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Potential for wind generation on the Guyana coastlands

Author

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  • Persaud, Shashi
  • Flynn, Damian
  • Fox, Brendan
Abstract
Guyanas dependence upon imported petroleum fuels can only be offset by the sustained exploitation of its indigenous resources. With its populated coastlands exposed to the northeast trade winds and a history of small-scale wind energy utilisation wind is one such potential energy source. In this study, the coastal wind regime is analysed and historical data from a coastal weather station are used to estimate the potential for wind generation. It is found that a hybrid Weibull probability density function best describes the annual wind speed frequency distribution at the reference height of 10.67 m. With an annual mean wind speed of 5.8 m⧸s, an energy pattern factor of 1.41, and an annual average power density of 159 W⧸m2, this distribution represents a class-3 wind resource, suitable for most wind turbine applications. Site analysis and observed trends in coastal wind availability suggest the strong likelihood of a greater wind resource in more open locations. In view of its apparent potential for wind farm operation, a comprehensive, wind resource assessment programme is recommended for the Guyana coastlands.

Suggested Citation

  • Persaud, Shashi & Flynn, Damian & Fox, Brendan, 1999. "Potential for wind generation on the Guyana coastlands," Renewable Energy, Elsevier, vol. 18(2), pages 175-189.
    • Handle: RePEc:eee:renene:v:18:y:1999:i:2:p:175-189
    DOI: 10.1016/S0960-1481(98)00793-9
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    Cited by:

    1. Wang, Jianzhou & Qin, Shanshan & Jin, Shiqiang & Wu, Jie, 2015. "Estimation methods review and analysis of offshore extreme wind speeds and wind energy resources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 26-42.
    2. Iskin, Ibrahim & Daim, Tugrul & Kayakutlu, Gulgun & Altuntas, Mehmet, 2012. "Exploring renewable energy pricing with analytic network process — Comparing a developed and a developing economy," Energy Economics, Elsevier, vol. 34(4), pages 882-891.
    3. Dong, Cong & Huang, Guohe (Gordon) & Cheng, Guanhui, 2021. "Offshore wind can power Canada," Energy, Elsevier, vol. 236(C).
    4. Mostafaeipour, A. & Sedaghat, A. & Dehghan-Niri, A.A. & Kalantar, V., 2011. "Wind energy feasibility study for city of Shahrbabak in Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(6), pages 2545-2556, August.
    5. Diaf, S. & Notton, G., 2013. "Evaluation of electricity generation and energy cost of wind energy conversion systems in southern Algeria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 23(C), pages 379-390.
    6. Mazhar H. Baloch & Safdar A. Abro & Ghulam Sarwar Kaloi & Nayyar H. Mirjat & Sohaib Tahir & M. Haroon Nadeem & Mehr Gul & Zubair A. Memon & Mahendar Kumar, 2017. "A Research on Electricity Generation from Wind Corridors of Pakistan (Two Provinces): A Technical Proposal for Remote Zones," Sustainability, MDPI, vol. 9(9), pages 1-31, September.
    7. Lepore, Antonio & Palumbo, Biagio & Pievatolo, Antonio, 2020. "A Bayesian approach for site-specific wind rose prediction," Renewable Energy, Elsevier, vol. 150(C), pages 691-702.
    8. Diaf, S. & Notton, G., 2013. "Technical and economic analysis of large-scale wind energy conversion systems in Algeria," Renewable and Sustainable Energy Reviews, Elsevier, vol. 19(C), pages 37-51.
    9. Ramez Abdallah & Hüseyin Çamur, 2022. "Assessing the Potential of Wind Energy as Sustainable Energy Production in Ramallah, Palestine," Sustainability, MDPI, vol. 14(15), pages 1-21, July.
    10. Zhou, Wei & Yang, Hongxing & Fang, Zhaohong, 2006. "Wind power potential and characteristic analysis of the Pearl River Delta region, China," Renewable Energy, Elsevier, vol. 31(6), pages 739-753.
    11. Wang, Jianzhou & Huang, Xiaojia & Li, Qiwei & Ma, Xuejiao, 2018. "Comparison of seven methods for determining the optimal statistical distribution parameters: A case study of wind energy assessment in the large-scale wind farms of China," Energy, Elsevier, vol. 164(C), pages 432-448.
    12. Chadee, Xsitaaz T. & Clarke, Ricardo M., 2014. "Large-scale wind energy potential of the Caribbean region using near-surface reanalysis data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 45-58.
    13. Islam, M.R. & Saidur, R. & Rahim, N.A., 2011. "Assessment of wind energy potentiality at Kudat and Labuan, Malaysia using Weibull distribution function," Energy, Elsevier, vol. 36(2), pages 985-992.
    14. Jiang, Haiyan & Wang, Jianzhou & Wu, Jie & Geng, Wei, 2017. "Comparison of numerical methods and metaheuristic optimization algorithms for estimating parameters for wind energy potential assessment in low wind regions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 1199-1217.
    15. Li, Meishen & Li, Xianguo, 2005. "MEP-type distribution function: a better alternative to Weibull function for wind speed distributions," Renewable Energy, Elsevier, vol. 30(8), pages 1221-1240.
    16. Keyhani, A. & Ghasemi-Varnamkhasti, M. & Khanali, M. & Abbaszadeh, R., 2010. "An assessment of wind energy potential as a power generation source in the capital of Iran, Tehran," Energy, Elsevier, vol. 35(1), pages 188-201.
    17. Ahmed, Ahmed Shata, 2011. "Analysis of electrical power form the wind farm sitting on the Nile River of Aswan, Egypt," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(3), pages 1637-1645, April.
    18. Chatzimouratidis, Athanasios I. & Pilavachi, Petros A., 2009. "Technological, economic and sustainability evaluation of power plants using the Analytic Hierarchy Process," Energy Policy, Elsevier, vol. 37(3), pages 778-787, March.
    19. Carta, J.A. & Ramírez, P. & Velázquez, S., 2009. "A review of wind speed probability distributions used in wind energy analysis: Case studies in the Canary Islands," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(5), pages 933-955, June.
    20. 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.

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