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Multilevel Control of Variable Speed Wind Turbine
Generator and MPPT using Fuzzy Logic Controller
Prathibha P K
Asst.Professor
Dept.of Electrical
Rajagiri School of Engg&Technology
[email protected]
V.P.Mini
Asst.Professor
Dept.of Electrical
College of Engg Trivandrum
[email protected]
Abstract— In this paper a full detailed modeling and a new
control scheme of a three phase grid connected wind energy
conversion system (WECS) is described. This WECS uses a
Permanent magnet synchronous generator and the power
conditioning system is composed of a back-back (AC-DC-AC)
power converter. The multi level control system is used for
identifying and extracting the maximum power from the wind
energy system and transferring this power to utility. In addition,
reactive power compensation of electric grid is included,
operating simultaneously and independently of the active power
generation. The phase angle of utility voltage is detected using
PLL (Phased Locked Loop) in d-q synchronous reference frame.
A three level voltage source inverter is used as interface with the
AC power grid. The maximum power point tracking (MPPT) is
done with fuzzy controller and it is compared with the results of
conventional controller. Simulation of models and control
schemes is performed in the MATLAB /Simulink environment.
Key Words— Control techniques, DC-DC converter,
Maximum Power Point Tracking (MPPT), Permanent magnet
synchronous generator (PMSG), PWM multi-level inverter,
Wind energy conversion systems (WECS), Fuzzy logic
controller, Membership functions.
I. INTRODUCTION
Major Renewable Energy Sources (RES) are today
economically viable alternatives to conventional electric
power generation. Among the various factors contributing to
this success are the development of new power electronic
technologies, new circuit topologies and control strategies [1].
Presently, grid integration of Wind Energy Conversion
Systems (WECS) is becoming the most important and fastest
form of electricity generation among renewable energies. This
trend is sustained by the cost competitiveness of WECS
technology, and is being increased because of the many
benefits of using RES in distributed (or dispersed) generation
(DG) power systems [2].
Differential heating of the earth's surface by the sun causes
the movement of large air masses on the surface of the earth,
i.e., the wind. Wind energy conversion systems convert the
kinetic energy of the wind into electricity or other forms of
energy. Wind power generation has experienced a tremendous
Prof. K.Rajendra Varmah
Head of the Department
Dept.of Electrical
Rajagiri School of Engg&Technology
[email protected]
growth in the past decade, and has been recognized as an
environmentally friendly and economically
competitive means of electric power generation [3].
The output voltage of a permanent magnet generator is
connected to a fixed DC-link through a three-phase rectifier
and a step-up DC-DC converter, which permits the
implementation of the Maximum Power Point Tracking. A
PWM multi-level voltage source inverter (VSI) is used to
convert the energy produced by wind turbines into useful
electricity and to provide requirements for power grid
interconnection. A buck-boost converter is proposed for dc-dc
chopper and the output current reference of the chopper is
decided for the maximum power point tracking of wind
turbine. But the voltage stress of chopper switch is greater than
that of boost converter. Also the leakage inductance of
generator and cable cannot be used as an equivalent dc
inductor [1] [3].
. In this paper, a simple ac-dc-ac converter is used and a
modular control strategy for grid-connected wind power
generation system is proposed. Line side inverter maintains
constant dc-link voltage and maximum power factor with the
help of a three level controller. Input current reference of boost
chopper is decided for the maximum power point tracking of
the turbine without any information of wind speed or generator
rpm. As the proposed control algorithm does not require any
speed sensor for wind speed or generator rpm, construction
and installation are simple, cheap, and reliable.
II. WIND ENERGY CONVERSION SYSTEM (WECS)
The selected wind generator employs a permanent magnet
synchronous generator directly coupled to the wind turbine
and connected to the electric grid through a power
conditioning system (PCS). The stator windings of the PMSG
are straightforwardly connected to the PCS composed of a
three-phase rectifier bridge, a DC-DC converter and a DC-AC
switching power inverter, as shown in Fig. 1.
Fig 1. Block diagram of WECS
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A. Wind Turbine
The amount of power harnessed from the wind of velocity
is as follows,
Pm  1/ 2 AC pV
3
v
-------------------------- (1)
  Air density (kg/m3)
C p  Power co-efficient of wind turbine
V  Wind speed (m/s)
A  Swept area ( m 2 )
Consequently, the output energy is determined by the power
coefficient of wind turbine if the swept area, air density, and
wind velocity is constant. The power coefficient depends on
the aerodynamic characteristics of blades.
As can be derived from Eqn. 1, the power coefficient Cp is a
nonlinear function of the blade pitch angle  (in degrees) and
the tip-speed ratio

In this work, a typical small-sized three-bladed horizontalaxis wind turbine generator with no blade pitch angle control
is considered, so that  =0º at all times.
B. Permanent magnet synchronous generator (PMSG)
This section presents the detailed modeling of the wind
turbine generator. The selected wind generator employs a
permanent magnet synchronous generator directly coupled to
the wind turbine and the machine parameters are given in the
Appendix. The generator itself has two electromagnetic
components: the rotating magnetic field constructed using
permanent magnets; and the stationary armature constructed
using electrical windings located in a slotted iron core.
In this work a 400W synchronous generator is used and the
equations governing the modeling are;
Lq
d
1
R
id 
vd  id 
pr iq        (4)
dt
Ld
Ld
Ld
(dimensionless).
Ld
d
1
R
pr

 16.5 
1  98
i

v

i

p

i

   (5)
q
q
q
r
d
C p   ,      0.4  5  exp 




(2)

dt
L
L
L
L
2  i

q
q
q
q

 i 
1
Te  1.5 p[iq  ( L d  Lq )id iq          (6)

1
0.035 

i  
 3
III. POWER CONDITIONING SYSTEM (PCS)
   0.089    1  ------------- (3)
The characteristic function Cp vs.  , for various values of
the pitch angle  , is shown in Fig. 2. The maximum value of
Cp and  opt is achieved for  =0º. These values results in
the point of optimal efficiency where the wind turbine captures
the maximum power [4].
Fig 2. Cp vs  for various pitch angles  .
It can be observed that, for each wind speed, there exists a
specific point in the wind generator power characteristic,
maximum power point (MPP), where the output power is
maximized. Thus, the control of the WECS load results in a
variable-speed operation of the turbine rotor, such that the
maximum power is extracted continuously from the wind
(maximum power point tracking control or MPPT).
The PCS used for this work is composed of a back-to-back
AC-DC-AC power converter that fulfills all the requirements
of a utility grid. Since the permanent magnet synchronous
generator produces an output voltage with variable amplitude
and frequency, additional conditioning is required to meet the
amplitude and frequency requirements of the utility grid. A
three-phase uncontrolled full-wave bridge rectifier is used here
for performing the AC-DC conversion and a three-phase threelevel DC-AC voltage source inverter using IGBTs is employed
for connecting to the grid[8]. For wide range of variable speed
operation, a dc-dc boost chopper is utilized between 3-phase
diode rectifier and IGBT inverter. The input dc current is
regulated using boost-up chopper to follow the optimized
current reference for maximum power point operation of
turbine system.
1) DC-DC Converter
The standard unidirectional topology of the DC-DC boost
converter or chopper in Fig. 5.a consist of a switching-mode
power device containing basically two semiconductor switches
(a rectifier diode and a power transistor with its corresponding
anti-parallel diode) and two energy storage devices (an
inductor and a smoothing capacitor) for producing an output
DC voltage at a level greater than its input DC voltage. This
converter acts as an interface between the full-wave rectifier
bridge and the Voltage Source Inverter, by employing pulsewidth modulation (PWM) control techniques.
In the Boost-up chopper , the voltage equation in continuous
current mode is given by eqns. (7) and (8).
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Ldc
I dc
dI dc
 Vin  Vs  Vin  (1  D)Vdc    (7)
dt
1

(Vin  (1  D)Vdc )dt        (8)
Ldc 
2) Voltage source inverter
The three-phase three-level voltage source inverter
proposed corresponds to a DC-AC switching power inverter
using IGBTs operated through sinusoidal PWM [9]. As the
high-frequency harmonics produced by the inverter as result of
the PWM control techniques employed are mostly filtered by
the sinusoidal line filter, the VSI can be seen as an ideal
sinusoidal voltage source, which is depicted in Fig.3. This
ideal inverter is shunt-connected to the network through an
inductance Ls, accounting for the equivalent leakage of the
step-up coupling transformer and a series resistance Rs,
representing the transformers winding resistance and VSI
semiconductors conduction losses. The magnetizing
inductance of the step-up transformer can also be taken into
consideration through a mutual equivalent inductance M.
Fig 3. Equivalent circuit diagram of the grid-connected VSI.
IV. MULTI LEVEL CONTROL STRATEGY
The three level control scheme for the three-phase gridconnected wind energy conversion system is depicted in Fig.
4. This three-level control consists of external, middle and
internal level, with different hierarchies between them. The
control approach is based on concepts of instantaneous power
on the synchronous-rotating dq reference frame. Rotating
reference frame is used because it offers higher accuracy than
stationary frame-based techniques.
Fig 4. Multi-level control scheme for the proposed three-phase
grid-connected WECS.[3-4]
1. External Level Control
The external level control (left side of Fig. 4) is responsible
for determining the active and reactive power exchange
between the WECS system and the utility grid. The external
level control scheme is designed for performing
simultaneously two major control objectives, that is the active
power control mode (APCM) and the voltage control mode
(VCM).
The generated output power signal Pr is then converted to a
direct current reference (idr1) for the middle level control
dividing Pr by the magnitude of the voltage vector at the point
of common coupling (PCC) of the inverter (vd1). This value is
computed by using Park’s transformation in such a way that
the instantaneous values of the three-phase AC bus voltages
are transformed into dq components, vd and vq respectively
and then filtered in order to obtain fundamental values.
2. Middle Level Control
The middle level control makes the expected output to
dynamically track the reference values set by the external level
(middle side of Fig. 4). In order to achieve a decoupled active
and reactive power control, it is simply required to decouple
the control of id and iq. Thus, by generating the appropriate
control signals x1 and x2, derived from setting to zero
derivatives of currents in the upper part (ac side) of Eq. 9, the
middle level control algorithms are obtained.
3. Internal Level Control
The internal level (right side of Fig. 4) is responsible for
generating the switching signals for the twelve valves of the
three-level VSI, according to the control mode (sinusoidal
PWM) and types of valves (IGBTs) used. This level is mainly
composed of a line synchronization module, a three-phase
three-level SPWM firing pulses generator for the VSI and a
PWM generator for the IGBT of the boost DC-DC converter.
The line synchronization module consists mainly of a phase
locked loop (PLL).
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V. FUZZY LOGIC CONTROLLER FOR MPPT
Recently the concept of fuzzy logic control (FLC) has been
employed in many industrial applications. The block
diagram of the controlled wind energy system with Fuzzy
Logic Controller is shown in Fig.5. It consists of the Wind
Energy System (WES) block, the Fuzzy Logic tracking
Controller (FLC) and the asynchronous link which couple
the two systems (Wind energy system and the grid utility).
Fig. 5 Block diagram of the WES with Fuzzy logic
controller
The inputs to the FLC are: the error signal (E), indicating
the difference between the Pmax and Pout and the derivative
of this error signal (CE). The output of the FLC is the
control signal (CU), indicating the change of the firing angle
of the inverter. These are given by;
Er  Ger [ Pmax (k  1)  Pout (k )]        (9)
CE  Gce [ Pmax (k )  Pout (k  1)]        (10)
Standard triangular membership functions, as
shown in Fig.6, are chosen for both the inputs and
output of the fuzzy logic controller.
Where ZE- Zero, SP- Small positive, MPMedium Positive, LP- Large Positive.
VI.SIMULATIONS AND RESULTS
In order to investigate the effectiveness of the proposed
models and control algorithms of the three-phase gridconnected WECS, time-discrete dynamic simulations were
implemented using SimPowerSystems of MATLAB/Simulink
environment. The wind speed varies in steps every 1 sec as
described in the figure 7, producing proportional changes in
the maximum power drawn from the WECS with a settling
time of almost 0.4 s. Fig .7 shows power Vs rotor speed at
various wind speeds and the Perturbation &Observation
method proves to be accurate in following the MPP of the
WECS, for an optimum duty cycle perturbation step in
accordance with the chopper dynamics. Fig .8 shows power
co-efficient (Cp) Vs tip speed ratio (  ) for various pitch
angles. The maximum value of Cp, that is Cpmax=0.47, is
achieved for  =0º and for  =6.75.
Fig. 9 shows the Gate pulse to the VSI obtained from the
multi level controller. Fig .10 shows the WTG output power
with P&O control method and a maximum WTG output power
of 280W is obtained. Simulations depicted in Fig. 11 shows
the case with only active power exchange with the utility grid,
i.e. with APCM activated, for a typical 400W three-bladed
horizontal-axis WTG connected to a 400 V electric system.
Fig 12 is the case with active and reactive power exchange
with the utility grid, i.e. the APCM is activated all the time
while the VCM is activated at t=0.4 s.
As can be observed, all the active power generated by the
WTG is injected into the electric grid, except losses. These
losses are increased with the injection of reactive power,
causing a slightly lower exchange of active power than the
previous simulation case. Fig. 13 shows the generated output
voltage that is equal to the grid voltage. Fuzzy surface
obtained for MPPT is given in fig.14. Step function for the
wind speed is given in fig. 15. The error signal (E), indicating
the difference between the Pmax and Pout is shown in fig.16.
Maximum power profile using FLC is obtained as shown in
fig. 17.
Fig. 6 Membership functions of the fuzzy input
The fuzzy rule table of these fuzzy sets is given in
Table 1.
TABLE 1
CE
E
ZE
SP
MP
LP
ZE
SP
MP
LP
MP
MP
LP
LP
SP
SP
LP
LP
ZE
SP
MP
LP
SP
SP
MP
LP
Fig 7. Power versus rotor speed at various wind speeds
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VSI output active and reactive power
 =0º
 =10º
 =20º
 =15º
Fig. 8 Cp vs  , for various pitch angles
Fig 11. Simulation results for APCM
VSI output active and reactive power
Fig. 9 VSI Gate pulse
Fig 12. Simulation results for APCM and VCM
Fig 13. Generated Output Voltage
Fig 10. WTG output power with P&O control method
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Fig. 17 Maximum Power Profile
Fig. 14 Fuzzy surface
VI. CONCLUSIONS
In this paper, a three level control approach of a three-phase
grid-connected wind energy conversion system, incorporating
a maximum power point tracker (MPPT) for dynamic active
power generation jointly with reactive power compensation of
distribution utility systems has been presented.. The fast
response of power electronic devices and the enhanced
performance of the proposed control techniques allow taking
full advantage of the Wind turbine generator. Fuzzy Logic
Controller for MPPT is found to be more efficient than the
conventional controller in terms of response time, settling time
and robustness.
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Fig. 15 Step function for wind speed
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