This paper provides a case study on application of wavelet techniques
to analyze wind speed and energy (renewable and environmental friendly
energy). Solar and wind are main sources of energy that allows farmers to have
the potential for transferring kinetic energy captured by the wind mill for
pumping water, drying crops, heating systems of green houses, rural
electrification’s or cooking. Larger wind turbines (over 1 MW) can pump
enough water for small–scale irrigation. This study tried to initiate data
gathering process for wavelet analyses, different scale effects and their role on
wind speed and direction variations. The wind data gathering system is mounted
at latitudes: 37º 50″ N; longitude 30º 33″ E and height: 1200 m above mean sea
level at a hill near Süleyman Demirel University campus. 10 minutes average
values of two levels wind speed and direction (10m and 30m above ground
level) have been recorded by a data logger between July 2001 and February
2002. Wind speed values changed between the range of 0 m/s and 54 m/s.
Annual mean speed value is 4.5 m/s at 10 m ground level. Prevalent wind
direction is south west. Artificial Neural Network analyses are also applied to
predict wind speed values in winter and spring.
Other ID | JA79RR88NR |
---|---|
Journal Section | Articles |
Authors | |
Publication Date | September 1, 2010 |
Submission Date | September 1, 2010 |
Published in Issue | Year 2010 Volume: 2 Issue: 7 |