Revealing the Impact of Climate Variability on the Wind Resource Using Data Mining Techniques (Poster) [electronic resource]

• Ngôn ngữ: eng
• Ký hiệu phân loại: 621.5 Pneumatic, vacuum, low-temperature technologies
• Thông tin xuất bản: Washington, D.C. : Oak Ridge, Tenn. : United States. Dept. of Energy. Office of Energy Efficiency and Renewable Energy ; Distributed by the Office of Scientific and Technical Information, U.S. Dept. of Energy, 2011
• Mô tả vật lý: Size: 1 MB : , digital, PDF file.
• Bộ sưu tập: Metadata
• ID: 259261
• Chủ đề: 1. 17 wind energy; 2. Climates; 3. Mining; 4. Pressure gradients; 5. Resource assessment

Tóm tắt

A data mining technique called 'k-means clustering' can be used to group winds at the NWTC into 4 major clusters. The frequency of some winds in the clusters is correlated with regional pressure gradients and climate indices. The technique could also be applied to wind resource assessment and selecting scenarios for flow modeling.