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Estimation of the Near Future Wind Power Potential in the Black Sea

Author

Listed:
  • Daniel Ganea

    (Department of Mechanical Engineering, ‘Dunarea de Jos’ University of Galati, 47 Domneasca Street, 800 008 Galati, Romania)

  • Elena Mereuta

    (Department of Mechanical Engineering, ‘Dunarea de Jos’ University of Galati, 47 Domneasca Street, 800 008 Galati, Romania)

  • Liliana Rusu

    (Department of Mechanical Engineering, ‘Dunarea de Jos’ University of Galati, 47 Domneasca Street, 800 008 Galati, Romania)

Abstract

The main objective of the present study is to quantify the recent past and explore the near future wind power potential in the Black Sea basin, evaluating the possible changes. Furthermore, an analysis of the wind climate in the target area was also performed. The wind resources have been assessed using the wind fields provided by various databases. Thus, the wind power potential from the recent past was assessed based two different sources covering each one the 30-year period (1981–2010). The first source is the ERA-Interim atmospheric reanalysis provided by the European Centre for Medium-Range Weather Forecasts (ECMWF), while the second source represents the hindcast wind fields simulated by a Regional Climate Model (RCM) and provided by EURO-CORDEX databases. The estimation of the near future wind power potential was made based on wind fields simulated by the same RCM under future climate projections, considering two Representative Concentration Pathways (RCPs) scenarios (RCP4.5 and RCP8.5) and they cover also a 30-year time interval (2021–2050). Information in various reference points were analyzed in detail. Several conclusions resulted from the present work. Thus, as regards the mean wind power potential in winter season, in 51% of the locations a significant increase is projected in the near future (both scenarios). Besides providing a detailed description of the wind conditions from the recent past over the Black Sea basin considering two major sources, the novelty of the present work consists in the fact that it gives an estimation of the expected wind climate in the target area for the near future period and at the same time an evaluation of the climate change impacts on the wind speed and wind power potential.

Suggested Citation

  • Daniel Ganea & Elena Mereuta & Liliana Rusu, 2018. "Estimation of the Near Future Wind Power Potential in the Black Sea," Energies, MDPI, vol. 11(11), pages 1-21, November.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:11:p:3198-:d:183683
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    1. Rusu, Liliana, 2020. "A projection of the expected wave power in the Black Sea until the end of the 21st century," Renewable Energy, Elsevier, vol. 160(C), pages 136-147.
    2. Jung, Christopher & Schindler, Dirk, 2022. "A review of recent studies on wind resource projections under climate change," Renewable and Sustainable Energy Reviews, Elsevier, vol. 165(C).
    3. Victoria Yildirir & Eugen Rusu & Florin Onea, 2022. "Wind Energy Assessments in the Northern Romanian Coastal Environment Based on 20 Years of Data Coming from Different Sources," Sustainability, MDPI, vol. 14(7), pages 1-21, April.
    4. Nezhad, M. Majidi & Neshat, M. & Groppi, D. & Marzialetti, P. & Heydari, A. & Sylaios, G. & Garcia, D. Astiaso, 2021. "A primary offshore wind farm site assessment using reanalysis data: a case study for Samothraki island," Renewable Energy, Elsevier, vol. 172(C), pages 667-679.
    5. Rusu, Eugen, 2022. "Assessment of the wind power dynamics in the North Sea under climate change conditions," Renewable Energy, Elsevier, vol. 195(C), pages 466-475.
    6. Andrés Ruiz & Florin Onea & Eugen Rusu, 2020. "Study Concerning the Expected Dynamics of the Wind Energy Resources in the Iberian Nearshore," Energies, MDPI, vol. 13(18), pages 1-25, September.
    7. Eugen Rusu & Vengatesan Venugopal, 2019. "Special Issue “Offshore Renewable Energy: Ocean Waves, Tides and Offshore Wind”," Energies, MDPI, vol. 12(1), pages 1-4, January.
    8. Jianzhou Wang & Chunying Wu & Tong Niu, 2019. "A Novel System for Wind Speed Forecasting Based on Multi-Objective Optimization and Echo State Network," Sustainability, MDPI, vol. 11(2), pages 1-34, January.

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