WIND ENERGY GENERATION IN EASTERN SUDAN | CASE STUDY IN RED SEA AREA (Port Sudan City).DE. Dieser Artikel ist nicht verfügbar.
Sprache: Englisch
Verlag: LAP Lambert Academic Publishing
- Softcover
- Neu

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WIND ENERGY GENERATION IN EASTERN SUDAN | CASE STUDY IN RED SEA AREA (Port Sudan [.] | Hashim Mohammed Mahmoud Idress (u. a.) | Taschenbuch | Großformatiges Paperback. Klappenbroschur | Englisch | LAP Lambert Academic Publishing | EAN 9786204738789 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.
Bestandsnummer des Verkäufers 121316882
- Titel
- WIND ENERGY GENERATION IN EASTERN SUDAN | CASE STUDY IN RED SEA AREA (Port Sudan City).DE
- Autor
- Hashim Mohammed Mahmoud Idress (u. a.)
- Verlag
- LAP Lambert Academic Publishing
- Zustand
- Neu
- Einband
- Taschenbuch
- Sprache
- Englisch
- ISBN-10
- 620473878X
- ISBN-13
- 9786204738789
- Verkäuferkataloge
- Bücher
Wind data analysis and evaluation of wind energy potential are critical. Among the critical factors for developing wind energy are the applications and determining the appropriate location for the construction and installation of wind turbines. In this book, we explore the distribution of wind speeds in the Red Sea State, Port Sudan City the place of study. By using the Weibull method, as it is the most accurate and effective method for energy outputs, analyzing and determining the extent of their benefit. The Weibull curve of the probability of dispersion for wind velocities depends on two variables, the shape factor (k), and the scale parameter (c).Weibull parameters were determined based on a data obtained by the Meteorological office of Khartoum city, where measurements were taken and the data readers of the winds from Port Sudan airport, the Meteorology office, In the wind energy conversion system (E w) the dimensional shape parameter and scale parameter are specified, Based on the available data of average wind speeds measured in hours over a time series 2015 to 2017.
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