算流体力学(computational fluid dynamics
CFD)已经广泛应用于风能开发领域,使得风能模型从应用于较平坦地形的线性模型,发展到应用于复杂地形、耦合天气过程,考虑风力发电机排布、尾流效应的模型链。本文首先介绍了目前风能评估、微观选址、风功率预测模型的发展,之后详细介绍了在这些风能模型中CFD方法的改进,主要集中在中尺度到微尺度的“降尺度”、尾流模拟和复杂地形风场模拟3个方面,最后对风能模型发展过程中CFD所面临的挑战进行了展望。
A very important aspect of the development of wind energy science is the study of different spatio-temporal scale motions
from atmospheric motion to wind turbine scale flow field. With the development of computational power
the CFD simulation has been widely used in the field of wind energy assessment. The wind energy model has been developed from the linear model suitable for the flat terrain to a model chain suitable for the complex terrain
which can include weather processes
fan arrangement and wake effect. In this paper
we firstly introduce the current wind energy assessment
microscopic location
and development of wind power prediction model. Then we introduce the improvement of CFD simulation method in the wind energy models. We mainly focus on the "downscaling" from mesoscale to microscale
wake simulation and wind field simulation over complex terrain. Finally
we discuss the challenges in developing the CFD simulation in the future wind energy models.
VEERS P, DYKES K, LANTZ E, et al. Grand challenges in the science of wind energy[J]. Science, 2019, 366(6464): eaau2027. DOI: 10.1126/science.aau2027
LARSEN S E. Lectures in micro meteorology[R]. Copenhagen: DTU Wind Energy Report, 2015.
ZHANG Y, WANG J X, WANG X F. Review on probabilistic forecasting of wind power generation[J]. Renewable and Sustainable Energy Reviews, 2014, 32: 255-270. DOI: 10.1016/j.rser.2014.01.033
HONG T, PINSON P, WANG Y, et al. Energy forecasting: a review and outlook[J]. IEEE Open Access Journal of Power and Energy, 2020, 7: 376-388. DOI: 10.1109/OAJPE.2020.3029979
RODRIGO J S, GANCARSKI P, ARROYO R C, et al. IEA-Task 31 WAKEBENCH: towards a protocol for wind farm flow model evaluation. Part 1: flow-over-terrain models[J]. Journal of Physics: Conference Series, 2014, 524: 012105. DOI: 10.1088/1742-6596/524/1/012105
HAUPT S E, KOSOVIC B, ANDERSON A, et al. First year report of the A2e mesoscale to microscale coupling project[R]. PNNL-25108, 2015.
HAHMANN A N, SĪLE T, WITHA B, et al. The making of the New European Wind Atlas - Part 1: model sensitivity[J]. Geoscientific Model Development, 2020, 13(10): 5053-5078. DOI: 10.5194/gmd-13-5053-2020
ELLEN HAUPT S, KOSOVIC B, SHAW W, et al. On bridging A modeling scale gap: mesoscale to microscale coupling for wind energy[J]. Bulletin of the American Meteorological Society, 2019, 100(12): 2533-2550. DOI: 10.1175/bams-d-18-0033.1
SANZ RODRIGO J, CHÁVEZ ARROYO R A, MORIARTY P, et al. Mesoscale to microscale wind farm flow modeling and evaluation[J]. WIREs Energy and Environment, 2017, 6(2). doi: 10.1002/wene.214
SMAGORINSKY J. General circulation experiments with the primitive equations[J]. Monthly Weather Review, 1963, 91(3): 99-164. DOI: 10.1175/1520-0493(1963)0910099: gcewtp2.3.co;2
SMAGORINSKY J. Problems and promises of deterministic extended range forecasting1[J]. Bulletin of the American Meteorological Society, 1969, 50(5): 286-312. DOI: 10.1175/1520-0477-50.5.286
KASAHARA A. Various vertical coordinate systems used for numerical weather prediction[J]. Monthly Weather Review, 1974, 102(7): 509-522. DOI: 10.1175/1520-0493(1974)1020509: vvcsuf2.0.co;2
FISHER E L. A theoretical study of the sea breeze[J]. Journal of Meteorology, 1961, 18(2): 216-233. DOI: 10.1175/1520-0469(1961)0180216: atsots2.0.co;2
FOSBERG M A. Airflow over a heated coastal mountain[J]. Journal of Applied Meteorology, 1969, 8(3): 436-442. DOI: 10.1175/1520-0450(1969)0080436: aoahcm2.0.co;2
YAMADA T, MERONEY R N. Numerical and wind tunnel simulation of airflow over an obstacle[C]// National Conference on Atmospheric Waves, American Meteorological Society, Salt Lake City, 1971.
MERONEY R N, YAMADA T. Numerical and physical simulation of a stratified airflow over a series of heated islands[C]// Proc of the Summer Simulation Conference, SanDiego, California, 1972.
DEAVES D M. . Wind over hills: a numerical approach[J]. Journal of Wind Engineering and Industrial Aerodynamics, 1975, 1: 371-391. DOI: 10.1016/0167-6105(75)90031-8
MURAKAMI S. Comparison of various turbulence models applied to a bluff body[J]. Journal of Wind Engineering and Industrial Aerodynamics, 1993, 46-47: 21-36. DOI: 10.1016/0167-6105(93)90112-2
STATHOPOULOS T, BASKARAN A. Boundary treatment for the computation of three-dimensional wind flow conditions around a building[J]. Journal of Wind Engineering and Industrial Aerodynamics, 1990, 35: 177-200. DOI: 10.1016/0167-6105(90)90215-X
STATHOPOULOS T, WU H. Using computational fluid dynamics (CFD) for pedestrian winds[C]//Proc of the Structures 2004, Nashville, Tennessee, USA. Reston, VA: American Society of Civil Engineers, 2004. doi: 10.1061/40700(2004)51
WOOD G S, KWOK K C S, MOTTERAM N A, et al. Physical and numerical modelling of thunderstorm downbursts[J]. Journal of Wind Engineering and Industrial Aerodynamics, 2001, 89(6): 535-552. DOI: 10.1016/s0167-6105(00)00090-8
HANGAN H, KIM J D, XU Z. The simulation of downbursts and its challenges[C]//Proc of the Structures 2004, Nashville, Tennessee, USA. Reston, VA: American Society of Civil Engineers, 2004. doi: 10.1061/40700(2004)170
SELVAM R P, MILLETT P C. Computer modeling of tornado forces on buildings[J]. Wind and Structures, 2003, 6(3): 209-220. DOI: 10.12989/was.2003.6.3.209
RAITHBY G D, STUBLEY G D, TAYLOR P A. The Askervein hill project: a finite control volume prediction of three-dimensional flows over the hill[J]. Boundary-Layer Meteorology, 1987, 39(3): 247-267. DOI: 10.1007/BF00116121
MAURIZI A, PALMA J M L M, CASTRO F A. Numerical simulation of the atmospheric flow in a mountainous region of the North of Portugal[J]. Journal of Wind Engineering and Industrial Aerodynamics, 1998, 74-76: 219-228. DOI: 10.1016/S0167-6105(98)00019-1
CASTRO F A, SILVA SANTOS C M P, PALMA J M L M. Parallelisation of the CFD code of a CFD-NWP coupled system for the simulation of atmospheric flows over complex terrain[M]//High Performance Computing for Computational Science - VECPAR 2008. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008: 27-38. doi: 10.1007/978-3-540-92859-1_4
POPE S B. Turbulent flows[M]. Cambridge: Cambridge University Press, 2000
SPALART P R, JOU W H, STRELETS M, et al. Comments on the feasibility of LES for wings and on a hybrid RANS/LES approach[G]. Liu, C. , Liu, Z. (Eds. ), Advances in DNS/LES. Greyden, Colombus, OH, USA, 1997.
WOOD N. Wind flow over complex terrain: a historical perspective and the prospect for large-eddy modelling[J]. Boundary-Layer Meteorology, 2000, 96(1): 11-32. DOI: 10.1023/A: 1002017732694
PIOMELLI U, BALARAS E. Wall-layer models for large-eddy simulations[J]. Annu. Rev. Fluid Mech. , 2002, 34: 349–374.
, PALMA J M, CASTRO F A. Simulation of the askervein flow. part 2: large-eddy simulations[J]. Boundary-Layer Meteorology, 2007, 125(1): 85-108. DOI: 10.1007/s10546-007-9195-4
JACKSON P S, HUNT J C R. Turbulent wind flow over a low hill[J]. Quarterly Journal of the Royal Meteorological Society, 1975, 101(430): 929-955. DOI: 10.1002/qj.49710143015
KAIMAL J C, FINNIGAN J J. Atmospheric boundary layer flows: their structure and measurement[M]. New York: Oxford University Press, 1994
BELJAARS A M, WALMSLEY J L, TAYLOR P A. A mixed spectral finite-difference model for neutrally stratified boundary-layer flow over roughness changes and topography[J]. Boundary-Layer Meteorology, 1987, 38(3): 273-303. DOI: 10.1007/BF00122448
MORTENSEN N G, LANDBERG L. Wind altas analysis and application program (WAsP) user’s guide[R]. Roskilde, Denmark, Risø National Laboratory, 1993, pp133.
OTT S, NIELSEN M. Developments of the offshore wind turbine wake model Fuga[R]. DTU Wind Energy E-0046, Technical University of Denmark, Denmark, 2014.
CHENG X L, HU F. The study of grid formation on complex terrain[J]. Chinese Journal of Computational Mechanics, 2006, 23(3): 313-316. DOI: 10.3969/j.issn.1007-4708.2006.03.011(in Chinese)
ZHOU Z Y, XIAO L, DING Q S, et al. Numerical simulation study of wind environment for the flow around large region with complex terrain[J]. Chinese Quarterly of Mechanics, 2010, 31(1): 101-107. DOI: 10.13774/j.cnki.kjtb.2018.08.048(in Chinese)
BITSUAMLAK G T, STATHOPOULOS T, BÉDARD C. Numerical evaluation of wind flow over complex terrain: review[J]. Journal of Aerospace Engineering, 2004, 17(4): 135-145. DOI: 10.1061/(asce)0893-1321(2004)17: 4(135)
STANGROOM P. CFD modeling of wind flow over terrain[D]. Thesis for the degree of PhD, the University of Nottingham, 2004.
BECHMANN A. Large eddy simulation of atmospheric flow over complex terrain[D]. Thesis for the degree of PhD, Ris National Laboratory, Technical University of Denmark, 2006.
LIANG S C, ZHANG X D, KANG S. Simulation method of flow over complex terrain[J]. Journal of Engineering Thermophysics, 2011, 32(6): 945-948. . DOI: 10.1016/j.jweia.2008.12.001(in Chinese)
CATTIN R, SCHAFFNER B, KUNZ S. Validation of CFD wind resource modeling in highly complex terrain[J]. European Wind Energy Conference and Exhibition 2006, EWEC 2006, 2006, 1: 36-46.
THOGERSEN M L, NIELSEN P, MADS V S, et al. Applying new computer-aided tools for wind farm planning and environmental impact analysis[C]// 2003 European Wind Energy Conference Exhibition, CD 2, Madrid, Spain, 2003.
OZERDEM B, TURKELI H M. Wind energy potential estimation and micrositting on Izmir Institute of Technology Campus, Turkey[J]. Renewable Energy, 2005, 30(10): 1623-1633. DOI: 10.1016/j.renene.2004.11.010
WANG Y, SMITH G M, SCHLEZ W. Recent developments in precision wind farm modelling[C]// Asian Wind Energy Conference Exhibition, Beijing, 2006.
DELAUNAY D, CHANTELOT A, GUYADER T, et al. Meteodyn WT: a software for wind resource assessment in complex terrain[C]// European Wind Energy Conference, London, UK, 2004.
BERGE E, GRAVDAHL A R, SCHELLING J, et al. Wind in complex terrain. A comparison of WAsP and two CFD-models[J]. European Wind Energy Conference and Exhibition 2006, EWEC 2006, 2006, 2: 1569-1577.
PEREIRA S R, GUEDES R, SANTOS C S. Comparing WAsP and CFD wind resource estimates for the “regular” user[J]. European Wind Energy Conference Exhibition 2010, 2010: 1-10.
VANLUVANEE D, ROGERS T, RANDALL G. Comparison of WAsP, MS-Micro/3, CFD, NWP, and analytical methods for estimating site-wide wind speeds[C]// Presentation from AWEA Wind Resource Assessment Workshop, Minneapolis, MN, 2009.
SUMNER J, WATTERS C S, MASSON C. CFD in wind energy: the virtual, multiscale wind tunnel[J]. Energies, 2010, 3(5): 989-1013. DOI: 10.3390/en3050989
THUNIS P, BORNSTEIN R. Hierarchy of mesoscale flow assumptions and equations[J]. Journal of the Atmospheric Sciences, 1996, 53(3): 380-397. DOI: 10.1175/1520-0469(1996)0530380: homfaa2.0.co;2
FINARDI S, MORSELLI M G, JEANNET P, et al. Wind flow models over complex terrain for dispersion calculations[R]. COST Action 710: Pre-processing of Meteorological Data for Dispersion Models, Report of Working Group 4, 1997.
TAYLOR P A, WALMSLEY J L, SALMON J R. A simple model of neutrally stratified boundary-layer flow over real terrain incorporating wavenumber-dependent scaling[J]. Boundary-Layer Meteorology, 1983, 26(2): 169-189. DOI: 10.1007/BF00121541
AYOTTE K W, TAYLOR P A. A mixed spectral finite-difference 3D model of neutral planetary boundary-layer flow over topography[J]. Journal of the Atmospheric Sciences, 1995, 52(20): 3523-3538. DOI: 10.1175/1520-0469(1995)0523523: amsfdm2.0.co;2
BROWER M. Validation of the WindMap program and development of MesoMap[C]//Proceeding from AWEA's WindPower conference. Washington, DC, USA, 1999.
SCIRE J S, ROBE F R, FERNAU M E, et al. A user's guide for the CALMET meteorological model (version 5)[R]. Report from Earth Tech, Inc. , Concord, Massachusetts, USA, 2000, pp332.
FRANK H P, LANDBERG L. Modelling the wind climate of Ireland[J]. Boundary-Layer Meteorology, 1997, 85(3): 359-377. DOI: 10.1023/A: 1000552601288
REED R, BROWER M, KREISELMAN J. Comparing SiteWind with standard models for energy output estimation[C]// Proceedings from EWEC, London, UK, 2004.
YU W, BENOIT R, GIRARD C, et al. Wind energy simulation toolkit (WEST): a wind mapping system for use by the wind-energy industry[J]. Wind Engineering, 2006, 30(1): 15-33. DOI: 10.1260/030952406777641450
ZHU R, HE X F, ZHOU R W, et al. Numerical simulation evaluation method of regional wind energy resources[J]. Wind Energy, 2010(6): 50-54. (in Chinese)
ZHOU R W, HE X F, ZHU R. Application of MM5/calmet model system in wind energy resource assessment[J]. Journal of Natural Resources, 2010, 25(12): 2101-2113. . DOI: 10.3321/j.issn: 0254-0096.2007.06.019(in Chinese)
LANGE M, FOCKEN U. Physical wind power prediction systems[M]//Physical Approach to Short-Term Wind Power Prediction. Berlin/Heidelberg: Springer-Verlag, 2006: 39-53. doi: 10.1007/3-540-31106-8_4
LI L, ZHANG L J, ZHANG N, et al. Application of FLUENT in fine simulation of complex terrain wind field[J]. Plateau Meteorology, 2010, 29(3): 621-628. DOI: 10.3321/j.issn: 1000-0534.2007.03.014(in Chinese)
HE X F, ZHOU R W, ZHU R. A study on wind resources in complex terrain simulated by the combination of MM5 and CFD software[J]. Resources Science, 2010, 32(4): 650-655. DOI: 10.3969/j.issn.1673-7148.2008.02.008(in Chinese)
FANG Y Y, XU H M, ZHU R, et al. Study on numerical simulation of wind energy resources based on WRF and CFD models[J]. Meteorological Monthly, 2012, 38(11): 1378-1389. (in Chinese)
CHENG X L, HU F, ZENG Q C. Refined numerical simulation of complex terrain flow field[J]. Climatic and Environmental Research, 2015, 20(1): 1-10. DOI: 10.3878/j.issn.1006-9585.2014.13225(in Chinese)
MA W T, ZHU R, LI Z C, et al. Study of the short-term wind power forecasting method for complex terrain wind farm based on the CFD dynamical downscalling[J]. Acta Meteorologica Sinica, 2016, 74(1): 89-102. DOI: 10.11755/j.issn.1006-7639(2014)-06-1015(in Chinese)
DEARDORFF J W. Numerical investigation of neutral and unstable planetary boundary layers[J]. Journal of the Atmospheric Sciences, 1972, 29(1): 91-115. DOI: 10.1175/1520-0469(1972)0290091: nionau2.0.co;2
MOENG C H. A large-eddy-simulation model for the study of planetary boundary-layer turbulence[J]. Journal of the Atmospheric Sciences, 1984, 41(13): 2052-2062. DOI: 10.1175/1520-0469(1984)0412052: alesmf2.0.co;2
MASON P J. Large-eddy simulation: a critical review of the technique[J]. Quarterly Journal of the Royal Meteorological Society, 1994, 120(515): 1-26. DOI: 10.1002/qj.49712051503
MARJANOVIC N, CHOW F K. Mesoscale and large-eddy simulations for wind energy[R]. LLNL-SR-471624, Berkeley, CA, USA, 2011.
TALBOT C, BOU-ZEID E, SMITH J. Nested mesoscale large-eddy simulations with WRF: performance in real test cases[J]. Journal of Hydrometeorology, 2012, 13(5): 1421-1441. DOI: 10.1175/jhm-d-11-048.1
BRETON S P, SUMNER J, SØRENSEN J N, et al. A survey of modelling methods for high-fidelity wind farm simulations using large eddy simulation[J]. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 2017, 375(2091): 20160097. DOI: 10.1098/rsta.2016.0097
MIROCHA J D, CHURCHFIELD M J, MUÑOZ-ESPARZA D, et al. Large-eddy simulation sensitivities to variations of configuration and forcing parameters in canonical boundary-layer flows for wind energy applications[J]. Wind Energy Science, 2018, 3(2): 589-613. DOI: 10.5194/wes-3-589-2018
YUBAO, LIU, . Simultaneous nested modeling from the synoptic scale to the LES scale for wind energy applications[J]. Journal of Wind Engineering and Industrial Aerodynamics, 2011, 99(4): 308-319. DOI: 10.1016/j.jweia.2011.01.013
BERG J, MANN J, BECHMANN A, et al. The bolund experiment, part I: flow over a steep, three-dimensional hill[J]. Boundary-Layer Meteorology, 2011, 141(2): 219-243. DOI: 10.1007/s10546-011-9636-y
BECHMANN A, SØRENSEN N N, BERG J, et al. The bolund experiment, part II: blind comparison of microscale flow models[J]. Boundary-Layer Meteorology, 2011, 141(2): 245-271. DOI: 10.1007/s10546-011-9637-x
BEAUCAGE P, BROWER M C, TENSEN J. Evaluation of four numerical wind flow models for wind resource mapping[J]. Wind Energy, 2014, 17(2): 197-208. DOI: 10.1002/we.1568
BEAUCAGE P, BROWER M C. Wind flow modeling performance[R]. AWS Truepower, New York, 2012.
TROEN I, LANDBERG L. Short term prediction of local wind conditions[C]// Proc of European community wind energy conference, Madrid, Spain, 1990.
LI J. Fine evaluation of wind energy resources in complex terrain and wind power forecast[D]. Beijing: University of Chinese Academy of Sciences, 2012. (in Chinese)
MARITI I, NIELSEN T, MADSEN H, et al. Prediction models in complex terrain[C]//Proc of European wind energy conference, Copenhagen, 2001.
SUN C Y. Research on short-term forecasting technology of wind power in wind farm[D]. Lanzhou: Lanzhou University (in Chinese).
KARINIOTAKIS G. , HALLIDAY J, BROWNSWORD R, et al. Next generation short-term forecasting of wind power – overview of the ANEMOS project[C]// Proc of the European Wind Energy Conference EWEC’06, Athens, Greece, 2006.
JURSA R. Wind power prediction with different artificial intelligence models[C]//Proc of the European Wind Energy Conference EWEC’07, Milan, Italy, 2007.
FUGON L, JUBAN J, KARINIOTAKIS G. Data mining for wind power forecasting[C]//Proc of the European Wind Energy Conference EWEC’08, Brussels, Belgium, 2008.
SANTOSO S, NEGNEVITSKY M, HATZIARGYRIOU N. Data mining and analysis techniques in wind power system applications: abridged[C]//Proc of the 2006 IEEE Power Engineering Society General Meeting, Montreal, QC, Canada. IEEE, 2006: 3pp. doi: 10.1109/PES.2006.1709356
ZHANG Y, YANG S P, GUO Z H, et al. Wind speed forecasting based on wavelet decomposition and wavelet neural networks optimized by the Cuckoo search algorithm[J]. Atmospheric and Oceanic Science Letters, 2019, 12(2): 107-115. DOI: 10.1080/16742834.2019.1569455
ELLEN HAUPT S, MCCANDLESS T C, DETTLING S, et al. Combining artificial intelligence with physics-based methods for probabilistic renewable energy forecasting[J]. Energies, 2020, 13(8): 1979. DOI: 10.3390/en13081979
LANDBERG L, GIEBEL G, NIELSEN H A, et al. Short-term Prediction? An overview[J]. Wind Energy, 2003, 6(3): 273-280. DOI: 10.1002/we.96
MONTEIRO C, BESSA R, MIRANDA V, et al. Wind power forecasting: state-of-the-art 2009[R]. Decision and Information Science Division, Argonne National Laboratory, 2009.
FOLEY A M, LEAHY P G, MARVUGLIA A, et al. Current methods and advances in forecasting of wind power generation[J]. Renewable Energy, 2012, 37(1): 1-8. DOI: 10.1016/j.renene.2011.05.033
JUNG J, BROADWATER R P. Current status and future advances for wind speed and power forecasting[J]. Renewable and Sustainable Energy Reviews, 2014, 31: 762-777. DOI: 10.1016/j.rser.2013.12.054
ROHRIG K, BERKHOUT V, CALLIES D, et al. Powering the 21st century by wind energy—Options, facts, figures[J]. Applied Physics Reviews, 2019, 6(3): 031303. DOI: 10.1063/1.5089877
WANG W S, WANG Z, DONG C, et al. Status and error analysis of short-term forecasting technology of wind power in China[J]. Automation of Electric Power Systems, 2021, 45(1): 17-27. . DOI: 10.7500/AEPS20200324003(in Chinese)
PETERSEN E L, MORTENSEN N G, LANDBERG L, et al. Wind power meteorology. Part I: climate and turbulence[J]. Wind Energy, 1998, 1(1): 2-22. DOI: 10.1002/(sici)1099-1824(199809)1: 12: aid-we153.0.co;2-y
JORGENSEN B H, HANSEN A, MYLLERUP L, et al. Computational wind power meteorology in complex terrain compared to measurements[C]//2004 European Wind Energy Conference and Exhibition, London, United Kingdom, 2005.
LANGE B. Offshore wind power meteorology[M]//Wind Energy. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007: 1-6. doi: 10.1007/978-3-540-33866-6_1
EMEIS S. Wind Energy Meteorology: atmospheric physics for wind power generation[M]. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. doi: 10.1007/978-3-642-30523-8
EMEIS S. Current issues in wind energy meteorology[J]. Meteorological Applications, 2014, 21(4): 803-819. DOI: 10.1002/met.1472
HOLTSLAG A A M, SVENSSON G, BAAS P, et al. Stable atmospheric boundary layers and diurnal cycles: challenges for weather and climate models[J]. Bulletin of the American Meteorological Society, 2013, 94(11): 1691-1706. DOI: 10.1175/bams-d-11-00187.1
HAUPT S E, BERG L, CHURCHFIELD M, et al. Mesoscale to microscale coupling for wind energy applications: addressing the challenges[J]. Journal of Physics: Conference Series, 2020, 1452(1): 012076. DOI: 10.1088/1742-6596/1452/1/012076
SANZ RODRIGO J, CHURCHFIELD M, KOSOVIC B. A methodology for the design and testing of atmospheric boundary layer models for wind energy applications[J]. Wind Energy Science, 2017, 2(1): 35-54. DOI: 10.5194/wes-2-35-2017
WANG Tongguang, TIAN Linlin, ZHONG Wei, et al. Aerodynamic research progress in wind energy Ⅱ: Inflow and wake characteristics[J]. Acta Aerodynamica Sinica, 2022, 40(4): 22-50. DOI: 10.7638/kqdlxxb-2021.0390
MARTÍ I, SAN ISIDRO M J, CABEZÓN D, et al. Wind power prediction in complex terrain: from the synoptic scale to the local scale[J]. Proceedings of the Science of Making Torque from Wind, 2004: 316-327.
-T MENGELKAMP H. Wind climate simulation over complex terrain and wind turbine energy output estimation[J]. Theoretical and Applied Climatology, 1999, 63(3): 129-139. DOI: 10.1007/s007040050098
SANDERSE B, PIJL S P, KOREN B. Review of computational fluid dynamics for wind turbine wake aerodynamics[J]. Wind Energy, 2011, 14(7): 799-819.
SCHULZ C, KLEIN L, WEIHING P, et al. CFD studies on wind turbines in complex terrain under atmospheric inflow conditions[J]. Journal of Physics: Conference Series, 2014, 524: 012134.
MAKRIDIS A, CHICK J. Validation of a CFD model of wind turbine wakes with terrain effects[J]. Journal of Wind Engineering and Industrial Aerodynamics, 2013, 123: 12-29.
JIMENEZ A, CRESPO A, MIGOYA E, et al. Advances in large-eddy simulation of a wind turbine wake[J]. Journal of Physics: Conference Series, 2007, 75: 012041. DOI: 10.1088/1742-6596/75/1/012041
CALAF M, MENEVEAU C, MEYERS J. Large eddy simulation study of fully developed wind-turbine array boundary layers[J]. Physics of Fluids, 2010, 22(1): 015110. DOI: 10.1063/1.3291077
SCHRECK S. The NREL full-scale wind tunnel experiment Introduction to the special issue[J]. Wind Energy, 2002, 5(2-3): 77-84. DOI: 10.1002/we.72
SONG Y L. Investigations into atmospheric stability and its impact on wind turbine wave daily cycle evolution[D]. Nanjing: Nanjing University of Aeronautics and Astronautics, 2022.
STOREY R C, NORRIS S E, STOL K A, et al. Large eddy simulation of dynamically controlled wind turbines in an offshore environment[J]. Wind Energy, 2013, 16(6): 845-864. DOI: 10.1002/we.1525
GUO N Z, ZHANG M M, LI B. A data-driven analytical model for wind turbine wakes using machine learning method[J]. Energy Conversion and Management, 2022, 252: 115130. DOI: 10.1016/j.enconman.2021.115130
TABIB M, RASHEED A, FUCHS F. Analyzing complex wake-terrain interactions and its implications on wind-farm performance[J]. Journal of Physics: Conference Series, 2016, 753: 032063. DOI: 10.1088/1742-6596/753/3/032063
VAN DER LAAN M P, SØRENSEN N N, RÉTHORÉ P E, et al. The k - ε - f P model applied to double wind turbine wakes using different actuator disk force methods[J ] . Wind Energy, 2015, 18(12): 2223-2240. DOI: 10.1002/we.1816
HANSEN K S, RÉTHORÉ P E, PALMA J, et al. Simulation of wake effects between two wind farms[J]. Journal of Physics: Conference Series, 2015, 625: 012008. DOI: 10.1088/1742-6596/625/1/012008
PORTÉ-AGEL F, BASTANKHAH M, SHAMSODDIN S. Wind-turbine and wind-farm flows: a review[J]. Boundary-Layer Meteorology, 2020, 174(1): 1-59. DOI: 10.1007/s10546-019-00473-0
LANDBERG L, MYLLERUP L, RATHMANN O, et al. Wind resource estimation-an overview[J]. Wind Energy, 2003, 6(3): 261-271. DOI: 10.1002/we.94
AYOTTE K W, HUGHES D E. Observations of boundary-layer wind-tunnel flow over isolated ridges of varying steepness and roughness[J]. Boundary-Layer Meteorology, 2004, 112(3): 525-556. DOI: 10.1023/B: BOUN.0000030663.13477.51
S, FINARDI, . Evaluation of different wind field modeling techniques for wind energy applications over complex topography[J]. Journal of Wind Engineering and Industrial Aerodynamics, 1998, 74-76: 283-294. DOI: 10.1016/S0167-6105(98)00025-7
BERNHARD, LANGE, . Evaluation of the wind-resource estimation program WAsP for offshore applications[J]. Journal of Wind Engineering and Industrial Aerodynamics, 2001, 89(3-4): 271-291. DOI: 10.1016/S0167-6105(00)00082-9
SHUZO, MURAKAMI, . Development of local area wind prediction system for selecting suitable site for windmill[J]. Journal of Wind Engineering and Industrial Aerodynamics, 2003, 91(12-15): 1759-1776. DOI: 10.1016/j.jweia.2003.09.040
, PALMA, . Linear and nonlinear models in wind resource assessment and wind turbine micro-siting in complex terrain[J]. Journal of Wind Engineering and Industrial Aerodynamics, 2008, 96(12): 2308-2326. DOI: 10.1016/j.jweia.2008.03.012
SADEK R, SOULHAC L, BROCHETON F, et al. Evaluation of wind field and dispersion models in the presence of complex terrain[C]//14th Conference on Harmonisation within Atmospheric Dispersion Modelling for Regulatory Purposes, Kos, Greece, 2011.
HRISTOV Y, OXLEY G, ŽAGAR M. Improvement of AEP predictions using diurnal CFD modelling with site-specific stability weightings provided from mesoscale simulation[J]. Journal of Physics: Conference Series, 2014, 524: 012116. DOI: 10.1088/1742-6596/524/1/012116
SOGACHEV A, KELLY M, LECLERC M Y. Consistent two-equation closure modelling for atmospheric research: buoyancy and vegetation implementations[J]. Boundary-Layer Meteorology, 2012, 145(2): 307-327. DOI: 10.1007/s10546-012-9726-5
KOBLITZ T. CFD simulation of non-neutral atmospheric boundary layer conditions[D]. PhD thesis, DTU Institute for Wind Energy, 2013.
CASTRO F A, PALMA J M L M, SILVA LOPES A. Simulation of the askervein flow. part 1: Reynolds averaged N-S equations (k∈ turbulence model)[J]. Boundary-Layer Meteorology, 2003, 107(3): 501-530. DOI: 10.1023/A: 1022818327584
AVILA M, FOLCH A, HOUZEAUX G, et al. A parallel CFD model for wind farms[J]. Procedia Computer Science, 2013, 18: 2157-2166. DOI: 10.1016/j.procs.2013.05.386
MENEVEAU C. Big wind power: seven questions for turbulence research[J]. Journal of Turbulence, 2019, 20(1): 2-20. DOI: 10.1080/14685248.2019.1584664
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