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Exploring the suitability of MERRA-2 reanalysis data for wind energy estimation, analysis of wind characteristics and energy potential assessment for selected sites in Pakistan

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  • Rabbani, R.
  • Zeeshan, M.

Abstract

In the first part of this study, correlation between MERRA-2 reanalysis wind data and ground data is assessed for 12 selected locations. The correlation coefficient ranges from 0.17 to 0.75 among the sites. Sites with higher average wind speeds show comparatively stronger correlation. Besides, site specific factors are also investigated. In the second part, wind energy potential at same 12 locations is evaluated using high frequency (10-min interval) ground observed data. The diurnal, monthly and annual means for the sites are calculated and wind speed variance is observed utilizing wind data at six altitude levels (10m, 20m, 40m, 50m, 60m and 80m). The data is fitted to the Weibull distribution. Most probable wind speeds, wind speeds carrying maximum energy and wind power densities for all the locations are calculated for 50m and 80m height wind data. Significant variation of wind power density is observed along the height. A low cut-in speed wind turbine is selected, and annual energy production and capacity factors are estimated. Four locations with high wind power densities, namely Sujawal (355.6 W/m2), Sanghar (312.9 W/m2), Tando Ghulam Ali (288.2 W/m2) and Umerkot (252.8 W/m2) showed good potential to add wind share to global energy mix.

Suggested Citation

  • Rabbani, R. & Zeeshan, M., 2020. "Exploring the suitability of MERRA-2 reanalysis data for wind energy estimation, analysis of wind characteristics and energy potential assessment for selected sites in Pakistan," Renewable Energy, Elsevier, vol. 154(C), pages 1240-1251.
    • Handle: RePEc:eee:renene:v:154:y:2020:i:c:p:1240-1251
    DOI: 10.1016/j.renene.2020.03.100
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    as
    1. Fagbenle, R.O. & Katende, J. & Ajayi, O.O. & Okeniyi, J.O., 2011. "Assessment of wind energy potential of two sites in North-East, Nigeria," Renewable Energy, Elsevier, vol. 36(4), pages 1277-1283.
    2. Wais, Piotr, 2017. "Two and three-parameter Weibull distribution in available wind power analysis," Renewable Energy, Elsevier, vol. 103(C), pages 15-29.
    3. Ahmed Shata, A.S. & Hanitsch, R., 2008. "Electricity generation and wind potential assessment at Hurghada, Egypt," Renewable Energy, Elsevier, vol. 33(1), pages 141-148.
    4. Jamil, M. & Parsa, S. & Majidi, M., 1995. "Wind power statistics and an evaluation of wind energy density," Renewable Energy, Elsevier, vol. 6(5), pages 623-628.
    5. Al-Yahyai, Sultan & Charabi, Yassine & Gastli, Adel, 2010. "Review of the use of Numerical Weather Prediction (NWP) Models for wind energy assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 14(9), pages 3192-3198, December.
    6. Laslett, Dean & Creagh, Chris & Jennings, Philip, 2016. "A simple hourly wind power simulation for the South-West region of Western Australia using MERRA data," Renewable Energy, Elsevier, vol. 96(PA), pages 1003-1014.
    7. Mostafaeipour, Ali & Jadidi, Mohsen & Mohammadi, Kasra & Sedaghat, Ahmad, 2014. "An analysis of wind energy potential and economic evaluation in Zahedan, Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 641-650.
    8. Lu, Lin & Yang, Hongxing & Burnett, John, 2002. "Investigation on wind power potential on Hong Kong islands—an analysis of wind power and wind turbine characteristics," Renewable Energy, Elsevier, vol. 27(1), pages 1-12.
    9. Kaygusuz, Kamil, 2012. "Energy for sustainable development: A case of developing countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1116-1126.
    10. Sharp, Ed & Dodds, Paul & Barrett, Mark & Spataru, Catalina, 2015. "Evaluating the accuracy of CFSR reanalysis hourly wind speed forecasts for the UK, using in situ measurements and geographical information," Renewable Energy, Elsevier, vol. 77(C), pages 527-538.
    11. Cannon, D.J. & Brayshaw, D.J. & Methven, J. & Coker, P.J. & Lenaghan, D., 2015. "Using reanalysis data to quantify extreme wind power generation statistics: A 33 year case study in Great Britain," Renewable Energy, Elsevier, vol. 75(C), pages 767-778.
    12. Staffell, Iain & Pfenninger, Stefan, 2016. "Using bias-corrected reanalysis to simulate current and future wind power output," Energy, Elsevier, vol. 114(C), pages 1224-1239.
    13. Mirza, Irfan Afzal & Khan, Nasim A. & Memon, Naeem, 2010. "Development of benchmark wind speed for Gharo and Jhimpir, Pakistan," Renewable Energy, Elsevier, vol. 35(3), pages 576-582.
    14. Li, Yi & Wu, Xiao-Peng & Li, Qiu-Sheng & Tee, Kong Fah, 2018. "Assessment of onshore wind energy potential under different geographical climate conditions in China," Energy, Elsevier, vol. 152(C), pages 498-511.
    15. Wang, Yi-Hui & Walter, Ryan K. & White, Crow & Farr, Hayley & Ruttenberg, Benjamin I., 2019. "Assessment of surface wind datasets for estimating offshore wind energy along the Central California Coast," Renewable Energy, Elsevier, vol. 133(C), pages 343-353.
    16. Shu, Z.R. & Li, Q.S. & Chan, P.W., 2015. "Investigation of offshore wind energy potential in Hong Kong based on Weibull distribution function," Applied Energy, Elsevier, vol. 156(C), pages 362-373.
    17. Fazelpour, Farivar & Markarian, Elin & Soltani, Nima, 2017. "Wind energy potential and economic assessment of four locations in Sistan and Balouchestan province in Iran," Renewable Energy, Elsevier, vol. 109(C), pages 646-667.
    18. Ren, Guorui & Wan, Jie & Liu, Jinfu & Yu, Daren, 2019. "Characterization of wind resource in China from a new perspective," Energy, Elsevier, vol. 167(C), pages 994-1010.
    19. Chang, Tian Pau, 2011. "Estimation of wind energy potential using different probability density functions," Applied Energy, Elsevier, vol. 88(5), pages 1848-1856, May.
    20. Rose, Stephen & Apt, Jay, 2015. "What can reanalysis data tell us about wind power?," Renewable Energy, Elsevier, vol. 83(C), pages 963-969.
    21. Weisser, D, 2003. "A wind energy analysis of Grenada: an estimation using the ‘Weibull’ density function," Renewable Energy, Elsevier, vol. 28(11), pages 1803-1812.
    22. González-Aparicio, I. & Monforti, F. & Volker, P. & Zucker, A. & Careri, F. & Huld, T. & Badger, J., 2017. "Simulating European wind power generation applying statistical downscaling to reanalysis data," Applied Energy, Elsevier, vol. 199(C), pages 155-168.
    23. Dongbum Kang & Kyungnam Ko & Jongchul Huh, 2018. "Comparative Study of Different Methods for Estimating Weibull Parameters: A Case Study on Jeju Island, South Korea," Energies, MDPI, vol. 11(2), pages 1-19, February.
    24. Olauson, Jon & Bergkvist, Mikael, 2015. "Modelling the Swedish wind power production using MERRA reanalysis data," Renewable Energy, Elsevier, vol. 76(C), pages 717-725.
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