IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v188y2019ics0360544219317219.html
   My bibliography  Save this article

Quantifying the wind energy potential differences using different WRF initial conditions on Mediterranean coast of Chile

Author

Listed:
  • González-Alonso de Linaje, N.
  • Mattar, C.
  • Borvarán, D.

Abstract

In this work, a comprehensive analysis of WRF initial conditions was performed to estimate the offshore wind power on the coasts of the IV region of Coquimbo, Chile. Three configurations of atmospheric physical models accounting for the planetary boundary layer and surface layer were put under consideration. In addition, sensitivity was estimated by using four physical-numerical simulations: spectral nudging, surface model, 10-days restart and definition of vertical levels. Simulations were carried out for January and July 2013. The results show that the initial condition composed of physical schemes MYNN3 – MYNN – Noah (C3) has the lowest RMSE and highest r2 with 1.748 m s−1 and 0.755 for January, and 2.512 m s−1 RMSE and 0.472 r2 for July. In the sensitivity analysis, the configuration of vertical levels (S3) has the lowest RMSE with 1.812 m s-1 and the highest r2 with 0.732. High seasonal variability between January and July 2013 and WRF initial conditions have an impact on the estimation of the wind power and technical feasibility indicators in the study area, with differences between simulated and LV data in the range of 0.01%–36.3%.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:energy:v:188:y:2019:i:c:s0360544219317219
    DOI: 10.1016/j.energy.2019.116027
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544219317219
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2019.116027?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. Nawri, Nikolai & Petersen, Guðrún Nína & Bjornsson, Halldór & Hahmann, Andrea N. & Jónasson, Kristján & Hasager, Charlotte Bay & Clausen, Niels-Erik, 2014. "The wind energy potential of Iceland," Renewable Energy, Elsevier, vol. 69(C), pages 290-299.
    2. 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.
    3. 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.
    4. Rose, Stephen & Apt, Jay, 2015. "What can reanalysis data tell us about wind power?," Renewable Energy, Elsevier, vol. 83(C), pages 963-969.
    5. 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.
    6. Wang, Yi-Hui & Walter, Ryan K. & White, Crow & Farr, Hayley & Ruttenberg, Benjamin I., 2019. "Assessment of surface wind datasets for estimating offshore wind energy along the Central California Coast," Renewable Energy, Elsevier, vol. 133(C), pages 343-353.
    7. Mattar, Cristian & Borvarán, Dager, 2016. "Offshore wind power simulation by using WRF in the central coast of Chile," Renewable Energy, Elsevier, vol. 94(C), pages 22-31.
    8. 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.
    9. 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.
    10. Mohammadpour Penchah, Mohammadreza & Malakooti, Hossein & Satkin, Mohammad, 2017. "Evaluation of planetary boundary layer simulations for wind resource study in east of Iran," Renewable Energy, Elsevier, vol. 111(C), pages 1-10.
    11. 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.
    12. Celik, Ali N. & Kolhe, Mohan, 2013. "Generalized feed-forward based method for wind energy prediction," Applied Energy, Elsevier, vol. 101(C), pages 582-588.
    13. 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.
    14. Sharp, Ed & Dodds, Paul & Barrett, Mark & Spataru, Catalina, 2015. "Evaluating the accuracy of CFSR reanalysis hourly wind speed forecasts for the UK, using in situ measurements and geographical information," Renewable Energy, Elsevier, vol. 77(C), pages 527-538.
    15. Prósper, Miguel A. & Otero-Casal, Carlos & Fernández, Felipe Canoura & Miguez-Macho, Gonzalo, 2019. "Wind power forecasting for a real onshore wind farm on complex terrain using WRF high resolution simulations," Renewable Energy, Elsevier, vol. 135(C), pages 674-686.
    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. William López-Castrillón & Héctor H. Sepúlveda & Cristian Mattar, 2021. "Off-Grid Hybrid Electrical Generation Systems in Remote Communities: Trends and Characteristics in Sustainability Solutions," Sustainability, MDPI, vol. 13(11), pages 1-29, May.
    2. Salvação, Nadia & Bentamy, Abderrahim & Guedes Soares, C., 2022. "Developing a new wind dataset by blending satellite data and WRF model wind predictions," Renewable Energy, Elsevier, vol. 198(C), pages 283-295.
    3. 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).
    4. Perini de Souza, Noele Bissoli & Sperandio Nascimento, Erick Giovani & Bandeira Santos, Alex Alisson & Moreira, Davidson Martins, 2022. "Wind mapping using the mesoscale WRF model in a tropical region of Brazil," Energy, Elsevier, vol. 240(C).
    5. Pedruzzi, Rizzieri & Silva, Allan Rodrigues & Soares dos Santos, Thalyta & Araujo, Allan Cavalcante & Cotta Weyll, Arthur Lúcide & Lago Kitagawa, Yasmin Kaore & Nunes da Silva Ramos, Diogo & Milani de, 2023. "Review of mapping analysis and complementarity between solar and wind energy sources," Energy, Elsevier, vol. 283(C).
    6. Annas Fauzy & Cheng-Dar Yue & Chien-Cheng Tu & Ta-Hui Lin, 2021. "Understanding the Potential of Wind Farm Exploitation in Tropical Island Countries: A Case for Indonesia," Energies, MDPI, vol. 14(9), pages 1-26, May.
    7. Rober Mamani & Patrick Hendrick, 2022. "Wind Power Potential in Highlands of the Bolivian Andes: A Numerical Approach," Energies, MDPI, vol. 15(12), pages 1-16, June.
    8. 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).
    9. Mateusz Rzeszutek & Adriana Kłosowska & Robert Oleniacz, 2023. "Accuracy Assessment of WRF Model in the Context of Air Quality Modeling in Complex Terrain," Sustainability, MDPI, vol. 15(16), pages 1-27, August.
    10. Cristian Mattar & Felipe Cabello-Españon & Nicolas G. Alonso-de-Linaje, 2021. "Towards a Future Scenario for Offshore Wind Energy in Chile: Breaking the Paradigm," Sustainability, MDPI, vol. 13(13), pages 1-16, June.

    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. Mattar, Cristian & Borvarán, Dager, 2016. "Offshore wind power simulation by using WRF in the central coast of Chile," Renewable Energy, Elsevier, vol. 94(C), pages 22-31.
    2. 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.
    3. 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.
    4. 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.
    5. Argüeso, D. & Businger, S., 2018. "Wind power characteristics of Oahu, Hawaii," Renewable Energy, Elsevier, vol. 128(PA), pages 324-336.
    6. de Assis Tavares, Luiz Filipe & Shadman, Milad & de Freitas Assad, Luiz Paulo & Silva, Corbiniano & Landau, Luiz & Estefen, Segen F., 2020. "Assessment of the offshore wind technical potential for the Brazilian Southeast and South regions," Energy, Elsevier, vol. 196(C).
    7. 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).
    8. Ulazia, Alain & Sáenz, Jon & Ibarra-Berastegui, Gabriel & González-Rojí, Santos J. & Carreno-Madinabeitia, Sheila, 2017. "Using 3DVAR data assimilation to measure offshore wind energy potential at different turbine heights in the West Mediterranean," Applied Energy, Elsevier, vol. 208(C), pages 1232-1245.
    9. 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.
    10. 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).
    11. 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).
    12. 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.
    13. 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).
    14. Pedruzzi, Rizzieri & Silva, Allan Rodrigues & Soares dos Santos, Thalyta & Araujo, Allan Cavalcante & Cotta Weyll, Arthur Lúcide & Lago Kitagawa, Yasmin Kaore & Nunes da Silva Ramos, Diogo & Milani de, 2023. "Review of mapping analysis and complementarity between solar and wind energy sources," Energy, Elsevier, vol. 283(C).
    15. 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.
    16. 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.
    17. Dhunny, A.Z. & Timmons, D.S. & Allam, Z. & Lollchund, M.R. & Cunden, T.S.M., 2020. "An economic assessment of near-shore wind farm development using a weather research forecast-based genetic algorithm model," Energy, Elsevier, vol. 201(C).
    18. 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).
    19. 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.
    20. Rabbani, R. & Zeeshan, M., 2020. "Exploring the suitability of MERRA-2 reanalysis data for wind energy estimation, analysis of wind characteristics and energy potential assessment for selected sites in Pakistan," Renewable Energy, Elsevier, vol. 154(C), pages 1240-1251.

    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:energy:v:188:y:2019:i:c:s0360544219317219. 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/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.