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Modelling the Effects of Wind Farming on the Local Weather Using Weather Research and Forecasting (WRF) Model

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Information Systems Design and Intelligent Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 863))

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Abstract

Exploitation of wind energy is rapidly growing around the world with large wind farms being set-up for the generation of electricity. It is reported in the literature that while converting the wind’s kinetic energy into electrical energy, the wind turbines may modify the transfer of energy, momentum and moisture within the atmospheric layers in the surroundings of the farms. In this work, an attempt is made to study whether the wind farm situated at Roches Noires (operational since January 2016), in the north-east part of the island of Mauritius, creates such changes within a sufficiently large space around the farm. The Weather Research and Forecasting (WRF) numerical model is employed for this endeavour due to the unavailability of measured weather data in regions close to the farm. The WRF model results are first validated with recorded meteorological data from several meteorological stations around the island and then simulations are carried out for the years 2015, 2016 and 2017. Analysis of results for two selected locations (one upstream and one downstream) around the Roches Noires wind farm demonstrates a slight decrease both in wind speed and precipitation, one year after installation of the farm.

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References

  1. AWS: Wind Resource Assessment Handbook Fundamentals for Conducting a Successful Monitoring Program (1997)

    Google Scholar 

  2. Baidya Roy, S., Pacala, S.W., Walko, R.L.: Can large wind farms affect local meteorology? J. Geophys. Res. Atmos. 109(D19) (2004)

    Google Scholar 

  3. Bilal, M., Solbakken, K., Birkelund, Y.: Wind speed and direction predictions by WRF and WindSim coupling over Nygardsfjell. J. Phys. Conf. Ser. 753(8), 082018 (2016)

    Google Scholar 

  4. Byrkjedal, O., Berge, E.: The use of WRF for wind resource mapping in Norway. In: 9th WRF Users Workshop (2008)

    Google Scholar 

  5. Carvalho, D., Rocha, A., Gómez-Gesteira, M., Santos, C.: A sensitivity study of the WRF model in wind simulation for an area of high wind energy. Environ. Model Softw. 33, 23–34 (2012)

    Google Scholar 

  6. Carvalho, D., Rocha, A., Gómez-Gesteira, M., Santos, C.S.: WRF wind simulation and wind energy production estimates forced by different reanalyses: comparison with observed data for Portugal. Appl. Energy 117, 116–126 (2014)

    Google Scholar 

  7. Chen, S.: Are wind farms changing the weather in China. South China Morning Post (2010)

    Google Scholar 

  8. ElTahan, M., & Magooda, M. (2017). Evaluation of different WRF microphysics schemes: severe rainfall over Egypt case study. https://arxiv.org/abs/1711.04163

  9. Evans, J., & McCabe, M. (2010). Regional climate simulation over Australia’s Murray-Darling basin: a multi-temporal assessment. J. Geophys. Res. D Atmos. 115(D14)

    Google Scholar 

  10. Fiedler, B., Bukovsky, M.: The effect of a giant wind farm on precipitation in a regional climate model. IOP (2011)

    Google Scholar 

  11. Guo, Z., Xiao, X.: Wind power assessment based on a WRF wind simulation with developed power curve modeling methods. Abstr. Appl. Anal. 2014 (2014)

    Google Scholar 

  12. GWEC: Wind in numbers | GWEC. [Online] Gwec.net. Available at: http://gwec.net/global-figures/wind-in-numbers/. Accessed 5 March 2018 (2017)

  13. Habtezion, B.L.: Wind Resource Assessment in Dragash-kosovo. UNDP, New York (2013)

    Google Scholar 

  14. Hahmann, A.N., Lennard, C., Badger, J., Vincent, C.L., Kelly, M., Volker, P.J., Argent, B., Refslund, J.: Mesoscale modelling for the wind atlas of South Africa (WASA) project. DTU Wind Energy 0050, 80 (2014)

    Google Scholar 

  15. Horvath, K., Koracin, D., Vellore, R., Jiang, J., Belu, R.: Sub‐kilometer dynamical downscaling of near-surface winds in complex terrain using WRF and MM5 mesoscale models. J. Geophys. Res. Atmos. 117(D11) (2012)

    Google Scholar 

  16. Larsén, X.G., Badger, J., Hahmann, A.N., Mortensen, N.G.: The selective dynamical downscaling method for extreme-wind atlases. Wind Energy 16(8), 1167–1182 (2013)

    Google Scholar 

  17. Larsén, X.G., Larsen, S., Hahmann, A.N.: Origin of the waves in a case-study of mesoscale spectra of wind and temperature, observed and simulated: Lee waves from the Norwegian mountains. Q. J. R. Meteorolog. Soc. 138(662, Part A), 274–279 (2012). https://doi.org/10.1002/qj.916

  18. Liming, Z.,Yuhong, T., Somnath Baidya, R., Chris, T.: Impacts of wind farms on land surface temperature. Nat. Clim. Change 2, 539–543 (2012)

    Google Scholar 

  19. Roy, S.B.: Simulating impacts of wind farms on local hydrometeorology. J. Wind Eng. Ind. Aerodyn. 99(4), 491–498 (2011)

    Google Scholar 

  20. Skamarock, W., Klemp, J., Dudhia, J., Gill, D., Barker, D., Duda, M., Huang, X., Wang, W., Powers, J.: A Description of the Advanced Research WRF Version 3, NCAR Technical Note, Mesoscale and Microscale Meteorology Division. National Centre for Atmospheric Research, Boulder, Colorado, USA (2008)

    Google Scholar 

  21. Storm, B., Dudhia, J., Basu, S., Swift, A., Giammanco, I.: Evaluation of the weather research and forecasting model on forecasting low-level jets: implications for wind energy. Wind Energy 12(1), 81–90 (2009)

    Google Scholar 

  22. Wang, C., Prinn, R.G.: Potential climatic impacts and reliability of very large-scale wind farms. Atmos. Chem. Phys. 10(4), 2053–2061 (2010)

    Google Scholar 

  23. Zhou, L., Tian, Y., Roy, S.B., Thorncroft, C., Bosart, L.F., Hu, Y.: Impacts of wind farms on land surface temperature. Nat. Clim. Change 2(7), 539 (2012)

    Google Scholar 

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Acknowledgements

The authors would like to thank the University of Mauritius and the University des Mascareignes for providing facilities for this research. Special thanks are extended to the Tertiary Education Commission for supporting the work of Z. Dhunny in the form of a Postdoctoral fellowship.

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Correspondence to T. S. M. Cunden .

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Jawaheer, B.O., Dhunny, A.Z., Cunden, T.S.M., Chandrasekaran, N., Lollchund, M.R. (2019). Modelling the Effects of Wind Farming on the Local Weather Using Weather Research and Forecasting (WRF) Model. In: Satapathy, S., Bhateja, V., Somanah, R., Yang, XS., Senkerik, R. (eds) Information Systems Design and Intelligent Applications. Advances in Intelligent Systems and Computing, vol 863. Springer, Singapore. https://doi.org/10.1007/978-981-13-3338-5_21

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