Gharyan Şehri (Libya) Rüzgar Verilerine Dayalı Dikey Eksenli Rüzgar Türbini Kurulumu

Year 2022, Volume: 25 Issue: 3, 975 - 984, 01.10.2022

Nagi Nassir , Bahadir Acar , Abdel Karim Amar Fahed

https://doi.org/10.2339/politeknik.781397

Abstract

Rüzgar enerjisinin değerlendirilmesi, herhangi bir yerde bulunan potansiyel rüzgar enerjisi hakkında uzmanları bilgilendiren entegre analizlerin bir biçimidir. Bu tür değerlendirmenin başlangıç noktası, belirli bir yerde yaygın olarak meydana gelen rüzgar modellerini anlamaktır. Bunu, rüzgar verileri toplama ve toplanan verileri analiz etme izler. Bu makale, birinci ve ikinci bölgelerin kapsamlı bir çalışmasıdır. Bu nedenle, ortalama rüzgar hızı, yön verisi, kısa vadeli varyasyonlar (veya rüzgarlar), yıllık, mevsimsel ve hatta günlük değişiklikler / varyasyonlar ve yüksekliğe bağlı varyasyonlar gibi birkaç parametre dikkate alınmalıdır. Bahsedilen tüm parametreler sahaya özgü olduğundan, uzun bir süre boyunca yerinde ölçümlerle doğru bir şekilde belirlenebilir. Bu çalışma, rüzgar değerlendirmesi ve potansiyel rüzgar enerjisi üzerine odaklandığından Gharyan şehri bir konum olarak seçildi ve alt konumları Gharyan 1, 2, 3 ve 4 olarak adlandırıldı. İlk olarak, rüzgar enerjisi kaynağı ile ilgili konumun yakınında bulunan meteoroloji istasyonlarından alınan veriler arka planda toplandı. Genellikle, her bir konum için 3 saatlik uzun vadeli rüzgar verileri kullanılır ve daha sonra, göbek yüksekliğindeki gerçek rüzgar hızını bulmak için rüzgar verilerinin yeniden hesaplanması yapılır. Önemli hesaplama parametreleri arasında, önerilen her bir saha için hesaplanması gereken Weibull dağılımı, ortalama rüzgar hızı, yıllık kapasite faktörü ve yıllık enerji faktörü yer alır. Yıllık kapasite ve enerji faktörlerinin hesaplanması, genellikle Vestas (V60, 850kW) olarak adlandırılan rüzgar türbinini seçmek için gereklidir. Bu makale, Libya'daki bazı tesislerin, özellikle yıllık enerji, kapasite faktörü ve kabul edilebilir enerji üretim kapasitesinin kaydedildiği Gharyan'da bulunan dört bölgede yeterli rüzgar enerjisine sahip olduğunu açıkça göstermektedir.

Keywords

şekil parametresi, ölçek parametresi, yıllık kapasite faktörü, kümülatif Weibull dağılımı

Vertical Axis Wind Turbine Installation Based on Wind Data Collected in Gharyan City, Libya

Abstract

Assessing the potential of wind energy involves an integrated analysis approach, the conclusions of which inform the experts of the field about the possibilities of harnessing wind energy on a certain location. This type of analysis is made of multiple steps, starting from observing and understanding commonly occurring wind patterns at the designated site, followed by collection of data and finally analysis. The current paper is an extended study on the first two steps where several parameters such as wind’s average speed and its direction, as well as various changes such as short-term ones (or gusts), yearly, seasonal, and even daily changes, and height-related variations were collected. Since the above-mentioned parameters are site-specific, they can be accurately determined through on-site measurements during extended time periods. The site for this study is the city of Gharyan in Libya which was divided into four sub-locations. Data were gathered from meteorological stations located in the vicinity of the designated area in three-hours periods, and they were then used to recalculate wind’s real speed and height at a specific hub. Among the important calculation parameters were Weibull's distribution, average wind speed, annual capacity factor, and the annual energy factor, all of them required for each proposed site. The calculations of the annual capacity and energy factors are necessary for choosing the appropriate wind turbine, generally named Vestas (V60, 850kW). The current study clearly shows that some sites, in particular four locations in Ghayran where feasible annual energy, capacity factor, and acceptable power generation capacity were recorded have wind energy for civilian purposes.

Keywords

shape parameter, scale parameter, annual capacity factor, cumulative Weibull distribution

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