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Tytuł artykułu

Method for wind turbine selection basing on in-field measurements

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The following paper covers a method for wind turbine selection with a horizontal axis of rotation basing on real in-field measurements of wind conditions. The basic meteorological properties and characteristics obtained during measurement campaigns using necessary equipment as well as the used methodology are vital for successful investment in wind farm. The main goal of in-field investigation is to collect meteorological data using a measurement mast installed at the possible future wind farm location. The conducted measurement campaign provided wind directions, velocities and wind blast parameters. The measurements were conducted in the northern Poland using measuring system installed on 100 meter high mast. The system was equipped with all devices necessary to measure and record the basic wind parameters. The reliability of measurements was verified using statistical data for the Weitbull distribution and the wind rose. In this way, the energy potential of raw air stream that could possibly drive a wind turbine was determined. Among 6 pre-selected wind turbine types, the optimal one for a given location was proposed.
Rocznik
Strony
77--84
Opis fizyczny
Bibliogr. 25 poz., rys., tab., wykr.
Twórcy
  • Faculty of Mechanical Engineering, Department of Energetics, Koszalin University of Technology, Racławicka 15-17, 75-620, Koszalin, Poland
  • Faculty of Mechanical Engineering, Department of Energetics, Koszalin University of Technology, Poland
  • Faculty of Civil Engineering, Environmental and Geodetic Sciences, Koszalin University of Technology, Poland
Bibliografia
  • 1. Mokrzycki E., Ney R., Siemek J. (2008). Global energy resources - conclusions for Poland. Energy Field, No 6, pp. 2-13. (in Polish)
  • 2. Magiera J. (2010). Energy, man, environment. AGH University of Science and Technology, Krakow. (in Polish)
  • 3. Zimny J. (2010). Renewable energy sources in low energy buildings. PGA AGH, Krakow-Warsaw. (in Polish)
  • 4. Akpinar E., Akpinar S. (2005). An assessment on seasonal analysis of wind energy characteristics and wind turbine characteristics. Energy Conversion and Management, Vol. 46(11), pp. 1848-1867.
  • 5. Celik A. (2003). Energy output estimation for small-scale wind power generators using Weibull-representative wind data. Journal of Wind Engineering and Industrial Aerodynamics, Vol. 91(5), pp. 693-707.
  • 6. Jaramillo O., Borja M. (2004). Wind speed analysis in La Ventosa, Mexico: a bimodal probability distribution case. Renewable Energy, Vol. 29, pp. 1613-1630.
  • 7. Rehman S. (2004). Wind energy resources assessment for Yanbo, Saudi Arabia. Energy Conversion and Management, Vol. 45(13), pp. 2019-2032.
  • 8. Akdag S., Dinler A. (2009). A new method to estimate Weibull parameters for wind energy applications. Energy Conversion and Management, Vol. 50(7), pp. 1761-1766.
  • 9. Akdag S., Bagiorgas H., Mihalakakou G. (2010). Use of two-component Weibull mixtures in the analysis of wind speed in the Eastern Mediterranean. Applied Energy, Vol. 87(8), pp. 2566-2573.
  • 10. Zhou J., Erdem E., Li G., Shi J. (2010). Comprehensive evaluation of wind speed distribution models: A case study for North Dakota sites. Energy Conversion and Management, Vol. 51, pp. 1449-1458.
  • 11. Ramirez P., Carta J. A. (2006). The use of wind probability distributions derived from the maximum entropy principle in the analysis of wind energy. A case study. Energy Conversion and Management, Vol. 47(15), pp. 2564-2577.
  • 12. Li M., Li X. (2005). Investigation of wind characteristics and assessment of wind energy potential for Waterloo region, Canada. Energy Conversion and Management, Vol. 46, pp. 3014-3033.
  • 13. Tar K. (2008). Some statistical characteristics of monthly average wind speed at various heights. Renewable and Sustainable Energy Reviews, Vol. 12(6), pp. 1712-1724.
  • 14. Morales J., Minguez R., Conejo A. (2010). A methodology to generate statistically dependent wind speed scenarios. Applied Energy, Vol. 87, pp. 843-855.
  • 15. Cadenas E., Rivera W. (2007). Wind speed forecasting in the South Coast of Oaxaca, México. Renewable Energy, Vol. 32, pp. 2116-2128.
  • 16. Sahin A., Sen Z. (2001). First-order Markov chain approach to wind speed modelling. Journal of Wind Engineering and Industrial Aerodynamics, Vol. 89, pp. 263-269.
  • 17. Bechrakis D., Deane J., McKeogh E. (2004). Wind resource assessment of an area using short term data correlated to a long term data set. Solar Energy, Vol. 76(6), pp. 725-732.
  • 18. IEC 61400-12-1:2005 (2005): Wind turbines: Part 21-1: Power performance of electricity producing wind turbines. IEC Genewa, Switzerland.
  • 19. PN-EN 61400-12-1:2006 (2002): Wind turbines. Power performance measurements of electricity producing wind turbines. PKN Poland.
  • 20. Jakubowski M., Mech Ł., Wolniewicz K. (2017). A methodology of wind turbines selection for the given wind conditions. Journal of Mechanical and Energy Engineering, Vol. 1(41), No 2, pp. 171-178.
  • 21. Zagubień A. (2017). The Results of the Measurements and Analyses of Impact of Wind Farms on Acoustic Climate. Rocznik Ochrona Srodowiska, Vol. 19, pp. 527-539. (in Polish)
  • 22. Zwoździak J., Zwoździak A., Szczurek A. (1998). Meteorology in the protection of the atmosphere. Oficyna Wydawnicza Politechniki Wrocławskiej, Wroclaw. (in Polish)
  • 23. Betz A. (1920). Das Maximum der theoretisch möglichen Ausnutzung des Windes durch Windmotoren. Zeitschrift für das gesamte Turbinenwesen, No 26, pp. 307-309. (in German)
  • 24. Okulov V., Sørensen J. (2008). Refined Betz limit for rotors with a finite number of blades. Wind Energy, Vol. 11, pp. 415-426.
  • 25. Vaz J., Wood D. (2016). Performance analysis of wind turbines at low tip-speed ratio using the Betz-Goldstein model. Energy Conversion and Management, Vol. 126, pp. 662-672.
Uwagi
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-0d2bff07-708c-4aa6-9670-ff30ae10857e
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