IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i2p206-d196328.html
   My bibliography  Save this article

The Potential of Advanced Scatterometer (ASCAT) 12.5 km Coastal Observations for Offshore Wind Farm Site Selection in Irish Waters

Author

Listed:
  • Tiny Remmers

    (MaREI Centre for Marine and Renewable Energy, Beaufort Building, Environmental Research Institute, University College Cork, Ringaskiddy, P43 C573, Ireland)

  • Fiona Cawkwell

    (Department of Geography, University College Cork, College Road, Cork, T12 ND89, Ireland)

  • Cian Desmond

    (MaREI Centre for Marine and Renewable Energy, Beaufort Building, Environmental Research Institute, University College Cork, Ringaskiddy, P43 C573, Ireland)

  • Jimmy Murphy

    (MaREI Centre for Marine and Renewable Energy, Beaufort Building, Environmental Research Institute, University College Cork, Ringaskiddy, P43 C573, Ireland)

  • Eirini Politi

    (Odermatt & Brockmann GmbH, CH-8006 Zürich, Switzerland)

Abstract

The offshore wind industry has seen unprecedented growth over the last few years. In line with this growth, there has been a push towards more exposed sites, farther from shore, in deeper water with consequent increased investor risk. There is therefore a growing need for accurate, reliable, met-ocean data to identify suitable sites, and from which to base preliminary design and investment decisions. This study investigates the potential of hyper-temporal satellite remote sensing Advanced Scatterometer (ASCAT) data in generating information necessary for the optimal site selection of offshore renewable energy infrastructure, and hence providing a cost-effective alternative to traditional techniques, such as in situ data from public or private entities and modelled data. Five years of the ASCAT 12.5 km wind product were validated against in situ weather buoys and showed a strong correlation with a Pearson coefficient of 0.95, when the in situ measurements were extrapolated with the log law. Temporal variations depicted by the ASCAT wind data followed the same inter-seasonal and intra-annual variations as the in situ measurements. A small diurnal bias of 0.12 m s −1 was observed between the descending swath (10:00 to 12:00) and the ascending swath (20:30 to 22:30), indicating that Ireland’s offshore wind speeds are slightly stronger in the daytime, especially in the nearshore areas. Seasonal maps showed that the highest spatial variability in offshore wind speeds are exhibited in winter and summer. The mean wind speed extrapolated at 80 m above sea level showed that Ireland’s mean offshore wind speeds at hub height ranged between 9.6 m s −1 and 12.3 m s −1 . To best represent the offshore wind resource and its spatial distribution, an operational frequency map and a maximum yield frequency map were produced based on the ASCAT wind product in an offshore zone between 20 km and 200 km from the coast. The operational frequency indicates the percentage of time during which the observed local wind speed is between cut-in (3 m/s) and cut-out (25 m/s) for a standard turbine. The operational frequency map shows that the frequency of the wind speed within the cut-in and cut-off range of wind turbines was between 92.4% and 97.2%, while the maximum yield frequency map showed that between 40.6% and 59.5% of the wind speed frequency was included in the wind turbine rated power range. The results showed that the hyper-temporal ASCAT 12.5 km wind speed product (five consecutive years, two observations daily per satellite, two satellites) is representative of wind speeds measured by in situ measurements in Irish waters, and that its ability to depict temporal and spatial variability can assist in the decision-making process for offshore wind farm site selection in Ireland.

Suggested Citation

  • Tiny Remmers & Fiona Cawkwell & Cian Desmond & Jimmy Murphy & Eirini Politi, 2019. "The Potential of Advanced Scatterometer (ASCAT) 12.5 km Coastal Observations for Offshore Wind Farm Site Selection in Irish Waters," Energies, MDPI, vol. 12(2), pages 1-16, January.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:2:p:206-:d:196328
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/2/206/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/2/206/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Charlotte Bay Hasager, 2014. "Offshore winds mapped from satellite remote sensing," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 3(6), pages 594-603, November.
    2. Lange, Marcus & O'Hagan, Anne Marie & Devoy, Robert R.N. & Le Tissier, Martin & Cummins, Valerie, 2018. "Governance barriers to sustainable energy transitions – Assessing Ireland's capacity towards marine energy futures," Energy Policy, Elsevier, vol. 113(C), pages 623-632.
    3. Balog, Irena & Ruti, Paolo M. & Tobin, Isabelle & Armenio, Vincenzo & Vautard, Robert, 2016. "A numerical approach for planning offshore wind farms from regional to local scales over the Mediterranean," Renewable Energy, Elsevier, vol. 85(C), pages 395-405.
    4. Pimenta, Felipe & Kempton, Willett & Garvine, Richard, 2008. "Combining meteorological stations and satellite data to evaluate the offshore wind power resource of Southeastern Brazil," Renewable Energy, Elsevier, vol. 33(11), pages 2375-2387.
    5. Carvalho, D. & Rocha, A. & Gómez-Gesteira, M. & Silva Santos, C., 2017. "Offshore winds and wind energy production estimates derived from ASCAT, OSCAT, numerical weather prediction models and buoys – A comparative study for the Iberian Peninsula Atlantic coast," Renewable Energy, Elsevier, vol. 102(PB), pages 433-444.
    6. Kaldellis, J.K. & Apostolou, D. & Kapsali, M. & Kondili, E., 2016. "Environmental and social footprint of offshore wind energy. Comparison with onshore counterpart," Renewable Energy, Elsevier, vol. 92(C), pages 543-556.
    7. Fernando Porté-Agel & Yu-Ting Wu & Chang-Hung Chen, 2013. "A Numerical Study of the Effects of Wind Direction on Turbine Wakes and Power Losses in a Large Wind Farm," Energies, MDPI, vol. 6(10), pages 1-17, October.
    8. Carton, J.G. & Olabi, A.G., 2010. "Wind/hydrogen hybrid systems: Opportunity for Ireland’s wind resource to provide consistent sustainable energy supply," Energy, Elsevier, vol. 35(12), pages 4536-4544.
    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. Nezhad, M. Majidi & Neshat, M. & Heydari, A. & Razmjoo, A. & Piras, G. & Garcia, D. Astiaso, 2021. "A new methodology for offshore wind speed assessment integrating Sentinel-1, ERA-Interim and in-situ measurement," Renewable Energy, Elsevier, vol. 172(C), pages 1301-1313.
    2. Hadjipetrou, Stylianos & Liodakis, Stelios & Sykioti, Anastasia & Katikas, Loukas & Park, No-Wook & Kalogirou, Soteris & Akylas, Evangelos & Kyriakidis, Phaedon, 2022. "Evaluating the suitability of Sentinel-1 SAR data for offshore wind resource assessment around Cyprus," Renewable Energy, Elsevier, vol. 182(C), pages 1228-1239.
    3. Arun Kumar, Surisetty V.V. & Nagababu, Garlapati & Kumar, Raj, 2019. "Comparative study of offshore winds and wind energy production derived from multiple scatterometers and met buoys," Energy, Elsevier, vol. 185(C), pages 599-611.
    4. O’Connell, Ross & de Montera, Louis & Peters, Jared L. & Horion, Stéphanie, 2020. "An updated assessment of Ireland’s wave energy resource using satellite data assimilation and a revised wave period ratio," Renewable Energy, Elsevier, vol. 160(C), pages 1431-1444.
    5. Majidi Nezhad, M. & Heydari, A. & Groppi, D. & Cumo, F. & Astiaso Garcia, D., 2020. "Wind source potential assessment using Sentinel 1 satellite and a new forecasting model based on machine learning: A case study Sardinia islands," Renewable Energy, Elsevier, vol. 155(C), pages 212-224.
    6. Mingcan Li & Hanbin Xiao & Lin Pan & Chengjun Xu, 2019. "Study of Generalized Interaction Wake Models Systems with ELM Variation for Off-Shore Wind Farms," Energies, MDPI, vol. 12(5), pages 1-32, March.

    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. Tuy, Soklin & Lee, Han Soo & Chreng, Karodine, 2022. "Integrated assessment of offshore wind power potential using Weather Research and Forecast (WRF) downscaling with Sentinel-1 satellite imagery, optimal sites, annual energy production and equivalent C," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    2. Felipe M. Pimenta & Allan R. Silva & Arcilan T. Assireu & Vinicio de S. e Almeida & Osvaldo R. Saavedra, 2019. "Brazil Offshore Wind Resources and Atmospheric Surface Layer Stability," Energies, MDPI, vol. 12(21), pages 1-21, November.
    3. González-Alonso de Linaje, N. & Mattar, C. & Borvarán, D., 2019. "Quantifying the wind energy potential differences using different WRF initial conditions on Mediterranean coast of Chile," Energy, Elsevier, vol. 188(C).
    4. Nikolaos Kokkos & Maria Zoidou & Konstantinos Zachopoulos & Meysam Majidi Nezhad & Davide Astiaso Garcia & Georgios Sylaios, 2021. "Wind Climate and Wind Power Resource Assessment Based on Gridded Scatterometer Data: A Thracian Sea Case Study," Energies, MDPI, vol. 14(12), pages 1-16, June.
    5. Soukissian, Takvor H. & Karathanasi, Flora E., 2017. "On the selection of bivariate parametric models for wind data," Applied Energy, Elsevier, vol. 188(C), pages 280-304.
    6. Tuchtenhagen, Patrícia & Carvalho, Gilvani Gomes de & Martins, Guilherme & Silva, Pollyanne Evangelista da & Oliveira, Cristiano Prestrelo de & de Melo Barbosa Andrade, Lara & Araújo, João Medeiros de, 2020. "WRF model assessment for wind intensity and power density simulation in the southern coast of Brazil," Energy, Elsevier, vol. 190(C).
    7. Takvor H. Soukissian & Dimitra Denaxa & Flora Karathanasi & Aristides Prospathopoulos & Konstantinos Sarantakos & Athanasia Iona & Konstantinos Georgantas & Spyridon Mavrakos, 2017. "Marine Renewable Energy in the Mediterranean Sea: Status and Perspectives," Energies, MDPI, vol. 10(10), pages 1-56, September.
    8. Enevoldsen, Peter & Sovacool, Benjamin K., 2016. "Integrating power systems for remote island energy supply: Lessons from Mykines, Faroe Islands," Renewable Energy, Elsevier, vol. 85(C), pages 642-648.
    9. Sun, Qian & Zou, Meishuai & Guo, Xiaoyan & Yang, Rongjie & Huang, Haitao & Huang, Peng & He, Xiangdong, 2015. "A study of hydrogen generation by reaction of an activated Mg–CoCl2 (magnesium–cobalt chloride) composite with pure water for portable applications," Energy, Elsevier, vol. 79(C), pages 310-314.
    10. Sward, J.A. & Ault, T.R. & Zhang, K.M., 2023. "Spatial biases revealed by LiDAR in a multiphysics WRF ensemble designed for offshore wind," Energy, Elsevier, vol. 262(PA).
    11. Luo, Yu & Shi, Yixiang & Li, Wenying & Cai, Ningsheng, 2014. "Comprehensive modeling of tubular solid oxide electrolysis cell for co-electrolysis of steam and carbon dioxide," Energy, Elsevier, vol. 70(C), pages 420-434.
    12. Díaz-González, Francisco & Sumper, Andreas & Gomis-Bellmunt, Oriol & Villafáfila-Robles, Roberto, 2012. "A review of energy storage technologies for wind power applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(4), pages 2154-2171.
    13. Hossam A. Gabbar, 2021. "Resiliency Analysis of Hybrid Energy Systems within Interconnected Infrastructures," Energies, MDPI, vol. 14(22), pages 1-12, November.
    14. Nyamdash, Batsaikhan & Denny, Eleanor, 2013. "The impact of electricity storage on wholesale electricity prices," Energy Policy, Elsevier, vol. 58(C), pages 6-16.
    15. Rabiee, Abdorreza & Khorramdel, Hossein & Aghaei, Jamshid, 2013. "A review of energy storage systems in microgrids with wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 18(C), pages 316-326.
    16. Ho, Lip-Wah & Lie, Tek-Tjing & Leong, Paul TM & Clear, Tony, 2018. "Developing offshore wind farm siting criteria by using an international Delphi method," Energy Policy, Elsevier, vol. 113(C), pages 53-67.
    17. Antonini, Enrico G.A. & Romero, David A. & Amon, Cristina H., 2019. "Improving CFD wind farm simulations incorporating wind direction uncertainty," Renewable Energy, Elsevier, vol. 133(C), pages 1011-1023.
    18. Rusu, Eugen, 2020. "An evaluation of the wind energy dynamics in the Baltic Sea, past and future projections," Renewable Energy, Elsevier, vol. 160(C), pages 350-362.
    19. Stosic, Tatijana & Telesca, Luciano & Stosic, Borko, 2021. "Multiparametric statistical and dynamical analysis of angular high-frequency wind speed time series," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 566(C).
    20. Song, Xingjuan & Zhang, Dongming, 2014. "Bimetallic Ag–Ni/C particles as cathode catalyst in AFCs (alkaline fuel cells)," Energy, Elsevier, vol. 70(C), pages 223-230.

    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:12:y:2019:i:2:p:206-:d:196328. 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.