Simulation of Variable Speed Induction Machine Wind Generation System Using Fuzzy Logic Controller (FLC)

International Journal of Scientific Research and Engineering Development-– Volume 2 Issue 6, Nov-Dec 2019
Available at www.ijsred.com
ISSN : 2581-7175 ©IJSRED: All Rights are Reserved Page 427
Simulation of Variable Speed Induction Machine Wind Generation
System Using Fuzzy Logic Controller (FLC)
Kommalapudi Srihari1
, C.Dinakaran2
1
UG Student, Department of Electrical and Electronics Engineering, Audisankara College of Engineering & Technology,
Gudur, A.P, India
2
Assistant Professor, Department of Electrical and Electronics Engineering, Audisankara College of Engineering &
Technology, Gudur, A.P, India
Email: dina4karan@gmail.com
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Abstract:
The worldwide electrical power utilization is increasing moreover there is stable enlarge of the
demand on energy generation. The presented conservative power sources are depleting. The substitute
power source reserves are appropriate further significant at the present day. Wind electrical production
systems are newly receiving lot of concentration, for the reason that they are the majority charge spirited,
ecological clean as well as secure renewable energy source. Artificial intelligence system such as fuzzy
logic, neural networks as well as genetic algorithms are recently performance a lot of assure in the
function of power electronic systems. The most important intention of this paper is to propose with
analyse the routine of a model 5KW unpredictable speed wind generation arrangement with fuzzy logic
controllers used for optimizing effectiveness furthermore improve the routine of the method. The
production system uses three Fuzzy Logic Controllers FLC-1, FLC-2 as well as FLC-3. The FLC-1 tracks
the generator speed through the wind velocity in the direction of extort utmost power identified as
producer speed tracking regulator. The FLC-2 programs engine flux for illumination load effectiveness
development known as Generator flux programming controller. The FLC-3 provides vigorous speed
control against wind current with turbine oscillatory torque recognized as closed loop generator speed
regulator. The fuzzy logic based control of the arrangement helps to optimize effectiveness as well as
improve performance of the arrangement is demonstrated by simulation via MATLAB/SIMULINK.
Keywords — Fuzzy Logic Control, Variable Speed Squirrel Cage Induction Machine, Wind Generator,
MATLAB 8.2 Software.
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I. INTRODUCTION
Electrical power utilization is increasing day by
day furthermore there is stable augment of the
demand on energy generation. The obtainable
conservative energy sources are diminishing [1].
Consequently substitute power source reserves are
fetching further significant at the present days [2].
Wind power generation systems are recently
receiving assortment of concentration, since they
are the majority charge aggressive, ecological
spotless with secure renewable energy source,
because compared to fossil fuel moreover nuclear
energy generation [3]. The exhaustion assets, raise
in insist moreover definite factors in globe policy
comprise collectively contributed to a quick rise in
the charge of conventional energy generation [4].
A lot of places as well accomplish not contain
the potential for generating hydro power. Nuclear
energy generation is previously treated by means of
immense optimism, however by the acquaintance of
RESEARCH ARTICLE OPEN ACCESS

the ecological hazards related through the
achievable outflow from nuclear power plants, the
majority countries comprise resolute not to
establish them to any further extent [5]. The
increasing attentiveness of these troubles leads to
discriminating investigate efforts meant for
increasing unconventional sources of power for
generation of electrical energy [6]. The majority
attractive resource would be individual so as to be
non pollutant presented in plenty with renewable as
well as be able to be harness on a tolerable price in
mutually huge level along with miniature extent
system [7]. The majority capable source agreeable
all these necessities is wind [8].
II. POWER FROM THE WIND
Kinetic power commencing the wind is used to
turn the generator within the wind turbine toward
generates electrical energy. There are a number of
factors with the aim of supply to the effectiveness
of the wind turbine in extract the power
commencing the wind. Initially, the wind speed is
individual of the significant factor in decisive how
greatly power is able to be extract commencing the
wind. This is for the reason that the energy
generated from the wind turbine is a purpose of the
cube of the wind speed. Therefore, the wind speed
if double the energy produced will be improved by
eight times the innovative power. Subsequently,
locality of the wind farm plays a vital role in
arrange for the wind turbine to take out the majority
available energy form the wind.
The subsequently significant aspect of the wind
turbine is the rotor blade. The rotor blades span of
the wind turbine is one of the essential aspects of
the wind turbine while the energy generated
commencing the wind is too relative to the swept
area of the rotor blades i.e. the square of the
diameter of the swept area.
Because the blade span increases these character
of the rotor blades develop into supplementary
elusive. Although in the midst of the current
advances in fibre glass along with carbon fibre skill.
The creation of lightweight with strong rotor blades
among 20 to 30 meters extensive is achievable.
Wind turbines through the dimension of these rotor
blades are able to generate up to 1 MW of power.
III. INDUCTION GENERATOR FOR WIND
GENERATION SYSTEM
Induction generator is normally used into the
wind turbine electric power generation suitable to
its condensed unit charge, brushless rotor creation,
ruggedness moreover simplicity of preservation.
Furthermore, induction generators contain a number
of uniqueness in excess of the synchronous
generator. The speed of the asynchronous generator
resolve fluctuates according to the rotating force
functional to it.
A functional mechanical belonging of the
generator is to facilitate it resolve amplify or
diminish its speed to some extent if the torque
varies also consequently will be less destroy as well
as carry on the gearbox within the system. This is
one of the significant reasons to employ
asynchronous generator compared to a synchronous
generator taking place a wind turbine.
An Induction generator is a kind of electrical
power generator with the intention of mechanically
as well as electrically related to a polyphase
induction motor. Induction generators create
electrical power while their shaft is rotated quicker
than the synchronous frequency of the comparable
induction motor.
Induction generators are frequently used in
wind turbines furthermore in a few micro hydro
installations suitable to their capability to generate
practical power at unstable rotor speeds. Induction
generators are mechanically as well as electrically
simpler than additional generator types. They are
also more rugged, requiring no brushes or
commutators.
IV. FUZZT LOGIC
Fuzzy logic is a structure of multi valued logic
derivative commencing fuzzy set theory to
arrangement with interpretation with the intention of
estimated relatively than precise. In dissimilarity
with "crisp logic", wherever binary sets contain
binary logic, fuzzy logic variables could encompass
a truth value that ranges between 0 and 1 and is not
controlled to the two truth values of typical
propositional logic. Moreover, when linguistic

variables are used these degrees might be managed
by definite functions. Fuzzy logic emerges as a
significance of the 1965 application of fuzzy set
theory by Lotfi Zadeh. However fuzzy logic have
been functional to many fields, beginning control
theory to artificial intelligence it still residue
contentious between the majority statisticians, who
prefer Bayesian logic along with some control
engineers have a preference conventional two valued
logic.
V. CONVERTER SYSTEM
A vertical wind turbine is attached to the shaft
of a squirrel cage induction generator during a
speedup gear ratio. The variable frequency variable
voltage power commencing the generator is
rectified by a Pulse Width Modulation insulated
gate bipolar transistor rectifier.
Fig. 1 Voltage fed converter system
The rectifier as well supplies the excitation
necessitate of the machine. The inverter topology is
the same to that of the rectifier with it equipment
the generated power at 60 Hz to the utility grid as
illustrated in figure 1.
It appears to facilitate fuzzy logic based
intellectual control is the majority for performance
development of wind generation systems. The
machine as well as inverter output currents are
sinusoidal. The machine absorbs lagging reactive
current except it is constantly zero on the line side
i.e., the line power factor is unity.
The rectifier uses indirect vector control during
the inner current control loop, while the direct
vector control method is used in favour of the
inverter current controller. Vector control permits
rapid transient response of the system. For a
exacting wind velocity, there resolve be an
optimum setting of generator speed. The speed loop
will produce the torque constituent of machine
current so as to equilibrium the developed torque
through the load torque.
The variable voltage and variable frequency
power from the tremendous synchronous induction
generator will be rectified along with pumped to the
DC link. The DC link voltage controller resolve
regulate the line power consequently to facilitate
the relation voltage constantly remains constant. A
feed forward energy signal commencing the
machine output to the DC voltage loop prevents
transient oscillation of link voltage. Obviously the
system is able to be adequately controlled for start
up with regenerative braking in power cut modes
moreover the natural generating model of process.
VI. FUZZY LOGIC CONTROLLERS IN WIND
GENERATION SYSTEM
Figure 2 illustrates a block diagram of the
power circuit as well as the fuzzy logic based
control of the wind generation system. The wind
turbine is attached to the squirrel cage type
induction generator through a speed up gear box.
Fig.2 Fuzzy logic controllers in wind generation system
The variable frequency and variable voltage
power generated through the machine is rectified to

direct current by an Insulated Gate Bipolar
Transistor Pulse Width Modulation bridge rectifier
to facilitate supplies lagging excitation current to
the machine. The DC link power is inverted to
60Hz, 220V alternating current through an
Insulated Gate Bipolar Transistor Pulse Width
Modulation inverter in addition to fed a utility grid.
Together the line as well as machine currents are
sinusoidal as represented in output waveforms. The
line side power factor is maintained at unity while it
can be programmed to be leading or lagging. The
generated power usually flows commencing the
machine to the line. Though, energy can also flow
in the opposite direction meant for the start up of a
vertical turbine. Because the speed of the
mechanism builds up it goes into a generating mode.
The machine is shut down by regenerative
braking. The generator speed is controlled by
indirect vector control with torque control as well
as synchronous current control in the inner loops.
The machine flux is controlled in open loop by
control of ids current. However in standard
condition the rotor flux is set to the rated value for
fast transient response. The line side converter is
moreover vector controlled with direct vector
control as well as synchronous current control in
the inner loops. Output power is controlled to
regulate the DC link voltage. Because an increase
of output power decreases the link voltage, the loop
error polarities have been inverted. The regulation
of Vd contained by a little tolerance band requires a
feed forward energy injection in the power loop as
indicated. The system uses three fuzzy controllers
are FLC-1, FLC- 2 as well as FLC-3.
VII. SIMULATION RESULTS & DISCUSSION
The proposed system has been tested along with
simulation results are exposed from figure 3 to
figure 20. This representation has been
implemented with MATLAB / SIMULINK
environment with SIMPOWER system toolbox.
A. SIMULINK MODEL OF WGS WITHOUT FUZZY
LOGIC CONTROLLERS
Fig. 3 SIMULINK model of WGS without fuzzy logic controllers
Fig. 4 Wind velocity (PU) – time (Sec)
Fig. 5 Generator speed (PU) – time (Sec)
Fig. 6 Flux current (PU) – time (Sec)

Fig. 7 Gating Pulses for Converter-1
Fig. 8 Gating Pulses for Converter-2
Fig. 9 Output power (PU) – time (Sec)
B. SIMULINK MODEL OF WGS WITH FUZZY LOGIC
CONTROLLERS
Fig. 10 SIMULINK model of WGS with fuzzy logic controllers
Fig. 11 Study system to generate Tref
Fig. 12 Study system to generate idsref1
Fig. 13 Study system to generate pulse 1
Fig. 14 Wind velocity (PU) – time (Sec)

Fig. 15 Generator speed (PU) – time (Sec)
Fig. 16 Flux current (PU) – time (Sec)
Fig. 17 Gating pulses for converter-1
Fig. 18 Gating pulses for converter-2
Fig. 19 Output power (pu) – time (sec)
Fig. 20 Fuzzy Output FLC-1, FLC-2, FLC-3
VIII. CONCLUSION
A model of fuzzy logic based 5KW variable
speed wind power generation system have been
designed along with performance have been
considered through MATLAB simulation. The
wind energy generation system uses three fuzzy
logic controllers FLC-1, FLC-2 moreover FLC-3.
The majority promising applications are those
wherever conventional control systems cannot
supply adequate performance, normally while the
representation of the generating plant is not
obtainable or extremely non-linear. While the
method is issue to important constraint variation.
Fuzzy Logic Controller constitutes a controlling
tool to convert creature practiced information
addicted to automatic control strategy.
The FLC-1 tracks the generator speed through
the wind velocity to extract maximum power
recognized as Generator speed tracking controller.
The FLC-2 programs machine flux for light load
effectiveness enhancement recognized as Generator
flux programming controller. The FLC-3 provides
robust speed control adjacent to wind vortex and

turbine oscillatory torque recognized as closed loop
generator speed controller.
REFERENCES
[1] K. Kaur, Dr.S.Chowdhury, Dr.S.P.Chowdhury, Dr. K.B.Mohanty,
Prof.A.Domijan,”Fuzzy logic based control of variable speed induction
machine wind generation system” IEEE transactions on Industry
Applications,(2008) pp 1-11.
[2] Bose, B.K. Modern power electronics and A.C drives .Upper saddle
river: Pearson Education, 2002.
[3] Simoes, M. G., Bose, B. K., Spiegel, R.J. “Design and performance
evaluation of fuzzy logic based variable speed wind generation
system”, IEEE Transactions on Industry Applications. Vol. 33, No. 4,
(July/august 1997), pp. 956-965.
[4] Bose, B. K., Simoes , M . G. “Project Summary – Fuzzy logic based
intelligent control of variable speed cage wind generation system”.
United States environmental Protection Agency, (March 1997): pp. 1-6.
[5] Zhao, Jin. , Bose, B.K. “Evaluation of membership functions for fuzzy
logic controlled induction motor drive”, IEEE Transactions on Power
Electronics, (2002), pp. 229-234.
[6] Zhao, Jin, Bose, B.K. “Membership function distribution effect on
fuzzy logic controlled induction motor drive”, IEEE Transactions on
Power Electronics, (2003), pp. 214-219.
[7] C.Dinakaran, “Temperature and Water Level Control in Boiler by using
Fuzzy Logic Controller,” International Journal of Electrical Power
System and Technology, Vol. 1, Issue 1, October 2015, PP. 27-37.
[8] C.Dinakaran, “Evaluation of Fault Diagnostic System for a Multistring
Multilevel Inverter using an Artificial Neural Network,” International
Electrical Engineering Journal, Vol. 6, No. 4, May 2015, PP. 1850-
1855.

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