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001-es BibID:	BIBFORM089362
Első szerző:	Hadnagy István (meteorológus)
Cím:	Climatic conditions of wind energy use in the Polonyna Borzhava Mountains (Transcarpathia, Ukraine) / Hadnagy István, Tar Károly, Lázár István, Kohut Erzsébet
Dátum:	2020
Megjegyzések:	This paper deals with the statistical structure, seasonal peculiarities of wind climate at meteorological station Play (in Ukrainian: meteorolog?čnastanc?âPlaj, location: 48°40'1'' N; 23°11'51'' E, 1330 m above sea level) located in the Polonyna Borzhava Mountain of the North-Eastern Carpathians. Furthermore, it determines significant parameters of exploiting wind energy. Weibull distribution was applied to determine specific wind power and characterize its annual course. Wind speed was analyzed together with the available daily and yearly course of wind power. Wind power density determined by means of distribution parameters at Play is 169.0 W/m2 and 8.0-9.0 m/s winds yield most energy over the year. The minimum number of energetically utilizable wind hours is in summer, while its maximum is in spring. On the territory represented by the measuring point, a 3 m/s start-up speed wind turbine could operate 63% time over the year. Finally, the periods were specified, and those wind directions were chosen that are richer in wind energy than others. The most frequent characteristic wind direction with the highest mean velocity in each season is southwestern; its average relative frequency is 34.4%. Mean speed of characteristic wind directions is 5.8 m/s. South-western wind direction yields 47% of the total energy.
Tárgyszavak:	Természettudományok Földtudományok idegen nyelvű folyóiratközlemény hazai lapban folyóiratcikk wind energy wind speed wind power density Transcarpathia
Megjelenés:	DRC, Sustainable Future: Journal of Environment, Agriculture, and Energy. - 1 : 2 (2020), p. 136-146. -
További szerzők:	Tar Károly (1947-) (klimatológus) Lázár István (1986-) (geográfus) Kohut Erzsébet
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001-es BibID:	BIBFORM125128
035-os BibID:	(Scopus)85207309110 (WoS)001345756700001
Első szerző:	Lázár István (geográfus)
Cím:	Comparative examinations of wind speed and energy extrapolation methods using remotely sensed data - A case study from Hungary / István Lázár, István Hadnagy, Boglárka Bertalan-Balázs, László Bertalan, Sándor Szegedi
Dátum:	2024
ISSN:	2590-1745
Megjegyzések:	Exact knowledge of wind energy potential is a fundamental issue in wind energy utilization. The vertical changes in wind speeds, that is, the wind profile, have a predominant impact on the wind energy available at a location because the kinetic energy of moving air is proportional to the square of the wind speed. Roughness describes the resistance of a 3D surface to moving air. The exponent α of the power law of Hellmann and the roughness length (z0) are two parameters that describe the effects of the roughness of the surface on the wind profile. They can be used for the vertical extrapolation of wind speeds. The exponent α can be determined using multiple height level wind speed measurement data, whereas a reliable technique for the calculation of the roughness length requires detailed knowledge of the 3D geometry of the measurement site. In the present study, the exponent α was calculated based on SODAR wind speed measurements, while (z0) was determined using a combination of GIS and UAS-based aerial survey methods. Wind speeds measured at 50?m were extrapolated for height levels of 80, 90, 100, 110, and 120?m using dynamic power law exponent values. Wind power was determined using the power law (method V1), roughness length (method V2), frequency distribution (method W-RF), and gamma distribution (method W-G), and Windographer software was compared to the values calculated from the empirical (measured) wind speeds. A comparative statistical analysis of the datasets of the power law and roughness length methods on monthly/diurnal, annual/diurnal, and month/direction contexts showed no significant differences at all height levels. Differences can be detected in the distribution of the signs of the differences at heights of 80 and 120?m for the entire dataset. Underestimation was dominant with a significant frequency (over 70?%) in the case of both methods and heights. There were no significant differences between the wind power estimations provided by the different methods, and all the methods involved in the study underestimated the wind speeds and wind energy potential for each height level. Methods V1 and V2 can be used alternatively, depending on the input data available for analysis. The major advantage of method V2 is that it provides the same accuracy as V1, which requires a UAS-based aerial survey at the beginning, but continuous wind measurements must be performed at a lower height only. This means that there is no need for a high measurement tower, which makes the measurements simpler, more cost-effective, and causes much less disturbance to the environment. Another important advantage of the methods presented here is that they use a dynamic approach of power law exponent values that provide a more realistic estimation of wind speed and energy on a diurnal scale.
Tárgyszavak:	Természettudományok Földtudományok idegen nyelvű folyóiratközlemény külföldi lapban folyóiratcikk wind profile remote sensing power law roughness length weibull distribution wind energy potential estimation
Megjelenés:	Energy Conversion and Management: X. - 24 (2024), p. 1-11. -
További szerzők:	Hadnagy István (1986-) (meteorológus) Balázs Boglárka (1985-) (geográfus) Bertalan László (1989-) (geográfus) Szegedi Sándor (1970-) (klimatológus)
Pályázati támogatás:	TKP2021-NKTA-34 Egyéb
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001-es BibID:	BIBFORM106201
035-os BibID:	(Scopus)85143897754
Első szerző:	Tar Károly (klimatológus)
Cím:	Statistical method for estimating average daily wind speed during the day / Károly Tar, István Lázár, István Hadnagy
Dátum:	2022
ISSN:	0324-6329
Megjegyzések:	Meteorologists keep searching and running models to provide the most accurate forecast of wind speed in addition to gaining a more detailed understanding of the wind conditions in Hungary. Wind speed and wind energy estimates, forecasts, and their verification are based on wind statistics from a longer or shorter previous period. Consequently, in addition to dynamic methods, purely statistical models also play an important role, i.e., findings that can be obtained from the statistical analysis of the existing database of measured data. The successive phases of the statistical method for producing scientific or operational information that can be extracted from measured, corrected, and stored meteorological data are generally: statistical analysis/processing, creating, verification, and application of the model, recording of the required information. The targeted information in this paper is the daily average of hourly wind speeds. The exact average of this time series can only be determined after the last measurement. To estimate this average during the day, however, the so-called sliding average model has been developed, which can be applied to any climatic element if its measured values are recorded at regular times over a certain period of time. The results presented in this paper are recommended for the preparation of the so-called "timetable", which is one of the most difficult problems for wind farm operators. This is basically the estimation of the amount of electricity produced the following day over short periods. It would be a significant help in the above if we can determine the probability of a decrease or increase in the average wind speed on the next day (and with it, the average daily wind power), or which of these two probabilities is greater. This requires an estimate of average wind speed of the next day. In addition, the results of one of our previous studies on the statistical structure of day-to-day changes in average daily wind speeds were also used. According to the results of the monthly testing of the model over a given period, the frequency of good estimates is between 80.6 % and 54.8%.
Tárgyszavak:	Természettudományok Földtudományok idegen nyelvű folyóiratközlemény hazai lapban folyóiratcikk sliding average model wind statistics wind farms daily wind power event frequency Hungary
Megjelenés:	Időjárás. - 126 : 4 (2022), p. 481-510. -
További szerzők:	Lázár István (1986-) (geográfus) Hadnagy István (1986-) (meteorológus)
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