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Wind resource assessment offshore the Atlantic Iberian coast with the WRF model

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  • Salvação, N.
  • Guedes Soares, C.

Abstract

A ten year wind hindcast is presented for the Iberian Peninsula coast. Simulations are conducted with the WRF model at 9 and 3 km of spatial resolution and 6 hourly output. The amount of energy that can be generated by an energy conversion device as well as the annual operating hours and capacity factors are estimated and presented as wind resource maps. The spatial variation of the error and the annual and seasonal variations of the wind energy resource are also depicted. Comparisons with observational data show the WRF model is a proficient wind generating tool, whether in coastal waters as in the open ocean, even when the model is run at a lower spatial resolution. The results show that wind farm planning offshore the Iberian coast is an eligible choice, with average annual energy density reaching up to 971 W/m2, 549 W/m2 and 398 W/m2 in the north, centre and southern regions respectively. The potential production by offshore energy conversion devices in selected sub-regions further indicates that wind farm implementation offshore the Iberian coast will produce high amounts of electricity.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:energy:v:145:y:2018:i:c:p:276-287
    DOI: 10.1016/j.energy.2017.12.101
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    as
    1. Cheng, William Y.Y. & Liu, Yubao & Bourgeois, Alfred J. & Wu, Yonghui & Haupt, Sue Ellen, 2017. "Short-term wind forecast of a data assimilation/weather forecasting system with wind turbine anemometer measurement assimilation," Renewable Energy, Elsevier, vol. 107(C), pages 340-351.
    2. Kalogeri, Christina & Galanis, George & Spyrou, Christos & Diamantis, Dimitris & Baladima, Foteini & Koukoula, Marika & Kallos, George, 2017. "Assessing the European offshore wind and wave energy resource for combined exploitation," Renewable Energy, Elsevier, vol. 101(C), pages 244-264.
    3. Amirinia, Gholamreza & Kamranzad, Bahareh & Mafi, Somayeh, 2017. "Wind and wave energy potential in southern Caspian Sea using uncertainty analysis," Energy, Elsevier, vol. 120(C), pages 332-345.
    4. 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.
    5. Murthy, K.S.R. & Rahi, O.P., 2017. "A comprehensive review of wind resource assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 1320-1342.
    6. Giannaros, Theodore M. & Melas, Dimitrios & Ziomas, Ioannis, 2017. "Performance evaluation of the Weather Research and Forecasting (WRF) model for assessing wind resource in Greece," Renewable Energy, Elsevier, vol. 102(PA), pages 190-198.
    7. 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.
    8. Milanese, Marco & Tornese, Ljuba & Colangelo, Gianpiero & Laforgia, Domenico & de Risi, Arturo, 2017. "Numerical method for wind energy analysis applied to Apulia Region, Italy," Energy, Elsevier, vol. 128(C), pages 1-10.
    9. 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.
    10. 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.
    11. Zhao, Jing & Guo, Zhen-Hai & Su, Zhong-Yue & Zhao, Zhi-Yuan & Xiao, Xia & Liu, Feng, 2016. "An improved multi-step forecasting model based on WRF ensembles and creative fuzzy systems for wind speed," Applied Energy, Elsevier, vol. 162(C), pages 808-826.
    12. Ali, E.S. & Abd Elazim, S.M. & Abdelaziz, A.Y., 2016. "Ant Lion Optimization Algorithm for Renewable Distributed Generations," Energy, Elsevier, vol. 116(P1), pages 445-458.
    13. Dvorak, Michael J. & Archer, Cristina L. & Jacobson, Mark Z., 2010. "California offshore wind energy potential," Renewable Energy, Elsevier, vol. 35(6), pages 1244-1254.
    14. 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.
    15. Oh, Ki-Yong & Kim, Ji-Young & Lee, Jun-Shin & Ryu, Ki-Wahn, 2012. "Wind resource assessment around Korean Peninsula for feasibility study on 100 MW class offshore wind farm," Renewable Energy, Elsevier, vol. 42(C), pages 217-226.
    16. 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.
    17. Zheng, Chong Wei & Li, Chong Yin & Pan, Jing & Liu, Ming Yang & Xia, Lin Lin, 2016. "An overview of global ocean wind energy resource evaluations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 1240-1251.
    18. Carvalho, D. & Rocha, A. & Gómez-Gesteira, M. & Silva Santos, C., 2017. "Potential impacts of climate change on European wind energy resource under the CMIP5 future climate projections," Renewable Energy, Elsevier, vol. 101(C), pages 29-40.
    19. Hong, Lixuan & Möller, Bernd, 2011. "Offshore wind energy potential in China: Under technical, spatial and economic constraints," Energy, Elsevier, vol. 36(7), pages 4482-4491.
    20. Chancham, Chana & Waewsak, Jompob & Gagnon, Yves, 2017. "Offshore wind resource assessment and wind power plant optimization in the Gulf of Thailand," Energy, Elsevier, vol. 139(C), pages 706-731.
    21. Pacheco, A. & Gorbeña, E. & Sequeira, C. & Jerez, S., 2017. "An evaluation of offshore wind power production by floatable systems: A case study from SW Portugal," Energy, Elsevier, vol. 131(C), pages 239-250.
    22. Staffell, Iain & Pfenninger, Stefan, 2016. "Using bias-corrected reanalysis to simulate current and future wind power output," Energy, Elsevier, vol. 114(C), pages 1224-1239.
    23. Langodan, Sabique & Viswanadhapalli, Yesubabu & Dasari, Hari Prasad & Knio, Omar & Hoteit, Ibrahim, 2016. "A high-resolution assessment of wind and wave energy potentials in the Red Sea," Applied Energy, Elsevier, vol. 181(C), pages 244-255.
    24. Ban, Marko & Perković, Luka & Duić, Neven & Penedo, Ricardo, 2013. "Estimating the spatial distribution of high altitude wind energy potential in Southeast Europe," Energy, Elsevier, vol. 57(C), pages 24-29.
    25. Zhao, Jing & Guo, Yanling & Xiao, Xia & Wang, Jianzhou & Chi, Dezhong & Guo, Zhenhai, 2017. "Multi-step wind speed and power forecasts based on a WRF simulation and an optimized association method," Applied Energy, Elsevier, vol. 197(C), pages 183-202.
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