IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i13p2635-d246895.html
   My bibliography  Save this article

The Consequences of Air Density Variations over Northeastern Scotland for Offshore Wind Energy Potential

Author

Listed:
  • Alain Ulazia

    (Department of NE and Fluid Mechanics, University of the Basque Country (UPV/EHU), Otaola 29, 20600 Eibar, Spain)

  • Ander Nafarrate

    (Department of NE and Fluid Mechanics, University of the Basque Country (UPV/EHU), Otaola 29, 20600 Eibar, Spain)

  • Gabriel Ibarra-Berastegi

    (Department of NE and Fluid Mechanics, University of the Basque Country (UPV/EHU), Alda. Urkijo, 48013 Bilbao, Spain
    Joint Research Unit (UPV/EHU-IEO) Plentziako Itsas Estazioa, University of the Basque Country (UPV/EHU), Areatza Hiribidea 47, 48620 Plentzia, Spain)

  • Jon Sáenz

    (Joint Research Unit (UPV/EHU-IEO) Plentziako Itsas Estazioa, University of the Basque Country (UPV/EHU), Areatza Hiribidea 47, 48620 Plentzia, Spain
    Department of Applied Physics II, University of the Basque Country (UPV/EHU), B. Sarriena s/n, 48940 Leioa, Spain)

  • Sheila Carreno-Madinabeitia

    (Meteorology Area, Energy and Environment Division, TECNALIA R&I, Basque Country, Spain)

Abstract

Hywind-Scotland is a wind farm in Scotland that for many reasons is at the leading edge of technology and is located at a paradigmatic study area for offshore wind energy assessment. The objective of this paper is to compute the Capacity Factor ( C F ) changes and instantaneous power generation changes due to seasonal and hourly fluctuations in air density. For that reason, the novel ERA5 reanalysis is used as a source of temperature, pressure, and wind speed data. Seasonal results for winter show that C F values increase by 3% due to low temperatures and denser air, with economical profit consequences of tens of thousands (US$). Hourly results show variations of 7% in air density and of 26% in power generation via FAST simulations, emphasizing the need to include air density in short-term wind energy studying.

Suggested Citation

  • Alain Ulazia & Ander Nafarrate & Gabriel Ibarra-Berastegi & Jon Sáenz & Sheila Carreno-Madinabeitia, 2019. "The Consequences of Air Density Variations over Northeastern Scotland for Offshore Wind Energy Potential," Energies, MDPI, vol. 12(13), pages 1-18, July.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:13:p:2635-:d:246895
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/13/2635/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/13/2635/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Unai Elosegui & Igor Egana & Alain Ulazia & Gabriel Ibarra-Berastegi, 2018. "Pitch Angle Misalignment Correction Based on Benchmarking and Laser Scanner Measurement in Wind Farms," Energies, MDPI, vol. 11(12), pages 1-20, December.
    2. Olauson, Jon, 2018. "ERA5: The new champion of wind power modelling?," Renewable Energy, Elsevier, vol. 126(C), pages 322-331.
    3. Dvorak, Michael J. & Archer, Cristina L. & Jacobson, Mark Z., 2010. "California offshore wind energy potential," Renewable Energy, Elsevier, vol. 35(6), pages 1244-1254.
    4. Jung, Christopher & Schindler, Dirk, 2019. "The role of air density in wind energy assessment – A case study from Germany," Energy, Elsevier, vol. 171(C), pages 385-392.
    5. Carvalho, D. & Rocha, A. & Santos, C. Silva & Pereira, R., 2013. "Wind resource modelling in complex terrain using different mesoscale–microscale coupling techniques," Applied Energy, Elsevier, vol. 108(C), pages 493-504.
    6. Engelhorn, Thorsten & Müsgens, Felix, 2018. "How to estimate wind-turbine infeed with incomplete stock data: A general framework with an application to turbine-specific market values in Germany," Energy Economics, Elsevier, vol. 72(C), pages 542-557.
    7. Yamaguchi, Atsushi & Ishihara, Takeshi, 2014. "Assessment of offshore wind energy potential using mesoscale model and geographic information system," Renewable Energy, Elsevier, vol. 69(C), pages 506-515.
    8. Ramirez Camargo, Luis & Gruber, Katharina & Nitsch, Felix, 2019. "Assessing variables of regional reanalysis data sets relevant for modelling small-scale renewable energy systems," Renewable Energy, Elsevier, vol. 133(C), pages 1468-1478.
    9. Carvalho, D. & Rocha, A. & Gómez-Gesteira, M. & Silva Santos, C., 2014. "Sensitivity of the WRF model wind simulation and wind energy production estimates to planetary boundary layer parameterizations for onshore and offshore areas in the Iberian Peninsula," Applied Energy, Elsevier, vol. 135(C), pages 234-246.
    10. Weisser, D, 2003. "A wind energy analysis of Grenada: an estimation using the ‘Weibull’ density function," Renewable Energy, Elsevier, vol. 28(11), pages 1803-1812.
    11. Alain Ulazia & Gabriel Ibarra-Berastegi & Jon Sáenz & Sheila Carreno-Madinabeitia & Santos J. González-Rojí, 2019. "Seasonal Correction of Offshore Wind Energy Potential due to Air Density: Case of the Iberian Peninsula," Sustainability, MDPI, vol. 11(13), pages 1-22, July.
    12. Carvalho, D. & Rocha, A. & Gómez-Gesteira, M. & Silva Santos, C., 2014. "WRF wind simulation and wind energy production estimates forced by different reanalyses: Comparison with observed data for Portugal," Applied Energy, Elsevier, vol. 117(C), pages 116-126.
    13. Ulazia, Alain & Saenz, Jon & Ibarra-Berastegui, Gabriel, 2016. "Sensitivity to the use of 3DVAR data assimilation in a mesoscale model for estimating offshore wind energy potential. A case study of the Iberian northern coastline," Applied Energy, Elsevier, vol. 180(C), pages 617-627.
    14. O’Keeffe, Aoife & Haggett, Claire, 2012. "An investigation into the potential barriers facing the development of offshore wind energy in Scotland: Case study – Firth of Forth offshore wind farm," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(6), pages 3711-3721.
    15. Rogier Floors & Morten Nielsen, 2019. "Estimating Air Density Using Observations and Re-Analysis Outputs for Wind Energy Purposes," Energies, MDPI, vol. 12(11), pages 1-12, May.
    16. Carvalho, D. & Rocha, A. & Gómez-Gesteira, M. & Silva Santos, C., 2014. "Offshore wind energy resource simulation forced by different reanalyses: Comparison with observed data in the Iberian Peninsula," Applied Energy, Elsevier, vol. 134(C), pages 57-64.
    17. Gökçek, Murat & Bayülken, Ahmet & Bekdemir, Şükrü, 2007. "Investigation of wind characteristics and wind energy potential in Kirklareli, Turkey," Renewable Energy, Elsevier, vol. 32(10), pages 1739-1752.
    18. Kecskemety, Krista M. & McNamara, Jack J., 2016. "Influence of wake dynamics on the performance and aeroelasticity of wind turbines," Renewable Energy, Elsevier, vol. 88(C), pages 333-345.
    19. Esteban, Miguel & Leary, David, 2012. "Current developments and future prospects of offshore wind and ocean energy," Applied Energy, Elsevier, vol. 90(1), pages 128-136.
    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. Gualtieri, G., 2022. "Analysing the uncertainties of reanalysis data used for wind resource assessment: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    2. Maddi Aizpurua-Etxezarreta & Sheila Carreno-Madinabeitia & Alain Ulazia & Jon Sáenz & Aitor Saenz-Aguirre, 2022. "Long-Term Freezing Temperatures Frequency Change Effect on Wind Energy Gain (Eurasia and North America, 1950–2019)," Sustainability, MDPI, vol. 14(9), pages 1-15, May.
    3. Giovanni Gualtieri, 2021. "Reliability of ERA5 Reanalysis Data for Wind Resource Assessment: A Comparison against Tall Towers," Energies, MDPI, vol. 14(14), pages 1-21, July.
    4. Shengjin Wang & Hongru Yang & Quoc Bao Pham & Dao Nguyen Khoi & Pham Thi Thao Nhi, 2020. "An Ensemble Framework to Investigate Wind Energy Sustainability Considering Climate Change Impacts," Sustainability, MDPI, vol. 12(3), pages 1-17, January.
    5. Carreno-Madinabeitia, Sheila & Ibarra-Berastegi, Gabriel & Sáenz, Jon & Ulazia, Alain, 2021. "Long-term changes in offshore wind power density and wind turbine capacity factor in the Iberian Peninsula (1900–2010)," Energy, Elsevier, vol. 226(C).
    6. Ahmed Elkhatat & Shaheen A. Al-Muhtaseb, 2023. "Combined “Renewable Energy–Thermal Energy Storage (RE–TES)” Systems: A Review," Energies, MDPI, vol. 16(11), pages 1-46, June.
    7. Alain Ulazia & Gabriel Ibarra-Berastegi, 2020. "Problem-Based Learning in University Studies on Renewable Energies: Case of a Laboratory Windpump," Sustainability, MDPI, vol. 12(6), pages 1-15, 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. Ulazia, Alain & Sáenz, Jon & Ibarra-Berastegi, Gabriel & González-Rojí, Santos J. & Carreno-Madinabeitia, Sheila, 2019. "Global estimations of wind energy potential considering seasonal air density changes," Energy, Elsevier, vol. 187(C).
    2. Alain Ulazia & Gabriel Ibarra-Berastegi & Jon Sáenz & Sheila Carreno-Madinabeitia & Santos J. González-Rojí, 2019. "Seasonal Correction of Offshore Wind Energy Potential due to Air Density: Case of the Iberian Peninsula," Sustainability, MDPI, vol. 11(13), pages 1-22, July.
    3. Ulazia, Alain & Saenz, Jon & Ibarra-Berastegui, Gabriel, 2016. "Sensitivity to the use of 3DVAR data assimilation in a mesoscale model for estimating offshore wind energy potential. A case study of the Iberian northern coastline," Applied Energy, Elsevier, vol. 180(C), pages 617-627.
    4. 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).
    5. Yuan, Renyu & Ji, Wenju & Luo, Kun & Wang, Jianwen & Zhang, Sanxia & Wang, Qiang & Fan, Jianren & Ni, MingJiang & Cen, Kefa, 2017. "Coupled wind farm parameterization with a mesoscale model for simulations of an onshore wind farm," Applied Energy, Elsevier, vol. 206(C), pages 113-125.
    6. Soares, Pedro M.M. & Lima, Daniela C.A. & Cardoso, Rita M. & Nascimento, Manuel L. & Semedo, Alvaro, 2017. "Western Iberian offshore wind resources: More or less in a global warming climate?," Applied Energy, Elsevier, vol. 203(C), pages 72-90.
    7. Gualtieri, G., 2022. "Analysing the uncertainties of reanalysis data used for wind resource assessment: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    8. 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.
    9. Gil Ruiz, Samuel Andrés & Cañón Barriga, Julio Eduardo & Martínez, J. Alejandro, 2022. "Assessment and validation of wind power potential at convection-permitting resolution for the Caribbean region of Colombia," Energy, Elsevier, vol. 244(PB).
    10. 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).
    11. Salvação, N. & Guedes Soares, C., 2018. "Wind resource assessment offshore the Atlantic Iberian coast with the WRF model," Energy, Elsevier, vol. 145(C), pages 276-287.
    12. de Assis Tavares, Luiz Filipe & Shadman, Milad & Assad, Luiz Paulo de Freitas & Estefen, Segen F., 2022. "Influence of the WRF model and atmospheric reanalysis on the offshore wind resource potential and cost estimation: A case study for Rio de Janeiro State," Energy, Elsevier, vol. 240(C).
    13. Nagababu, Garlapati & Kachhwaha, Surendra Singh & Naidu, Natansh K. & Savsani, Vimal, 2017. "Application of reanalysis data to estimate offshore wind potential in EEZ of India based on marine ecosystem considerations," Energy, Elsevier, vol. 118(C), pages 622-631.
    14. Carvalho, D. & Rocha, A. & Gómez-Gesteira, M. & Silva Santos, C., 2014. "Sensitivity of the WRF model wind simulation and wind energy production estimates to planetary boundary layer parameterizations for onshore and offshore areas in the Iberian Peninsula," Applied Energy, Elsevier, vol. 135(C), pages 234-246.
    15. Chen, Xinping & Foley, Aoife & Zhang, Zenghai & Wang, Kaimin & O'Driscoll, Kieran, 2020. "An assessment of wind energy potential in the Beibu Gulf considering the energy demands of the Beibu Gulf Economic Rim," Renewable and Sustainable Energy Reviews, Elsevier, vol. 119(C).
    16. Erdong Zhao & Jing Zhao & Liwei Liu & Zhongyue Su & Ning An, 2015. "Hybrid Wind Speed Prediction Based on a Self-Adaptive ARIMAX Model with an Exogenous WRF Simulation," Energies, MDPI, vol. 9(1), pages 1-20, December.
    17. Carreno-Madinabeitia, Sheila & Ibarra-Berastegi, Gabriel & Sáenz, Jon & Ulazia, Alain, 2021. "Long-term changes in offshore wind power density and wind turbine capacity factor in the Iberian Peninsula (1900–2010)," Energy, Elsevier, vol. 226(C).
    18. Carvalho, D. & Rocha, A. & Gómez-Gesteira, M. & Silva Santos, C., 2014. "Offshore wind energy resource simulation forced by different reanalyses: Comparison with observed data in the Iberian Peninsula," Applied Energy, Elsevier, vol. 134(C), pages 57-64.
    19. Giovanni Gualtieri, 2021. "Reliability of ERA5 Reanalysis Data for Wind Resource Assessment: A Comparison against Tall Towers," Energies, MDPI, vol. 14(14), pages 1-21, July.
    20. Santos, F. & Gómez-Gesteira, M. & deCastro, M. & Añel, J.A. & Carvalho, D. & Costoya, Xurxo & Dias, J.M., 2018. "On the accuracy of CORDEX RCMs to project future winds over the Iberian Peninsula and surrounding ocean," Applied Energy, Elsevier, vol. 228(C), pages 289-300.

    More about this item

    Keywords

    ERA5; air density; offshore wind energy; FAST; Scotland;
    All these keywords.

    JEL classification:

    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:gam:jeners:v:12:y:2019:i:13:p:2635-:d:246895. 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.