1-year hourly wind speed data from two Burundian stations, namely
Bujumbura and Muyinga, have been processed in this work to bring an efficient
help for the planning and installation of wind energy conversion systems (WECS)
at those localities. Mean seasonal and diurnal variations of wind direction and
wind shear exponent have been derived. Two-parameter Weibull probability
density functions (PDFs) fitting the observed monthly and annual wind speed
relative frequency distributions have been implemented. As shown through three
complementary statistical tests, the fitting technique was very satisfactory. Awind resourceanalysis at 10 m above
ground level (AGL) has led toa mean
power density at Bujumbura which is almost thirteen fold higher than at
Muyinga. The use of the empirical power law to extrapolate wind characteristics
atheights
from 150 to 350 m AGL has shown that energy potential of hilltops around
Muyinga was only suitable for small, individual scale wind energy applications.
At the opposite, wind energy potential of ridge-tops and hilltops around
Bujumbura has been found suitable for medium and large scale electricity
production. For that locality and at those heights, energy outputs and capacity
factors (CF or Cf) have been computed for ten selected wind turbines
(WTs), together with costs of electricity (COE)
using the present value of cost (PVC)
method. Amongst those WTs, YDF-1500-87 and S95-2.1 MW have emerged as the best
options for installation owing to their highest CFand lowest COE
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