Blade Design, Manufacture, and Testing - Small Wind Turbines: Analysis, Design, and Application - page 129

Table 7.2 Optimisation

Parameter and value Parameter and value

parameters

Population = 2000 Number of blade elements = 15

No. generations = 400 Crossover factor, CR = 0.1

Max. blade age = 20
generations

design as the starting performance will be judged relatively. The limits on blade
chord and twist are to be viewed as typical limits imposed, say, by the manu-
facturing process (Table 7.1 ). Table 7.2 lists the optimisation parameters.
A snippet of an optimisation run is shown below with the output from the data
structure data suppressed

which shows the increase in C p and decrease in T s with generation number.
Figures 7.3 and 7.4 show the evolved chord and twist distributions for Q r = 0
and 0.5 Nm respectively, for the values of a indicated on the figures. Figure 7.3
shows that the results for a = 1 with no tip losses generally follow the distribu-
tions of Eqs. 5.12 and 5.13 . The DE optimisation reproduces the analytical results
for this special case.
The solid and dashed lines are the optimal chord and twist from Eqs. 5.12 and
5.13 as explained in the captions. Reproducing the analytical optimisation in the
limiting case gives confidence that the evolutionary strategy does find the optimal
fitness front in general. There is some scatter in the numerical results, particularly
near the hub for the high values of a, because the hub region contributes little to
the power and, therefore exerts little evolutionary pressure on the developing
design of power-producing blades. As a reduces, and starting becomes more
important, the scatter reduces. Figure 7.3 for Q r = 0 shows some increase in the
chord near the hub, and a more noticeable increase in the twist. The tip region