IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v154y2020icp1240-1251.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148120304328
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2020.03.100?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    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. Rose, Stephen & Apt, Jay, 2015. "What can reanalysis data tell us about wind power?," Renewable Energy, Elsevier, vol. 83(C), pages 963-969.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    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. 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.
    13. 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.
    14. 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.
    15. 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.
    16. Olauson, Jon & Bergkvist, Mikael, 2015. "Modelling the Swedish wind power production using MERRA reanalysis data," Renewable Energy, Elsevier, vol. 76(C), pages 717-725.
    17. 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.
    18. Kaygusuz, Kamil, 2012. "Energy for sustainable development: A case of developing countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(2), pages 1116-1126.
    19. 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.
    20. 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.
    21. 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.
    22. 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.
    23. 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.
    24. Chang, Tian Pau, 2011. "Estimation of wind energy potential using different probability density functions," Applied Energy, Elsevier, vol. 88(5), pages 1848-1856, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. José Rafael Dorrego Portela & Geovanni Hernández Galvez & Quetzalcoatl Hernandez-Escobedo & Ricardo Saldaña Flores & Omar Sarracino Martínez & Orlando Lastres Danguillecourt & Pascual López de Paz & A, 2022. "Microscale Wind Assessment, Comparing Mesoscale Information and Observed Wind Data," Sustainability, MDPI, vol. 14(19), pages 1-12, September.
    2. Victoria Yildirir & Eugen Rusu & Florin Onea, 2022. "Wind Energy Assessments in the Northern Romanian Coastal Environment Based on 20 Years of Data Coming from Different Sources," Sustainability, MDPI, vol. 14(7), pages 1-21, April.
    3. Majidi Nezhad, Meysam & Heydari, Azim & Neshat, Mehdi & Keynia, Farshid & Piras, Giuseppe & Garcia, Davide Astiaso, 2022. "A Mediterranean Sea Offshore Wind classification using MERRA-2 and machine learning models," Renewable Energy, Elsevier, vol. 190(C), pages 156-166.
    4. de Aquino Ferreira, Saulo Custodio & Cyrino Oliveira, Fernando Luiz & Maçaira, Paula Medina, 2022. "Validation of the representativeness of wind speed time series obtained from reanalysis data for Brazilian territory," Energy, Elsevier, vol. 258(C).
    5. Rabbani, Rabab & Zeeshan, Muhammad, 2022. "Impact of policy changes on financial viability of wind power plants in Pakistan," Renewable Energy, Elsevier, vol. 193(C), pages 789-806.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. He, Junyi & Chan, P.W. & Li, Qiusheng & Lee, C.W., 2020. "Spatiotemporal analysis of offshore wind field characteristics and energy potential in Hong Kong," Energy, Elsevier, vol. 201(C).
    2. Kena Likassa Nefabas & Lennart Söder & Mengesha Mamo & Jon Olauson, 2021. "Modeling of Ethiopian Wind Power Production Using ERA5 Reanalysis Data," Energies, MDPI, vol. 14(9), pages 1-17, April.
    3. Mehr Gul & Nengling Tai & Wentao Huang & Muhammad Haroon Nadeem & Moduo Yu, 2019. "Assessment of Wind Power Potential and Economic Analysis at Hyderabad in Pakistan: Powering to Local Communities Using Wind Power," Sustainability, MDPI, vol. 11(5), pages 1-23, March.
    4. He, J.Y. & Chan, P.W. & Li, Q.S. & Lee, C.W., 2022. "Characterizing coastal wind energy resources based on sodar and microwave radiometer observations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    5. Gualtieri, G., 2022. "Analysing the uncertainties of reanalysis data used for wind resource assessment: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    6. 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.
    7. Munir Ali Elfarra & Mustafa Kaya, 2018. "Comparison of Optimum Spline-Based Probability Density Functions to Parametric Distributions for the Wind Speed Data in Terms of Annual Energy Production," Energies, MDPI, vol. 11(11), pages 1-15, November.
    8. Hayes, Liam & Stocks, Matthew & Blakers, Andrew, 2021. "Accurate long-term power generation model for offshore wind farms in Europe using ERA5 reanalysis," Energy, Elsevier, vol. 229(C).
    9. Fazelpour, Farivar & Soltani, Nima & Soltani, Sina & Rosen, Marc A., 2015. "Assessment of wind energy potential and economics in the north-western Iranian cities of Tabriz and Ardabil," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 87-99.
    10. 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.
    11. Katinas, Vladislovas & Gecevicius, Giedrius & Marciukaitis, Mantas, 2018. "An investigation of wind power density distribution at location with low and high wind speeds using statistical model," Applied Energy, Elsevier, vol. 218(C), pages 442-451.
    12. Matti Koivisto & Kaushik Das & Feng Guo & Poul Sørensen & Edgar Nuño & Nicolaos Cutululis & Petr Maule, 2019. "Using time series simulation tools for assessing the effects of variable renewable energy generation on power and energy systems," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 8(3), May.
    13. Siyavash Filom & Soheil Radfar & Roozbeh Panahi & Erfan Amini & Mehdi Neshat, 2021. "Exploring Wind Energy Potential as a Driver of Sustainable Development in the Southern Coasts of Iran: The Importance of Wind Speed Statistical Distribution Model," Sustainability, MDPI, vol. 13(14), pages 1-24, July.
    14. Mohammadzadeh Bina, Saeid & Jalilinasrabady, Saeid & Fujii, Hikari & Farabi-Asl, Hadi, 2018. "A comprehensive approach for wind power plant potential assessment, application to northwestern Iran," Energy, Elsevier, vol. 164(C), pages 344-358.
    15. 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.
    16. 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.
    17. He, J.Y. & Li, Q.S. & Chan, P.W. & Zhao, X.D., 2023. "Assessment of future wind resources under climate change using a multi-model and multi-method ensemble approach," Applied Energy, Elsevier, vol. 329(C).
    18. Zhang, Hengxu & Cao, Yongji & Zhang, Yi & Terzija, Vladimir, 2018. "Quantitative synergy assessment of regional wind-solar energy resources based on MERRA reanalysis data," Applied Energy, Elsevier, vol. 216(C), pages 172-182.
    19. Hdidouan, Daniel & Staffell, Iain, 2017. "The impact of climate change on the levelised cost of wind energy," Renewable Energy, Elsevier, vol. 101(C), pages 575-592.
    20. 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.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:154:y:2020:i:c:p:1240-1251. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.