IDEAS home Printed from https://ideas.repec.org/a/wly/envmet/v31y2020i7ne2651.html
   My bibliography  Save this article

Discussion on A high‐resolution bilevel skew‐t stochastic generator for assessing Saudi Arabia's wind energy resources

Author

Listed:
  • Emilio Porcu
  • Jonas Rysgaard
  • Valerie Eveloy

Abstract

We provide a detailed discussion on the analysis presented by Tagle and co‐authors, who suggested an approach to improve earlier models for handling non‐Gaussianity in spatial wind field speed data by simplifying the model formulation to better accommodate large data sets. Our discussion focuses on the energy and socio‐economic context of wind potential assessment in Saudi Arabia – an oil‐rich country, statistical aspects associated with wind field forecasting, and the prediction of the wind electricity production potential from the wind field forecast.

Suggested Citation

  • Emilio Porcu & Jonas Rysgaard & Valerie Eveloy, 2020. "Discussion on A high‐resolution bilevel skew‐t stochastic generator for assessing Saudi Arabia's wind energy resources," Environmetrics, John Wiley & Sons, Ltd., vol. 31(7), November.
  • Handle: RePEc:wly:envmet:v:31:y:2020:i:7:n:e2651
    DOI: 10.1002/env.2651
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/env.2651
    Download Restriction: no

    File URL: https://libkey.io/10.1002/env.2651?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
    ---><---

    References listed on IDEAS

    as
    1. Al-Yahyai, Sultan & Charabi, Yassine, 2015. "Assessment of large-scale wind energy potential in the emerging city of Duqm (Oman)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 438-447.
    2. Dhiman, Harsh S. & Deb, Dipankar & Foley, Aoife M., 2020. "Bilateral Gaussian Wake Model Formulation for Wind Farms: A Forecasting based approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 127(C).
    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. Yassine Charabi & Sabah Abdul-Wahab & Abdul Majeed Al-Mahruqi & Selma Osman & Isra Osman, 2022. "The potential estimation and cost analysis of wind energy production in Oman," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 24(4), pages 5917-5937, April.
    2. Sun, Shilin & Wang, Tianyang & Chu, Fulei, 2022. "In-situ condition monitoring of wind turbine blades: A critical and systematic review of techniques, challenges, and futures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    3. Chadee, Xsitaaz T. & Clarke, Ricardo M., 2018. "Wind resources and the levelized cost of wind generated electricity in the Caribbean islands of Trinidad and Tobago," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2526-2540.
    4. Purohit, Shantanu & Ng, E.Y.K. & Syed Ahmed Kabir, Ijaz Fazil, 2022. "Evaluation of three potential machine learning algorithms for predicting the velocity and turbulence intensity of a wind turbine wake," Renewable Energy, Elsevier, vol. 184(C), pages 405-420.
    5. Fahd A. Alturki & Emad Mahrous Awwad, 2021. "Sizing and Cost Minimization of Standalone Hybrid WT/PV/Biomass/Pump-Hydro Storage-Based Energy Systems," Energies, MDPI, vol. 14(2), pages 1-20, January.
    6. Anwarzai, Mohammad Abed & Nagasaka, Ken, 2017. "Utility-scale implementable potential of wind and solar energies for Afghanistan using GIS multi-criteria decision analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 71(C), pages 150-160.
    7. Kaldellis, John K. & Triantafyllou, Panagiotis & Stinis, Panagiotis, 2021. "Critical evaluation of Wind Turbines’ analytical wake models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    8. Yip, Chak Man Andrew & Gunturu, Udaya Bhaskar & Stenchikov, Georgiy L., 2016. "Wind resource characterization in the Arabian Peninsula," Applied Energy, Elsevier, vol. 164(C), pages 826-836.
    9. Amann, Juergen & Cantore, Nicola & Calí, Massimiliano & Todorov, Valentin & Cheng, Charles Fang Chin, 2021. "Switching it up: The effect of energy price reforms in Oman," World Development, Elsevier, vol. 142(C).
    10. Onar, Sezi Cevik & Oztaysi, Basar & Otay, İrem & Kahraman, Cengiz, 2015. "Multi-expert wind energy technology selection using interval-valued intuitionistic fuzzy sets," Energy, Elsevier, vol. 90(P1), pages 274-285.
    11. Dhiman, Harsh S. & Deb, Dipankar, 2020. "Wake management based life enhancement of battery energy storage system for hybrid wind farms," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
    12. Yongnian Zhao & Yu Xue & Shanhong Gao & Jundong Wang & Qingcai Cao & Tao Sun & Yan Liu, 2022. "Computation and Analysis of an Offshore Wind Power Forecast: Towards a Better Assessment of Offshore Wind Power Plant Aerodynamics," Energies, MDPI, vol. 15(12), pages 1-17, June.
    13. Wang, Xuguang & Ren, Huan & Zhai, Junhai & Xing, Hongjie & Su, Jie, 2022. "Adaptive support segment based short-term wind speed forecasting," Energy, Elsevier, vol. 249(C).
    14. Lu, Peng & Ye, Lin & Zhao, Yongning & Dai, Binhua & Pei, Ming & Li, Zhuo, 2021. "Feature extraction of meteorological factors for wind power prediction based on variable weight combined method," Renewable Energy, Elsevier, vol. 179(C), pages 1925-1939.
    15. Paxis Marques João Roque & Shyama Pada Chowdhury & Zhongjie Huan, 2021. "Performance Enhancement of Proposed Namaacha Wind Farm by Minimising Losses Due to the Wake Effect: A Mozambican Case Study," Energies, MDPI, vol. 14(14), pages 1-22, July.
    16. Zhu, Huixing & Xu, Tianfu & Xin, Xin & Yuan, Yilong & Feng, Guanhong, 2022. "Numerical investigation of the three-phase layer production performance of an offshore natural gas hydrate trial production," Energy, Elsevier, vol. 257(C).

    More about this item

    Statistics

    Access and download statistics

    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:wly:envmet:v:31:y:2020:i:7:n:e2651. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.interscience.wiley.com/jpages/1180-4009/ .

    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.