EMS Annual Meeting Abstracts
Vol. 20, EMS2023-114, 2023, updated on 06 Jul 2023
EMS Annual Meeting 2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Analysis of Wind Data and Assessment of Wind Energy Potential in North-West Hungary

Abderrahmane Mendyl1, Peter Peter K. Musyimi3, Gyöngyösi Adrás Zénó1,2, and Tamás Weidinger1
Abderrahmane Mendyl et al.
  • 1Eötvös Loránd University, Institute of Geography and Earth Sciences, Department of Meteorology, Budapest Pázmány Péter prom 1/A, Hungary (mendyl.abderrahmane@gmail.com)
  • 2Eötvös Loránd University, Institute of Chemistry, Budapest Pázmány Péter prom 1/A, Hungary
  • 3ELTE Eötvös Lorand University, Institute of Geography and Earth Sciences, Department of Geophysics and Space Science, Budapest, Hungary

Recently, the world is facing an increasing use of renewable sources of energy that will require a clear understanding of wind energy as an affordable source for sustainability. North-West part of Transdanubia is the windiest region of Hungary. Energy production from two Energon type wind generators are investigated in a wind farm near Mosonmagyaróvár, 10 km from the Austrian border. Wind speed, direction and energy production were recorded with 10 minutes time resolution for a period of 6 years (2010-2015). The hourly wind speed and direction dataset from ERA5 are also investigated. The collection of historical wind data serves the same objective as any other statistical information to improve weather forecasting by knowing what the wind was like on a specific period of time at a specific location and identifying a wind pattern allows you to compare this information to the prediction. This was done using E40 wind-turbine on 65 m height (Max power 600 kW), with mean wind speed of 5.26 ±2.8 m/s and an average power of 103 kW and E70 wind-turbine on 113 m height (Max power 2000 kW), measured wind speed of 5.87±3.12 m/s with an average power of 457 kW. The study adopted Weibull distribution to model wind speeds and applied Power density method to estimate the scale and shape parameters. This is a relatively new, simple formulation and requires less computation. The values of k and c factors were retrieved as functions of the mean wind speed, wind sectors and energy pattern factor respectively.

Wind energy production forecasts were provided by WRF model system for 48 hours with site specific model output statistics. The model was run twice a day (00 and 12 UTC) with 10 km horizontal resolution and 28 vertical level based on GFS model outputs. Uncertainties of energy forecasts were also investigated. In most cases, the model underestimated the wind speed. Further application of the developed model system will be carried out in semi-arid region of Morocco.

How to cite: Mendyl, A., Peter K. Musyimi, P., Adrás Zénó, G., and Weidinger, T.: Analysis of Wind Data and Assessment of Wind Energy Potential in North-West Hungary, EMS Annual Meeting 2023, Bratislava, Slovakia, 4–8 Sep 2023, EMS2023-114, https://doi.org/10.5194/ems2023-114, 2023.