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Their databases by any of various techniques, assemble new generation that will
informative be even better.
In Sect.
1
, FFFV comprises two portions: one of them differentiates generated
rules with optimal worth, thus a rule that shields most of the best values could be
inclination rule.
In a further part; integer similar of rules are being computed on wind turbine
power formula thus these rules calculated on case (1
4) either, accordingly a rule
that minutest slide from nominal value could be good rule.
At the end, for each segment for these parts has been distributed a weight. As a
reaction the best rules have nominated from primary random rules.
In Sect.
2
, SFFV committed the greatest speci
-
c meantime for any rule to
compute the twist angel for the turbine.
10.4 Simulation Result of TFGS
This part includes Simulation result of TFGS. Figure
15
a reveals Tip-Speed Ratio
of wind turbine. Figure
15
b shows the pitch angle response. It is corroborated that
the pitch actuator does not suffer from excessive activity despite the strong tur-
bulence. Figure
15
c shows the evolution of the controlled torque of wind turbine in
Pu that is controlled by TFGS. The turbine is required to operate at its rated power.
Figure
15
d shows the evolution of the output power of wind turbine in Pu that is
controlled by TFGS.
11 Discussion and Comparison on the Presented Methods
By considering the simulation results, it can be concluded that the present models
allow an accurate approximation of the dynamic response of the wind turbine
operating with different winds, although the wind turbines generate the maximum
reactive power. In this chapter it has been tried to control turbine in wind turbulence.
Consequently, output power in any methods has least variations with differences that
have been compared them in this section. In addition proposal methods are com-
pared with other related works. Classical methods based on PI(D) algorithms are a
good starting point for many aspects of closed-loop controller design for variable-
speed turbines. Control design is a task that demands rigorous test data and extensive
engineering judgment. The presented approach in Endusa and Aki (
2009
) has been
employed to model the WECS subsystems as a basis for multi objective controller
design. Model validation is carried out to authenticate the results. Produced power
and generator torque from this strategy is shown in the Fig.
16
b. A PID controller
based on the BP neural network has been offered and used in the variable pitch angle
wind turbine control system in Xing et al. (
2009
). Figure
16
c, indicates output power
of this strategy. The System response has sudden change, and hence is sensitive to
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