IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i9p3668-d1131860.html
   My bibliography  Save this article

Wind Energy Supply Profiling and Offshore Potential in South Africa

Author

Listed:
  • Stefan Karamanski

    (Energy Supply and Demand Group, Council for Scientific and Industrial Research, Stellenbosch 7600, South Africa)

  • Gareth Erfort

    (Department of Mechanical and Mechatronic Engineering, Stellenbosch University, Stellenbosch 7600, South Africa)

Abstract

South Africa’s energy network is under severe pressure due to low supply and overwhelming demand. With an increase in renewable energy providers, specifically wind energy, knowing how the supply can satisfy the electricity demand may relieve apprehensions. This research aims to provide insight into the wind energy supply of South Africa and question how well this supply meets the demand of South Africa. The methodology used in this work highlights the importance of access to public datasets to dispel misconceptions in the energy industry. Additionally, the work supports network planning and the arguments for increasing wind energy penetration on the South African grid. Wind profiles and the typical energy production of South African wind farms are compared to electricity demand. The geographical spacing of the operational wind farms is considered. It is observed that wind energy supply assists in the peak electricity hourly demand as well as seasonal peaks. Furthermore, South Africa’s coast is analysed to determine the offshore wind power potential, where shallow and deep waters are considered. It is observed that South Africa has a high potential for offshore wind, even after losses are applied.

Suggested Citation

  • Stefan Karamanski & Gareth Erfort, 2023. "Wind Energy Supply Profiling and Offshore Potential in South Africa," Energies, MDPI, vol. 16(9), pages 1-24, April.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:9:p:3668-:d:1131860
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/9/3668/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/9/3668/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Pusat, Saban & Ekmekçi, İsmail & Akkoyunlu, Mustafa Tahir, 2015. "Generation of typical meteorological year for different climates of Turkey," Renewable Energy, Elsevier, vol. 75(C), pages 144-151.
    2. Kockel, Christina & Nolting, Lars & Priesmann, Jan & Praktiknjo, Aaron, 2022. "Does renewable electricity supply match with energy demand? – A spatio-temporal analysis for the German case," Applied Energy, Elsevier, vol. 308(C).
    3. Wu, Xiaoni & Hu, Yu & Li, Ye & Yang, Jian & Duan, Lei & Wang, Tongguang & Adcock, Thomas & Jiang, Zhiyu & Gao, Zhen & Lin, Zhiliang & Borthwick, Alistair & Liao, Shijun, 2019. "Foundations of offshore wind turbines: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 379-393.
    4. Daniel R. Drew & Dirk J. Cannon & David J. Brayshaw & Janet F. Barlow & Phil J. Coker, 2015. "The Impact of Future Offshore Wind Farms on Wind Power Generation in Great Britain," Resources, MDPI, vol. 4(1), pages 1-17, March.
    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. Abayomi A. Adebiyi & Katleho Moloi, 2024. "Renewable Energy Source Utilization Progress in South Africa: A Review," Energies, MDPI, vol. 17(14), pages 1-21, July.

    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. Cui, Ying & Yan, Da & Hong, Tianzhen & Xiao, Chan & Luo, Xuan & Zhang, Qi, 2017. "Comparison of typical year and multiyear building simulations using a 55-year actual weather data set from China," Applied Energy, Elsevier, vol. 195(C), pages 890-904.
    2. García, Ignacio & Torres, José Luis, 2018. "Temporal downscaling of test reference years: Effects on the long-term evaluation of photovoltaic systems," Renewable Energy, Elsevier, vol. 122(C), pages 392-405.
    3. Putra, I Dewa Gede Arya & Nimiya, Hideyo & Sopaheluwakan, Ardhasena & Kubota, Tetsu & Lee, Han Soo & Pradana, Radyan Putra & Alfata, Muhammad Nur Fajri & Perdana, Reza Bayu & Permana, Donaldi Sukma & , 2024. "Development of typical meteorological years based on quality control of datasets in Indonesia," Renewable Energy, Elsevier, vol. 221(C).
    4. Zhang, Lijun & Li, Ye & Xu, Wenhao & Gao, Zhiteng & Fang, Long & Li, Rongfu & Ding, Boyin & Zhao, Bin & Leng, Jun & He, Fenglan, 2022. "Systematic analysis of performance and cost of two floating offshore wind turbines with significant interactions," Applied Energy, Elsevier, vol. 321(C).
    5. Sun, Chuan & Chen, Yueyi & Cheng, Cheng, 2021. "Imputation of missing data from offshore wind farms using spatio-temporal correlation and feature correlation," Energy, Elsevier, vol. 229(C).
    6. Li, Honglian & Huang, Jin & Hu, Yao & Wang, Shangyu & Liu, Jing & Yang, Liu, 2021. "A new TMY generation method based on the entropy-based TOPSIS theory for different climatic zones in China," Energy, Elsevier, vol. 231(C).
    7. Moez Krichen & Yasir Basheer & Saeed Mian Qaisar & Asad Waqar, 2023. "A Survey on Energy Storage: Techniques and Challenges," Energies, MDPI, vol. 16(5), pages 1-29, February.
    8. Oluwaseu Kilanko & Sunday O Oyedepo & Joseph O Dirisu & Richard O Leramo & Philip Babalola & Abraham K Aworinde & Mfon Udo & Alexander M Okonkwo & Marvelous I Akomolafe, 2023. "Typical meteorological year data analysis for optimal usage of energy systems at six selected locations in Nigeria," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 18, pages 637-658.
    9. Fan, Xinying, 2022. "A method for the generation of typical meteorological year data using ensemble empirical mode decomposition for different climates of China and performance comparison analysis," Energy, Elsevier, vol. 240(C).
    10. Soares-Ramos, Emanuel P.P. & de Oliveira-Assis, Lais & Sarrias-Mena, Raúl & Fernández-Ramírez, Luis M., 2020. "Current status and future trends of offshore wind power in Europe," Energy, Elsevier, vol. 202(C).
    11. Jieyan Chen & Chengxi Li, 2020. "Design Optimization and Coupled Dynamics Analysis of an Offshore Wind Turbine with a Single Swivel Connected Tether," Energies, MDPI, vol. 13(14), pages 1-26, July.
    12. Mingyuan Wang & Miao Wang & Xinglei Cheng & Qun Lu & Jiaqing Lu, 2022. "A New p–y Curve for Laterally Loaded Large-Diameter Monopiles in Soft Clays," Sustainability, MDPI, vol. 14(22), pages 1-16, November.
    13. Hernandez-Estrada, Edwin & Lastres-Danguillecourt, Orlando & Robles-Ocampo, Jose B. & Lopez-Lopez, Andres & Sevilla-Camacho, Perla Y. & Perez-Sariñana, Bianca Y. & Dorrego-Portela, Jose R., 2021. "Considerations for the structural analysis and design of wind turbine towers: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    14. Xu, Jiuping & Liu, Tingting, 2020. "Technological paradigm-based approaches towards challenges and policy shifts for sustainable wind energy development," Energy Policy, Elsevier, vol. 142(C).
    15. Li, Honglian & Yang, Yi & Lv, Kailin & Liu, Jing & Yang, Liu, 2020. "Compare several methods of select typical meteorological year for building energy simulation in China," Energy, Elsevier, vol. 209(C).
    16. Pei Zhang & Shugeng Yang & Yan Li & Jiayang Gu & Zhiqiang Hu & Ruoyu Zhang & Yougang Tang, 2020. "Dynamic Response of Articulated Offshore Wind Turbines under Different Water Depths," Energies, MDPI, vol. 13(11), pages 1-20, June.
    17. Min-Chih Hsu & Hsuan-Shih Lee, 2023. "Applying AHP-IFNs-DEMATEL in Establishing a Supplier Selection Model: A Case Study of Offshore Wind Power Companies in Taiwan," Energies, MDPI, vol. 16(11), pages 1-23, June.
    18. McMorland, J. & Collu, M. & McMillan, D. & Carroll, J., 2022. "Operation and maintenance for floating wind turbines: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    19. Golnary, Farshad & Moradi, Hamed, 2022. "Identification of the dynamics of the drivetrain and estimating its unknown parts in a large scale wind turbine," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 192(C), pages 50-69.
    20. Majidi Nezhad, Meysam & Neshat, Mehdi & Piras, Giuseppe & Astiaso Garcia, Davide, 2022. "Sites exploring prioritisation of offshore wind energy potential and mapping for wind farms installation: Iranian islands case studies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).

    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:16:y:2023:i:9:p:3668-:d:1131860. 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.