Determination of the Surface Roughness Parameter and Wind Shear Exponent of Kisii Region from the On-Site Measurement of Wind Profiles

Abstract

The research sought to investigate the surface roughness parameter (Zo) and wind shear exponent (α) of Kisii region (elevation 1710m above sea level, 0.68°S, 34.79°E). A six-month experiment was set at three sites of Kisii region. Two PRO AcuRite 01036 Wireless Weather Stations with pro+ 5-in-1 Sensors were placed at different hub heights above the ground and data were sent and received by a display board set at a room through remote sensing at an interval of 12 minutes. Data was collected from the display board through the pc connect software, grouped into discrete data and then calculated to represent mean wind speed, diurnal variation, daily variation, and monthly variations. The calculated averages of wind speeds at hub heights of 10m and 13m were then used to determine the wind shear exponent and surface roughness parameter of the sites. The wind shear exponents were found to be 0.92, 0.41, and 0.54 for Nyamecheo, Kisii University, and Ikobe stations, respectively, with an average of 0.64. The roughness parameter was also calculated and found to be 3.75, 1.32, and 1.96 for Nyamecheo, Kisii University (KSU), and Ikobe, respectively, with an average of 2.35.

Evaluation of the Technical Wind Energy Potential of Kisii Region Based on the Weibull and Rayleigh Distribution Models

“…Kisii University being higher in altitude than Ikobe and Nyamecheo in that order exhibited higher wind speeds. This is backed with the values of the wind shear exponent obtained during this study [25]. The higher value of wind shear meant higher picking of wind speed from one hub height to another.…”

“…By use of the PC connect software, data received and stored by the display boards were transferred to the computer for analysis. The data collected was used to determine the wind shear exponents and surface roughness parameters of the sites [25]. The data was also used to audit the data collected from the Kenya meteorological department.…”

“…It all depends on the topography, terrain, surface cover, and temperature stratification of the region under study. 11 Journal of Energy In extrapolating wind power to higher hub heights, knowledge of wind shear exponent and surface roughness parameter is mandatory [25]. According to [37], wind power can be classified into seven classes depending on the height and wind speeds [39].…”

“…To establish the wind potential of any locality, modelling of the wind behaviour is mandatory. In modelling, the wind shear exponent and surface roughness parameters should be determined [25]. This is because they play a big role in determining how wind power picks from one height to another and in determining wind power at other higher heights above the experimental ones.…”

Comprehensive Review of Wind Energy in Malaysia: Past, Present, and Future Research Trends

“…A comprehensive onshore or offshore wind resource mapping is necessary to assess wind feasibility, especially for Malaysia since it has a low wind profile. It is well known that wind speed varies depending on the terrain conditions, such as temperature, wind direction, height from the ground, surface roughness, day time, and year seasons [127]. Wind resource geographical maps can be generated using either spatial prediction or altimetry wind data for those unobserved or uncovered by MMD stations locations.…”