IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v102y2017ipap35-49.html
   My bibliography  Save this article

Wind power characteristics of seven data collection sites in Jubail, Saudi Arabia using Weibull parameters

Author

Listed:
  • Baseer, M.A.
  • Meyer, J.P.
  • Rehman, S.
  • Alam, Md. Mahbub

Abstract

The wind characteristics of seven locations in Jubail, Saudi Arabia were analysed by using five years of wind data of six sites and three years data of one site at 10 m above ground level (AGL). The highest annual mean wind speed of 4.52 m/s was observed at Industrial area (east) and lowest of 2.52 m/s at Pearl beach with standard deviations of 2.52 and 1.1 m/s respectively. Weibull parameters were estimated using maximum likelihood, least-squares regression method (LSRM) and WAsP algorithm. The most probable and maximum energy carrying wind speed were found by all the three methods. The correlation coefficient (R2), root mean square error (RMSE), mean bias error (MBE) and mean bias absolute error (MAE) showed that all three methods represent wind data at all sites accurately. However, the maximum likelihood method is slightly better than LSRM followed by WAsP algorithm. The wind power output at all seven sites from five commercially available wind machines of rated power from 1.8 to 3.3 MW showed that Jubail industrial area (east) is most promising. The energy output from a 3 MW wind machine at this site was found to be 11,136 MWh/yr. with a plant capacity factor (PCF) of 41.3%.

Suggested Citation

  • Baseer, M.A. & Meyer, J.P. & Rehman, S. & Alam, Md. Mahbub, 2017. "Wind power characteristics of seven data collection sites in Jubail, Saudi Arabia using Weibull parameters," Renewable Energy, Elsevier, vol. 102(PA), pages 35-49.
    • Handle: RePEc:eee:renene:v:102:y:2017:i:pa:p:35-49
    DOI: 10.1016/j.renene.2016.10.040
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148116309053
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2016.10.040?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. Alawaji, S.H. & Eugenio, N.N. & Elani, U.A., 1996. "Wind energy resource assessment in Saudi Arabia," Renewable Energy, Elsevier, vol. 9(1), pages 818-821.
    2. 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.
    3. Rehman, Shafiqur & Halawani, Talal Omar, 1994. "Statistical characteristics of wind in Saudi Arabia," Renewable Energy, Elsevier, vol. 4(8), pages 949-956.
    Full references (including those not matched with items on IDEAS)

    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. Baseer, M.A. & Meyer, J.P. & Alam, Md. Mahbub & Rehman, S., 2015. "Wind speed and power characteristics for Jubail industrial city, Saudi Arabia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1193-1204.
    2. Ramli, Makbul A.M. & Twaha, Ssennoga & Al-Hamouz, Zakariya, 2017. "Analyzing the potential and progress of distributed generation applications in Saudi Arabia: The case of solar and wind resources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 287-297.
    3. Rehman, Shafiqur & Al-Abbadi, Naif M., 2007. "Wind shear coefficients and energy yield for Dhahran, Saudi Arabia," Renewable Energy, Elsevier, vol. 32(5), pages 738-749.
    4. Shafiqur Rehman & Naif M. Al-Abbadi, 2009. "Wind Power Characteristics on the North West Coast of Saudi Arabia," Energy & Environment, , vol. 20(8-1), pages 1257-1270, December.
    5. 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.
    6. Rahman, Syed Masiur & Khondaker, A.N., 2012. "Mitigation measures to reduce greenhouse gas emissions and enhance carbon capture and storage in Saudi Arabia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 2446-2460.
    7. Rehman, S & Halawani, T.O & Mohandes, M, 2003. "Wind power cost assessment at twenty locations in the kingdom of Saudi Arabia," Renewable Energy, Elsevier, vol. 28(4), pages 573-583.
    8. Nor, Khalid Mohamed & Shaaban, Mohamed & Abdul Rahman, Hasimah, 2014. "Feasibility assessment of wind energy resources in Malaysia based on NWP models," Renewable Energy, Elsevier, vol. 62(C), pages 147-154.
    9. Amr Khaled Khamees & Almoataz Y. Abdelaziz & Makram R. Eskaros & Mahmoud A. Attia & Mariam A. Sameh, 2022. "Optimal Power Flow with Stochastic Renewable Energy Using Three Mixture Component Distribution Functions," Sustainability, MDPI, vol. 15(1), pages 1-21, December.
    10. Alam, Md. Mahbub & Rehman, Shafiqur & Meyer, Josua P. & Al-Hadhrami, Luai M., 2011. "Review of 600–2500kW sized wind turbines and optimization of hub height for maximum wind energy yield realization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(8), pages 3839-3849.
    11. Joselin Herbert, G.M. & Iniyan, S. & Sreevalsan, E. & Rajapandian, S., 2007. "A review of wind energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 11(6), pages 1117-1145, August.
    12. J. Wang, 2016. "Reviews of seismicity around Taiwan: Weibull distribution," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 80(3), pages 1651-1668, February.
    13. Mohandes, M. & Rehman, S. & Rahman, S.M., 2011. "Estimation of wind speed profile using adaptive neuro-fuzzy inference system (ANFIS)," Applied Energy, Elsevier, vol. 88(11), pages 4024-4032.
    14. Pierini, Jorge O. & Lovallo, Michele & Telesca, Luciano, 2012. "Visibility graph analysis of wind speed records measured in central Argentina," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 5041-5048.
    15. Lidong Zhang & Qikai Li & Yuanjun Guo & Zhile Yang & Lei Zhang, 2018. "An Investigation of Wind Direction and Speed in a Featured Wind Farm Using Joint Probability Distribution Methods," Sustainability, MDPI, vol. 10(12), pages 1-15, November.
    16. Das, Himadry Shekhar & Tan, Chee Wei & Yatim, A.H.M. & Lau, Kwan Yiew, 2017. "Feasibility analysis of hybrid photovoltaic/battery/fuel cell energy system for an indigenous residence in East Malaysia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 1332-1347.
    17. Ho, Lip-Wah, 2016. "Wind energy in Malaysia: Past, present and future," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 279-295.
    18. Angelis-Dimakis, Athanasios & Biberacher, Markus & Dominguez, Javier & Fiorese, Giulia & Gadocha, Sabine & Gnansounou, Edgard & Guariso, Giorgio & Kartalidis, Avraam & Panichelli, Luis & Pinedo, Irene, 2011. "Methods and tools to evaluate the availability of renewable energy sources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(2), pages 1182-1200, February.
    19. Rehman, Shafiqur & Al-Abbadi, Naif M., 2008. "Wind shear coefficient, turbulence intensity and wind power potential assessment for Dhulom, Saudi Arabia," Renewable Energy, Elsevier, vol. 33(12), pages 2653-2660.
    20. Zhao, Xuejing & Wang, Chen & Su, Jinxia & Wang, Jianzhou, 2019. "Research and application based on the swarm intelligence algorithm and artificial intelligence for wind farm decision system," Renewable Energy, Elsevier, vol. 134(C), pages 681-697.

    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:102:y:2017:i:pa:p:35-49. 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.