Abstract
In this paper, an urban environmental wind field distribution around the wind turbine is numerically investigated by using ANSYS Fluent with the k–ω SST turbulence model. A computational domain designed with an octagonal prism shape is used to simulate wind from eight different directions. As a case study, the wind field and wind power output at the location of the 850 kW wind turbine in the Dundalk Institute of Technology campus are analyzed. The simulated inlet wind speeds adopted are 6 m/s, 12 m/s, 14 m/s, and 22 m/s. The simulation results show that, at both high and low wind speeds, specific wind directions would generate wakes behind tall narrow buildings and affect the wind speed at the location of the wind turbine. The local acceleration of the wind speed could only occur next to buildings. Moreover, in a low-speed southwesterly wind, the wind speed at the location of the wind turbine will be significantly reduced due to the presence of low-wide buildings. When the wind of 14 m/s comes from the south–east direction and the wind of 6 m/s comes from the north–east direction, the maximum percentage changes in wind speed and power output are − 2.41% and − 5.59%, respectively.
Similar content being viewed by others
Data availability
The data used to support the findings of this study are available from the corresponding author upon request.
References
Porte-Agel, F., Bastankhah, M., Shamsoddin, S.: Wind-turbine and wind-farm flows: a review. Bound. Layer Meteorol. 174, 1–59 (2020). https://doi.org/10.1007/s10546-019-00473-0
Olabi, A.G., Wilberforce, T., Elsaid, K., Salameh, T., Sayed, E.T., Husain, K.S., Abdelkareem, M.A.: Selection guidelines for wind energy technologies. Energies 14, 3244 (2021). https://doi.org/10.3390/en14113244
Chaudhuri, A., Datta, R., Kumar, M.P., Davim, J.P., Pramanik, S.: Energy conversion strategies for wind energy system: electrical, mechanical and material aspects. Materials 15, 1232 (2022). https://doi.org/10.3390/ma15031232
Díaz, H., Guedes Soares, C.: Review of the current status, technology and future trends of offshore wind farms. Ocean Eng. 209, 107381 (2020). https://doi.org/10.1016/j.oceaneng.2020.107381
Farrugia, R.N., Sant, T.: Modelling wind speeds for cup anemometers mounted on opposite sides of a lattice tower: a case study. J. Wind Eng. Ind. Aerodyn. 115, 173–183 (2013). https://doi.org/10.1016/j.jweia.2012.11.006
Baseer, M.A., Meyer, J.P., Rehman, S., Mahbub Alam, Md., Al-Hadhrami, L.M., Lashin, A.: Performance evaluation of cup-anemometers and wind speed characteristics analysis. Renew. Energy 86, 733–744 (2016). https://doi.org/10.1016/j.renene.2015.08.062
Hanslian, D., Hosek, J.: Combining the VAS 3D interpolation method and wind atlas methodology to produce a high-resolution wind resource map for the Czech Republic. Renew. Energy 77, 291–299 (2015). https://doi.org/10.1016/j.renene.2014.12.013
Ozelkan, E., Chen, G., Ustundag, B.B.: Spatial estimation of wind speed: a new integrative model using inverse distance weighting and power law. Int. J. Digit. Earth 9, 733–747 (2016). https://doi.org/10.1080/17538947.2015.1127437
Cheynet, E., Jakobsen, J.B., Snæbjörnsson, J., Reuder, J., Kumer, V., Svardal, B.: Assessing the potential of a commercial pulsed lidar for wind characterisation at a bridge site. J. Wind Eng. Ind. Aerodyn. 161, 17–26 (2017). https://doi.org/10.1016/j.jweia.2016.12.002
Rehman, S., Mohandes, M.A., Alhems, L.M.: Wind speed and power characteristics using LiDAR anemometer based measurements. Sustain. Energy Technol. Assess. 27, 46–62 (2018). https://doi.org/10.1016/j.seta.2018.03.009
Dai, L.D., Xin, J.Y., Zuo, H.C., Ma, Y.X., Zhang, L., Wu, X.R., Ma, Y.J., Jia, D.J., Wu, F.K.: Multilevel validation of doppler wind lidar by the 325 m meteorological tower in the planetary boundary layer of Beijing. Atmosphere 11, 1051 (2020). https://doi.org/10.3390/atmos11101051
Kogaki, T., Sakurai, K., Shimada, S., Kawabata, H., Otake, Y., Kondo, K., Fujita, E.: Field measurements of wind characteristics using lidar on a wind farm with downwind turbines installed in a complex terrain region. Energies 13, 5135 (2020). https://doi.org/10.3390/en13195135
Lang, S., McKeogh, E.: LIDAR and SODAR measurements of wind speed and direction in upland terrain for wind energy purposes. Remote Sens. 3, 1871–1901 (2011). https://doi.org/10.3390/rs3091871
El Kasmi, A., Masson, C.: Turbulence modeling of atmospheric boundary layer flow over complex terrain: a comparison of models at wind tunnel and full scale. Wind Energy 13, 689–704 (2010). https://doi.org/10.1002/we.390
Mattuella, J.M.L., Loredo-Souza, A.M., Oliveira, M.G.K., Petry, A.P.: Wind tunnel experimental analysis of a complex terrain micrositing. Renew. Sust. Energy Rev. 54, 110–119 (2016). https://doi.org/10.1016/j.rser.2015.09.088
Wang, Z., Zou, Y.F., Yue, P., He, X.H., Liu, L.L., Luo, X.Y.: Effect of topography truncation on experimental simulation of flow over complex terrain. Appl. Sci. 12, 2477 (2022). https://doi.org/10.3390/app12052477
Dhunny, A.Z., Lollchund, M.R., Rughooputh, S.D.D.V.: A high-resolution mapping of wind energy potentials for Mauritius using computational fluid dynamics (CFD). Wind Struct. Int. J. 20, 565578 (2015). https://doi.org/10.12989/was.2015.20.4.565
Yan, B.W., Li, Q.S.: Coupled on-site measurement/CFD based approach for high-resolution wind resource assessment over complex terrains. Energy Convers. Manag. 117, 351–366 (2016). https://doi.org/10.1016/j.enconman.2016.02.076
Sessarego, M., Shen, W.Z., van der Laan, M.P., Hansen, K.S., Zhu, W.J.: CFD simulations of flows in a wind farm in complex terrain and comparisons to measurements. Appl. Sci. 8, 788 (2018). https://doi.org/10.3390/app8050788
Blocken, B., van der Hout, A., Dekker, J., Weiler, O.: CFD simulation of wind flow over natural complex terrain: case study with validation by field measurements for Ria de Ferrol, Galicia Spain. J. Wind Eng. Ind. Aerodyn. 147, 43–57 (2015). https://doi.org/10.1016/j.jweia.2015.09.007
Huang, W.F., Zhang, X.B.: Wind field simulation over complex terrain under different inflow wind directions. Wind Struct. Int. J. 28, 239–253 (2019). https://doi.org/10.12989/was.2019.28.4.239
Tse, K.T., Li, S.W., Fung, J.C.H.: A comparative study of typhoon wind profiles derived from field measurements, meso-scale numerical simulations, and wind tunnel physical modeling. J. Wind Eng. Ind. Aerodyn. 131, 46–58 (2014). https://doi.org/10.1016/j.jweia.2014.05.001
Niyomtham, L., Lertsathittanakorn, C., Waewsak, J., Gagnon, Y.: Mesoscale/microscale and CFD modeling for wind resource assessment: application to the Andaman Coast of Southern Thailand. Energies 15, 3025 (2022). https://doi.org/10.3390/en15093025
Toparlar, Y., Blocken, B., Maiheu, B., van Heijst, G.J.F.: A review on the CFD analysis of urban microclimate. Renew. Sustain. Energy Rev. 80, 1613–1640 (2017). https://doi.org/10.1016/j.rser.2017.05.248
Ramponi, R., Blocken, B., de Coo, L.B., Janssen, W.D.: CFD simulation of outdoor ventilation of generic urban configurations with different urban densities and equal and unequal street widths. Build. Environ. 92, 152–166 (2015). https://doi.org/10.1016/j.buildenv.2015.04.018
Toja-Silva, F., Kono, T., Peralta, C., Lopez-Garcia, O., Chen, J.: A review of computational fluid dynamics (CFD) simulations of the wind flow around buildings for urban wind energy exploitation. J. Wind Eng. Ind. Aerodyn. 180, 66–87 (2018). https://doi.org/10.1016/j.jweia.2018.07.010
Yang, A.-S., Su, Y.-M., Wen, C.-Y., Juan, Y.-H., Wang, W.-S., Cheng, C.-H.: Estimation of wind power generation in dense urban area. Appl. Energy 171, 213–230 (2016). https://doi.org/10.1016/j.apenergy.2016.03.007
Ku, C.-A., Tsai, H.-K.: Evaluating the influence of urban morphology on urban wind environment based on computational fluid dynamics simulation. ISPRS Int. J. Geo-Inf. 9, 399 (2020). https://doi.org/10.3390/ijgi9060399
Kalmikov, A., Dupont, G., Dykes, K., Chan, C.: Wind power resource assessment in complex urban environments: MIT campus case-study using CFD analysis. In: Proceedings of the AWEA 2010 WINDPOWER Conference, Dallas, TX, USA, 23–26 May 2010
Jamdade, P.G., Jamdade, S.G.: Evaluation of wind energy potential for four sites in Ireland using the Weibull distribution model. J. Power Technol. 95, 48–53 (2015)
Cooney, C., Byrne, R., Lyons, W.: Performance characterisation of a commercial-scale wind turbine operating in an urban environment, using real data. Energy Sustain. 36, 44–54 (2017). https://doi.org/10.1016/j.esd.2016.11.001
Byrne, R., Hewitt, N.J., Grif, P., Macartain, P.: Observed site obstacle impacts on the energy performance of a large scale urban wind turbine using an electrical energy rose. Energy Sustain. Dev. 43, 23–37 (2018). https://doi.org/10.1016/j.esd.2017.12.002
Byrne, R., Hewitt, N.J., Griffiths, P., MacArtain, P.: An assessment of the mesoscale to microscale influences on wind turbine energy performance at a peri-urban coastal location from the Irish wind atlas and onsite LiDAR measurements. Sustain. Energy Technol. Assess. 36, 100537 (2019). https://doi.org/10.1016/j.seta.2019.100537
Vestas Wind Systems: V52-850 kW the turbine that goes anywhere. https://users.wpi.edu/~cfurlong/me3320/DProject/V52_850kW_US.pdf (2005)
Acknowledgements
The authors also wish to acknowledge the support of the INTERREG VA SPIRE2 project. This research was supported by the European Union's INTERREG VA Programme (Grant No. INT-VA/049), managed by the Special EU Programmes Body (SEUPB). The views and opinions expressed in this document do not necessarily reflect those of the European Commission or the Special EU Programmes Body (SEUPB). The authors also acknowledge the Research Office at Dundalk Institute of Technology. The authors also acknowledge IEA Wind Task 41, Enabling wind to contribute to a distributed energy future.
Funding
This work was supported by the Ministry of Science and Technology, Taiwan (Grant Number 108-3116-F-042A-006-).
Author information
Authors and Affiliations
Contributions
Y-TL and RB conceptualized the study. Y-CC, Y-TL, and HCW conducted laboratory works, provided the statistics, processed the data and fulfilled the analysis, wrote the draft. HCW provided software and performed the analysis supervision, draft writing supervision. RB and P-HC performed the analysis supervision, final manuscript writing and editing. All authors read and approved the final manuscript.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare they have no competing interests.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Chien, YC., Lin, YT., Weng, H.C. et al. Influence of nearby urban buildings on the wind field around a wind turbine: a case study in Dundalk Institute of Technology. Int J Energy Environ Eng 14, 511–524 (2023). https://doi.org/10.1007/s40095-022-00531-3
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s40095-022-00531-3