United States
Environmental Protection
Agency
National Risk Management
Research Laboratory
Research Triangle Park, NC 27711
Research and Development
EPA/600/SR-97/010
March 1997
SEPA Project Summary
Fuzzy Logic Based Intelligent
Control of a Variable Speed
Cage Machine Wind Generation
System
Bimal K. Bose and Marcelo G. Simoes
This report gives results of a demon-
stration of the successful application
of fuzzy logic to enhance the perfor-
mance and control of a variable speed
wind generation system. A squirrel cage
induction generator feeds the power to
a double-sided pulse width modulation
converter system which pumps power
to either a utility grid or an autono-
mous system. Maximum power point
tracker control is performed with three
fuzzy controllers, without wind velocity
measurement. A fuzzy logic controller
(FLC-1) searches the generator speed
on-line to optimize the aerodynamic ef-
ficiency of the wind turbine. A second
fuzzy controller (FLC-2) programs the
machine flux by on-line search so as
to optimize the machine-converter sys-
tem efficiency. A third fuzzy controller
(FLC-3) performs robust speed control
against turbine oscillatory torque and
wind vortex.
Detailed analysis and simulation
studies were performed for develop-
ment of the control strategy and fuzzy
algorithms, and DSP TMS320C30 based
hardware with C control software was
built for the performance evaluation of
a laboratory experimental setup. The
theoretical development was fully vali-
dated, and the system is ready to be
reproduced in a higher power installa-
tion.
This Project Summary was developed
by EPA's National Risk Management
Research Laboratory's Air Pollution
Prevention and Control Division, Re-
search Triangle Park, NC, to announce
key findings of the research project
that is fully documented in a separate
report of the same title (see Project
Report ordering information at back).
Introduction
The report describes work performed
by the University of Tennessee on fuzzy
logic based control of a variable speed
wind generation system. The purpose of
this research and development was to op-
timize efficiency and enhance performance
for a variable speed wind turbine electri-
cal generation system by using fuzzy logic
principles. The project involved power sys-
tem topology selection, control strategy
formulation, system analysis, performance
study by simulation, converter system de-
sign, control hardware and software de-
velopment for digital signal processors,
and experimental study in the laboratory
with a 3.5 kW generation system to dem-
onstrate performance. In general, all sys-
tem performance goals have been suc-
cessfully demonstrated. The control, with
a small change, can be easily applied to a
larger wind generation system in the field.
System Description
Figure 1 is a block diagram of the power
circuit and the fuzzy logic based control of
the wind generation system. The wind tur-
bine is coupled to the squirrel cage type
induction generator through a speed-up
gear box (not shown). The variable fre-
quency variable voltage power generated
by the machine is rectified to direct cur-
rent (dc) by an IGBT PWM bridge rectifier
that also supplies lagging excitation cur-
rent to the machine. The dc link power is
inverted to 60 Hz, 220 V alternating cur-
rent (ac) through an IGBT PWM inverter
and fed to a utility grid. Both the line and
machine currents are sinusoidal, as shown.
The line-side power factor is maintained
at unity although it can be programmed to
be leading or lagging. The generated
power normally flows from the machine to
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Synchronous current
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Figure 1. Fuzzy logic based control block diagram of wind generation system
the line. However, power can also flow in
the opposite direction for the start-up of a
vertical turbine. As the speed of the ma-
chine builds up, it goes into a generating
mode. The machine is shut down by re-
generative braking. The generator speed
is controlled by indirect vector control with
torque control and synchronous current
control in the inner loops. The machine
flux is controlled in open loop by control of
ids current, but in normal condition, the
rotor flux is set to the rated value for fast
transient response. The line-side converter
is also vector-controlled using direct vec-
tor control and synchronous current con-
trol in the inner loops. Output power is
controlled to regulate the dc link voltage.
Since an increase of output power de-
creases the link voltage, the loop error
polarity has been inverted. The tight regu-
lation of Vd within a small tolerance band
requires a feed forward power injection in
the power loop, as indicated. The system
uses three fuzzy controllers ( FLC-1, FLC-
2 and FLC-3).
Neglecting losses, the line power out-
put of the system as a function of genera-
tor speed at different wind velocity is ex-
plained in Figure 2. For a certain wind
velocity, if generator speed is increased,
output power first increases, reaches a
maximum value, and then decreases. If
the wind velocity increases, the maximum
power point also increases and shifts to
the right side, as shown. It is desirable
that, for any wind velocity, the system
should always operate at the maximum
power point where the turbine aerodynamic
efficiency is maximum. Since wind veloc-
ity is an unknown parameter, the speed of
the generator can be modified by on-line
search until the maximum power point is
attained.
Three Controllers
The function of fuzzy controller FLC-1,
shown in Figure 1, is to search the gen-
erator speed until the system settles down
at the maximum output power condition.
If, for example, wind velocity is Vw4, output
power will be at point A for generator
speed wr1. The output power can be raised
to the maximum value at B by increasing
the speed to wr2. If wind velocity now
increases to Vw2, the power output jumps
to point D. However, at this wind velocity,
the maximum power can be obtained by
increasing generator speed further to wr4.
This means that as wind velocity changes,
generator speed has to track it in order to
extract maximum power. This control func-
tion is done by fuzzy controller FLC-1.
The details of the control are described in
the full report. Fuzzy control has several
advantages: the control algorithm is uni-
versal (the same algorithm can be applied
to any similar system), control converges
fast because of the adaptively decreasing
step size in the search, and the system
can tolerate noisy and inaccurate signals.
Note that it does not need wind velocity
information, and the system parameter
variation does not affect the search.
The light load efficiency of the genera-
tor-converter system is optimized on the
basis of on-line search of the machine
rotor flux, and is implemented here by
fuzzy controller FLC-2. At a certain steady
state wind velocity and at the correspond-
ing optimum speed established by con-
troller FLC-1 (see Figure 1), the rated
rotor flux is reduced by decreasing excita-
tion current ids. This causes an increase of
the torque component of current by the
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que
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550 RPfr
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Wind velocity (m/sec)
Figure 3. Wnd turbine static characteristics, (a) turbine power, (b) turbine torque, and (c) line power.
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Generator Speed - 940 RPM
Efficiency improvement
due to FL(j-1
0.7 0.8
Wind velocity (pu)
Figure 4. Efficiency improvement by controllers FLC-1 and FLC-2 at different wind velocities (1.0 pu - 31.5 mph)
Figure 5. Line-side voltage and current waves showing unity power factor operation
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Bimal K. Bose and Marcelo G. Simoes are with the University of Tennessee,
Knoxville, TN 37996.
Ronald J. Spiegel is the EPA Project Officer (see below).
The complete report, entitled "Fuzzy Logic Based Intelligent Control of a Variable
Speed Cage Machine Wind Generation System," (Order No. PB97-144851; Cost:
$35.00, subject to change) will be available only from:
National Technical Information Service
5285 Port Royal Road
Springfield, VA 22161
Telephone: 703-487-4650
The EPA Project Officer can be contacted at:
Air Pollution Prevention and Control Division
National Risk Management Research Laboratory
U.S. Environmental Protection Agency
Research Triangle Park, NC 27711
United States
Environmental Protection Agency
Center for Environmental Research Information
Cincinnati, OH 45268
Official Business
Penalty for Private Use $300
BULK RATE
POSTAGE & FEES PAID
EPA
PERMIT NO. G-35
EPA/600/SR-97/010
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