IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2023i1p65-d1305138.html
   My bibliography  Save this article

Potential of Offshore Wind Energy in Malaysia: An Investigation into Wind and Bathymetry Conditions and Site Selection

Author

Listed:
  • Mingxin Li

    (Department of Electronic & Electrical Engineering, University of Strathclyde, Glasgow G1 1XW, UK)

  • James Carroll

    (Department of Electronic & Electrical Engineering, University of Strathclyde, Glasgow G1 1XW, UK)

  • Ahmad Sukri Ahmad

    (PETRONAS Research Sdn Bhd, Kajang 43000, Selangor, Malaysia)

  • Nor Shahida Hasan

    (PETRONAS Research Sdn Bhd, Kajang 43000, Selangor, Malaysia)

  • M. Zaid B. Zolkiffly

    (PETRONAS Research Sdn Bhd, Kajang 43000, Selangor, Malaysia)

  • Gboyega Bishop Falope

    (PETRONAS Centre of Excellence in Subsurface Engineering & Energy Transition (PACESET), Heriot Watt University, Edinburgh EH14 4AP, UK)

  • Khalik Mohamad Sabil

    (PETRONAS Research Sdn Bhd, Kajang 43000, Selangor, Malaysia)

Abstract

The government has set an ambitious target of renewable energy development in Malaysia. As a promising renewable energy source, wind energy plays an important role in the Malaysia renewable energy roadmap. Compared to onshore wind energy, offshore wind resources with better quality can be provided in the areas away from the coast, which has greater potential to contribute to electricity generation. Wind and bathymetry conditions are two important factors that determine the feasibility and economics of offshore wind turbines. In this paper, an investigation is conducted on wind and bathymetry conditions around Malaysia. The data source mainly originates from the Global Wind Atlas. The conditions of the coastal areas in different states and federal territories of both Peninsular Malaysia and East Malaysia are analysed, with a specific focus on wind speed, wind energy density, and bathymetry conditions in high-wind-speed regions. The data and survey are verified and compared with the past published literature. This paper aims to investigate the wind and bathymetry conditions around Malaysia, assess the potential of offshore wind energy, discuss the feasibility of offshore wind turbines, and provide references for offshore wind development in Malaysia.

Suggested Citation

  • Mingxin Li & James Carroll & Ahmad Sukri Ahmad & Nor Shahida Hasan & M. Zaid B. Zolkiffly & Gboyega Bishop Falope & Khalik Mohamad Sabil, 2023. "Potential of Offshore Wind Energy in Malaysia: An Investigation into Wind and Bathymetry Conditions and Site Selection," Energies, MDPI, vol. 17(1), pages 1-17, December.
    • Handle: RePEc:gam:jeners:v:17:y:2023:i:1:p:65-:d:1305138
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/1/65/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/1/65/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Li, Mingxin & Jiang, Xiaoli & Carroll, James & Negenborn, Rudy R., 2022. "A multi-objective maintenance strategy optimization framework for offshore wind farms considering uncertainty," Applied Energy, Elsevier, vol. 321(C).
    3. Caglayan, Dilara Gulcin & Ryberg, David Severin & Heinrichs, Heidi & Linßen, Jochen & Stolten, Detlef & Robinius, Martin, 2019. "The techno-economic potential of offshore wind energy with optimized future turbine designs in Europe," Applied Energy, Elsevier, vol. 255(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. 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.
    2. Si, Guojin & Xia, Tangbin & Gebraeel, Nagi & Wang, Dong & Pan, Ershun & Xi, Lifeng, 2025. "Holistic opportunistic maintenance scheduling and routing for offshore wind farms," Renewable and Sustainable Energy Reviews, Elsevier, vol. 207(C).
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Jeong, Michael & Loth, Eric & Qin, Chris & Selig, Michael & Johnson, Nick, 2024. "Aerodynamic rotor design for a 25 MW offshore downwind turbine," Applied Energy, Elsevier, vol. 353(PA).
    8. Kang, Dongbum & Ko, Kyungnam & Huh, Jongchul, 2015. "Determination of extreme wind values using the Gumbel distribution," Energy, Elsevier, vol. 86(C), pages 51-58.
    9. Jaime Meza-Carreto & Rosario Romero-Centeno & Bernardo Figueroa-Espinoza & Efraín Moreles & Carlos López-Villalobos, 2024. "Outlook for Offshore Wind Energy Development in Mexico from WRF Simulations and CMIP6 Projections," Energies, MDPI, vol. 17(8), pages 1-30, April.
    10. El Alimi, Souheil & Maatallah, Taher & Dahmouni, Anouar Wajdi & Ben Nasrallah, Sassi, 2012. "Modeling and investigation of the wind resource in the gulf of Tunis, Tunisia," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(8), pages 5466-5478.
    11. Suwarno Suwarno & M. Fitra Zambak, 2021. "The Probability Density Function for Wind Speed Using Modified Weibull Distribution," International Journal of Energy Economics and Policy, Econjournals, vol. 11(6), pages 544-550.
    12. Redha, Adel Mohammed & Dincer, Ibrahim & Gadalla, Mohamed, 2011. "Thermodynamic performance assessment of wind energy systems: An application," Energy, Elsevier, vol. 36(7), pages 4002-4010.
    13. Lin, Zi & Liu, Xiaolei, 2020. "Wind power forecasting of an offshore wind turbine based on high-frequency SCADA data and deep learning neural network," Energy, Elsevier, vol. 201(C).
    14. Lee, Namkyoung & Lee, Hyuntae & Joung, Seulgi, 2025. "A wake-induced two-phase planning framework for offshore wind farm maintenance with stochastic mixed-integer program," Applied Energy, Elsevier, vol. 380(C).
    15. Arslan, Talha & Bulut, Y. Murat & Altın Yavuz, Arzu, 2014. "Comparative study of numerical methods for determining Weibull parameters for wind energy potential," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 820-825.
    16. Centeno-Telleria, Manu & Yue, Hong & Carrol, James & Aizpurua, Jose I. & Penalba, Markel, 2024. "O&M-aware techno-economic assessment for floating offshore wind farms: A geospatial evaluation off the North Sea and the Iberian Peninsula," Applied Energy, Elsevier, vol. 371(C).
    17. Li, Mingxin & Jiang, Xiaoli & Carroll, James & Negenborn, Rudy R., 2022. "A multi-objective maintenance strategy optimization framework for offshore wind farms considering uncertainty," Applied Energy, Elsevier, vol. 321(C).
    18. Yu, Jie & Chen, Kuilin & Mori, Junichi & Rashid, Mudassir M., 2013. "A Gaussian mixture copula model based localized Gaussian process regression approach for long-term wind speed prediction," Energy, Elsevier, vol. 61(C), pages 673-686.
    19. Morteza Aien & Omid Mahdavi, 2020. "On the Way of Policy Making to Reduce the Reliance of Fossil Fuels: Case Study of Iran," Sustainability, MDPI, vol. 12(24), pages 1-28, December.
    20. Abul Kalam Azad & Mohammad Golam Rasul & Talal Yusaf, 2014. "Statistical Diagnosis of the Best Weibull Methods for Wind Power Assessment for Agricultural Applications," Energies, MDPI, vol. 7(5), pages 1-30, May.

    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:gam:jeners:v:17:y:2023:i:1:p:65-:d:1305138. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.