Magyar
Toggle navigation
Tudóstér
Magyar
Tudóstér
Keresés
Egyszerű keresés
Összetett keresés
CCL keresés
Egyszerű keresés
Összetett keresés
CCL keresés
Böngészés
Saját polc tartalma
(
0
)
Korábbi keresések
CCL parancs
CCL
Összesen 2 találat.
#/oldal:
12
36
60
120
Rövid
Hosszú
MARC
Részletezés:
Rendezés:
Szerző növekvő
Szerző csökkenő
Cím növekvő
Cím csökkenő
Dátum növekvő
Dátum csökkenő
1.
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
Internet cím:
Szerző által megadott URL
DOI
Intézményi repozitóriumban (DEA) tárolt változat
Borító:
Saját polcon:
2.
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)
Internet cím:
Szerző által megadott URL
DOI
Intézményi repozitóriumban (DEA) tárolt változat
Borító:
Saját polcon:
Rekordok letöltése
1
Corvina könyvtári katalógus v8.2.27
© 2023
Monguz kft.
Minden jog fenntartva.