IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v118y2018icp627-643.html
   My bibliography  Save this article

Co-located offshore wind and tidal stream turbines: Assessment of energy yield and loading

Author

Listed:
  • Lande-Sudall, D.
  • Stallard, T.
  • Stansby, P.

Abstract

Co-location of wind and tidal stream turbines provides opportunity for improved economic viability of electricity generation from these resources relative to projects exploiting each resource separately. Here co-deployment is assessed in terms of energy generation and loading of support structures. Energy yield is modelled using an eddy viscosity wake model for wind turbines and superposition of self-similar wakes for tidal turbines. A case-study of the Inner Sound of the Pentland Firth is considered. For 3.5 years of coincident resource data, 12 MW wind capacity co-located with a 20 MW tidal array results in a 70% increase in energy yield, compared to operating the tidal turbines alone. Environmental loads are modelled for a braced monopile structure supporting both a wind and tidal turbine, as well as for each system in isolation. Peak loading of the combined system is found to be driven by wind loads with greatest overturning moment occurring with the wind turbine operating at close to rated-speed and the tidal turbine close to its shutdown speed. Mean loads vary across the tidal array by 6% indicating no significant shielding effects are gained by co-locating in more sheltered regions of the array.

Suggested Citation

  • Lande-Sudall, D. & Stallard, T. & Stansby, P., 2018. "Co-located offshore wind and tidal stream turbines: Assessment of energy yield and loading," Renewable Energy, Elsevier, vol. 118(C), pages 627-643.
  • Handle: RePEc:eee:renene:v:118:y:2018:i:c:p:627-643
    DOI: 10.1016/j.renene.2017.10.063
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148117310248
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2017.10.063?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. Heptonstall, Philip & Gross, Robert & Greenacre, Philip & Cockerill, Tim, 2012. "The cost of offshore wind: Understanding the past and projecting the future," Energy Policy, Elsevier, vol. 41(C), pages 815-821.
    2. Santo, H. & Taylor, P.H. & Eatock Taylor, R. & Stansby, P., 2016. "Decadal variability of wave power production in the North-East Atlantic and North Sea for the M4 machine," Renewable Energy, Elsevier, vol. 91(C), pages 442-450.
    3. Foley, Aoife M. & Leahy, Paul G. & Marvuglia, Antonino & McKeogh, Eamon J., 2012. "Current methods and advances in forecasting of wind power generation," Renewable Energy, Elsevier, vol. 37(1), pages 1-8.
    4. Stansby, Peter & Stallard, Tim, 2016. "Fast optimisation of tidal stream turbine positions for power generation in small arrays with low blockage based on superposition of self-similar far-wake velocity deficit profiles," Renewable Energy, Elsevier, vol. 92(C), pages 366-375.
    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. Wiegner, J.F. & Andreasson, L.M. & Kusters, J.E.H. & Nienhuis, R.M., 2024. "Interdisciplinary perspectives on offshore energy system integration in the North Sea: A systematic literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PA).
    2. Bahaj, AbuBakr S. & Mahdy, Mostafa & Alghamdi, Abdulsalam S. & Richards, David J., 2020. "New approach to determine the Importance Index for developing offshore wind energy potential sites: Supported by UK and Arabian Peninsula case studies," Renewable Energy, Elsevier, vol. 152(C), pages 441-457.
    3. Liu, Xiaodong & Chen, Zheng & Si, Yulin & Qian, Peng & Wu, He & Cui, Lin & Zhang, Dahai, 2021. "A review of tidal current energy resource assessment in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
    4. Yang, Zhixue & Ren, Zhouyang & Li, Hui & Pan, Zhen & Xia, Weiyi, 2024. "A review of tidal current power generation farm planning: Methodologies, characteristics and challenges," Renewable Energy, Elsevier, vol. 220(C).
    5. Tao, Siyu & Xu, Qingshan & Feijóo-Lorenzo, Andrés E. & Zheng, Gang & Zhou, Jiemin, 2021. "Optimal layout of a Co-Located wind/tidal current farm considering forbidden zones," Energy, Elsevier, vol. 228(C).

    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. Lande-Sudall, D. & Stallard, T. & Stansby, P., 2019. "Co-located deployment of offshore wind turbines with tidal stream turbine arrays for improved cost of electricity generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 492-503.
    2. Kubik, M.L. & Coker, P.J. & Hunt, C., 2012. "The role of conventional generation in managing variability," Energy Policy, Elsevier, vol. 50(C), pages 253-261.
    3. Levi, Peter G. & Pollitt, Michael G., 2015. "Cost trajectories of low carbon electricity generation technologies in the UK: A study of cost uncertainty," Energy Policy, Elsevier, vol. 87(C), pages 48-59.
    4. Carpintero Moreno, Efrain & Stansby, Peter, 2019. "The 6-float wave energy converter M4: Ocean basin tests giving capture width, response and energy yield for several sites," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 307-318.
    5. Yang, Mao & Wang, Da & Xu, Chuanyu & Dai, Bozhi & Ma, Miaomiao & Su, Xin, 2023. "Power transfer characteristics in fluctuation partition algorithm for wind speed and its application to wind power forecasting," Renewable Energy, Elsevier, vol. 211(C), pages 582-594.
    6. Liu, Wen & Hu, Weihao & Lund, Henrik & Chen, Zhe, 2013. "Electric vehicles and large-scale integration of wind power – The case of Inner Mongolia in China," Applied Energy, Elsevier, vol. 104(C), pages 445-456.
    7. Geels, Frank W. & Kern, Florian & Fuchs, Gerhard & Hinderer, Nele & Kungl, Gregor & Mylan, Josephine & Neukirch, Mario & Wassermann, Sandra, 2016. "The enactment of socio-technical transition pathways: A reformulated typology and a comparative multi-level analysis of the German and UK low-carbon electricity transitions (1990–2014)," Research Policy, Elsevier, vol. 45(4), pages 896-913.
    8. Santo, H. & Taylor, P.H. & Stansby, P.K., 2020. "The performance of the three-float M4 wave energy converter off Albany, on the south coast of western Australia, compared to Orkney (EMEC) in the U.K," Renewable Energy, Elsevier, vol. 146(C), pages 444-459.
    9. Pasta, Edoardo & Faedo, Nicolás & Mattiazzo, Giuliana & Ringwood, John V., 2023. "Towards data-driven and data-based control of wave energy systems: Classification, overview, and critical assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    10. Geels, Frank W. & Ayoub, Martina, 2023. "A socio-technical transition perspective on positive tipping points in climate change mitigation: Analysing seven interacting feedback loops in offshore wind and electric vehicles acceleration," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    11. Santamaría-Bonfil, G. & Reyes-Ballesteros, A. & Gershenson, C., 2016. "Wind speed forecasting for wind farms: A method based on support vector regression," Renewable Energy, Elsevier, vol. 85(C), pages 790-809.
    12. Wasilewski, J. & Baczynski, D., 2017. "Short-term electric energy production forecasting at wind power plants in pareto-optimality context," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 177-187.
    13. Àlex Alonso & Jordi de la Hoz & Helena Martín & Sergio Coronas & Pep Salas & José Matas, 2020. "A Comprehensive Model for the Design of a Microgrid under Regulatory Constraints Using Synthetical Data Generation and Stochastic Optimization," Energies, MDPI, vol. 13(21), pages 1-26, October.
    14. Neeraj Bokde & Andrés Feijóo & Daniel Villanueva & Kishore Kulat, 2018. "A Novel and Alternative Approach for Direct and Indirect Wind-Power Prediction Methods," Energies, MDPI, vol. 11(11), pages 1-19, October.
    15. Chandel, S.S. & Ramasamy, P. & Murthy, K.S.R, 2014. "Wind power potential assessment of 12 locations in western Himalayan region of India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 530-545.
    16. Ahmad, Muhammad Waseem & Mourshed, Monjur & Rezgui, Yacine, 2018. "Tree-based ensemble methods for predicting PV power generation and their comparison with support vector regression," Energy, Elsevier, vol. 164(C), pages 465-474.
    17. Da Liu & Kun Sun & Han Huang & Pingzhou Tang, 2018. "Monthly Load Forecasting Based on Economic Data by Decomposition Integration Theory," Sustainability, MDPI, vol. 10(9), pages 1-22, September.
    18. Sun, Xiaojing & Huang, Diangui & Wu, Guoqing, 2012. "The current state of offshore wind energy technology development," Energy, Elsevier, vol. 41(1), pages 298-312.
    19. He, J.Y. & Chan, P.W. & Li, Q.S. & Huang, Tao & Yim, Steve Hung Lam, 2024. "Assessment of urban wind energy resource in Hong Kong based on multi-instrument observations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
    20. Bracco, Stefano & Delfino, Federico & Pampararo, Fabio & Robba, Michela & Rossi, Mansueto, 2013. "The University of Genoa smart polygeneration microgrid test-bed facility: The overall system, the technologies and the research challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 18(C), pages 442-459.

    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:118:y:2018:i:c:p:627-643. 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.