Due to its advancements and enhanced usability Doubly fed Induction Generator
find its application in most of the Wind Turbines and in all wind Power
Generation. Grid connected wind turbine will generally experience faulty
condition, it will leads to fault ride through of the turbine which in turn
reduces the reliability of the system. To enhance the low voltage ride through
capability of wind turbine a control strategy is to be framed. The existing
crowbar method for DFIG to protect Rotor Side Converter and Grid Side Converter
but makes the system more weak by absorbing more reactive power from the
system. In this paper Fuzzy Logic controller is used to limit the deviations of
steady state values during and after faults in the grid and thereby reduces the
need of crowbar for the system. The designed fault detection and confrontation
system manages attenuate the disturbance during fault which would supply the
reactive power to the grid. The MATLAB/SIMULINK TOOL is used to model the
controller and test the validity of the control over the Grid connected wind
turbine over weak ac signal.
Words: Fuzzy Control, DFIG, LVRT
The grid connected DFIG contains wound
rotor and stator windings. The stator windings are directly connected to grid and rotor winding
connected to grid via two back-to-back converter. This converter provide
optimized control of active and reactive power and it is cost effective and
smaller in size. Although DFIG has a major drawback of absorbing more reactive
power from the grid when subjected to fault. Whenever fault occurs, at the
stator windings results change in stator flux of the DFIG which provide an over
current to the rotor windings due to magnetic coupling.
to this over current the rotor side converter is affected and that leads to
large fluctuations of DC-LINK voltage . In order to protect the rotor windings
crowbar protection was applied. Crowbar circuit consists of bank of resistors
and with the help of power electronic devices it is connected to the rotor
windings. Whenever the fault occurs, Rotor Side Converters is disabled
temporarily and crowbar circuit is connected to the rotor windings. This type
of protection is not much effective there is considerable loss of output power.
When the large transients and faults occurs in the grid crowbar protection is
deactivated and DFIG is disconnected from the grid.
a days wind generator contributes substantial amount of power over the total
power generation in India. As per grid code requirements the WT should have
LVRT capability during grid faults resulting in more than 85% voltage drop.
This clearly shows that they should provide supply power to the grid during and
after grid faults, to improve the system stability 5.
8 is proposes a control by flux linkage tracking control method. The control
system is not depends on the system parameters for that decoupling of DC and
negative sequence components is not necessary. Even though the proposed method
is manages to enlarge the control action, but it has many drawbacks that could
not be avoided. Properly designed fuzzy controller (FC) is better than a
traditional proportional integral (PI) controller. There are many research
works are carried out to prove that the FC manages to limit the rotor current
during the fault, with the elimination of
external devices. However in these work grid code requirements is not
described properly. This control scheme can applied to the small voltage dip.
Fuzzy logic controller acts as a protective device when the DFIG subjected to
external fault when compare to traditional PI controller, result FC satisfies
the grid code requirements.
Based on the various analysis and
results studied from works so far, this paper interested to expand the concept
of the protection of the DFIG without the presence of added hardware. This
endeavor is applied to DFIG during asymmetrical fault. The proposed method
contribution to the most optimum co-ordination of the two converters. The
objective is to improve system stability and reduce the disturbances to the
system 9. In order to come across from the difficulties met due to unresolved
of the system, the controller were proposed based on Fuzzy Logic Controller
(FLC). By using the concept FC model the rotor over current and dc link over
voltages are effectively diminished. In addition the grid code requirement
fulfilled such as FRT capability of the DFIG and reactive power supplied to the
II. MODELLING OF DFIG
2.1. General Schematic Diagram of DFIG
shows the general schematic diagram of a grid connected DFIG system. The
modelling of DFIG have been suggested by grid code is that, the WT should be
connected through a mechanical shaft system, which is to be a low speed turbine
shaft connected to high speed generator shaft via a gearbox. The DFIG is a
variable speed wind generator , it consists of two windings rotor and stator
side, where the stator windings is connected to a grid output without any
intermediary and rotor windings are connected via two back to back converter
namely RSC& GSC as shown in Fig. 1. The ac/dc/ac converter is an IGBT based
PWM converter 3.
of Wind Turbine
It is accepted that the efficient design
of Wind Turbine Rotor plays a major role to accomplish maximum wind power
generation. To achieve an optimum wind power generation design of wind turbine
blades, diameter of rotor, blade pitch angle, the transmission system and gear
box, blade chord, tower length should be determined. The maximum power obtained
from the wind is directly depends on the speed of the rotor and maximum power
can be expressed as,
Pmax = (1)
At the optimum operating point the
maximum value of power can be written as,
– Maximum power
– Radius of the rotor
– Tip Speed Ratio
– Rotor Speed
– Wind Speed
The maximum power extraction is the
function of tip speed ratio and pitch angle so that the specific value of TSR
(?) should be maintained. Figure 2 shows
typical characteristics of the wind turbine using the Cp versus ? curve.
2.2. Cp versus ? curve
pitch angle ? is kept constant at zero degree until the speed reaches point D
as shown in Figure 2.2.
2.3. ABCD curve
Modeling of DFIG
studied system represented by the following equations, the mechanical power and
the stator electric power output are computed as follows,
Protor = Tm*
For a loss less
generator the mechanical equation is,
at fixed speed for a loss less generator,
Tm = Tsm and Pm
= Ps + Pr (4)
Pr = Pm-
Ps = Tm ?r + Tem ?s =
s=( ?s- ?r) ? ?s
Based on the
dynamic operating characteristics of DFIG the voltage and flux linkage
equations are given by,
?ds = – Ls ids
+ Lmidr (9)
?qs = – Ls iqs
?dr = Lr idr + Lmids
?qr = Lr iqr + Lmiqs (12)
,Vds – direct and quadrature
axis stator voltages
,ids – direct and
quadrature axis stator current
,?ds – direct and quadrature
axis stator flux linkage
,Vdr – direct and quadrature axis rotor voltage
,idr – rotor current in d-q reference frame.
,?dr – direct and quadrature axis rotor flux linkages
,Rr are the stator and rotor
resistances of machine per phase
,Lr are the leakage inductances of stator and rotor windings.
Figure 2. Rotor Side Converter
3. Grid Side Converter
Optimized control system for the DFIG has been separated into two converters
RSC and GSC as shown in figure 2, figure 3. These two converters are generally
used to obtain regulated voltage by controlling real and reactive power. In
order to reach enhanced control of active and reactive power, the park
transformation of current components is accomplished using a reference frame
oriented technique where q-axis current component controls the active power in stator
efficiency of the system is depends on the load characteristics of the entire
system, thus the Maximum Power Point Tracking (MPPT) Technique is employed to
determine the feasible operating point of the system, that can be given to the
reference value of the active power. The input of the power controller is the
difference between Pr and Pr-ref, the error is given to the power controller.
The observed value of the q-axis rotor current is compared with the actual
value of iqr and the error is
driven to the current controller. This output value has been considered as reference voltage for
q axis component vqr.
the DFIG is subjected to fault and connected with weak power system the RSC can
be activated to provide reactive power compensation. In case the DFIG is connected with strong power system the
control action is not involved. In this work, the DFIG is connected to weak ac
grid and unconventional performance of the system is studied and appropriate
control action has been taken instead of reactive power control. The computed
voltage from the generator terminals is compared with its reference value and
error signal for the d-axis current. The
current controller provides
reference voltage for the d-axis rotor terminals in which input of the
controller is obtained by comparing the error signal from voltage regulator and
the d-axis current. The desired output signal vdr and vqr are
transformed into abc components. These components are driven by the PWM module
to generate the IGBT gate control signals.
dc link voltage is maintained as constant with the help of GSC. In this paper,
the reactive power is considered to be neutral by setting Qgc_ref=0.
The control system of GSC is shown in Figure. 3. The reference frame oriented
vector control is applied for three
phase quantities into dq transformation. The dc voltage and the reactive power
can be controlled by d-axis reference frame current and q-axis reference
III. OPTIMIZED CONTROL SYSTEM
optimized control system intends to have enhanced LVRT capability of the DFIG
independently. RSC is modified with fine-tune fuzzy controller. In other words
modified RSC to make it an optimized control system. Figure 4 shows optimized
control system where fault detection and confrontation system (FDCS) is
introduced. Depending on the deviation of percentage of voltage control block
is activated (or) else set to be ideal. Only 10% of voltage sag is allowed from
the reference value. The abstraction of the control strategy is achieved by
considering two major deviations in RSC. By the means of the drastic decrement
in rotor over current and dc link over voltage will lead to successful
protection of DFIG. Due to sudden changes in the system , dc voltage and rotor
current will be exceed their limits. During the period of transient the
existing amount of energy, that is to be properly pumped through converter and
connected to the grid, in order to fetch the value of the rotor current and dc
voltage back to their desired
voltage can be attenuated or eliminated by reducing the rotor current but the
rotor current cannot be minimized after certain value. Fault ride through
capability of the DFIG can be achieved only by taking rectifying signals into
account and also the value of dc voltage should be consider.
A. Fuzzy Controller
logic controller is used to control the speed and power of DFIG. It is known for its precision and it
can be implemented in simple manner. Mamdhani type fuzzy controller is used due
to its robustness of control. Rotor current and dc voltage are input signals of
fuzzy controller and output signal is command signal generator which will be
compared with the quadrature axis rotor voltage and this signal from the fault
detection. The current controller is corrected by a quantity derived by a Fuzzy
Controller, FCFRT. The inputs of
FCFRT, Vdc?, ir? are
given by equation.13, 14. Where ss denotes for the steady state value just
before fault, mv stands for manufacturer value.
Figure 4. Optimized Control System
The actual values of Vdc’, ir’
are processed through fuzzy control system. They are made as fuzzy values when
it is processed through fuzzy interference system. Triangular membership
function will be apt for both voltage and current as their values will increase
and reach peak value at a time. The modulation index (Ucrf)
calculated from the fuzzy expert system finds the deviation from the settled
value. The deviations include both positive and negative deviations. Positive
deviations shall be taken into account leaving out negative deviations. The
fuzzification process is done in Mamdani
system. The rules framed in fuzzy set between two inputs and the index are
classified into five subsets for the three different values classification of
inputs. Neglecting of negative values of Ucrf will lead to easy
defuzzification process when we can obtain the actual value to be applied to
the controller system.
MATLAB STIMUATION TOOL is used
for stimulation work. The twice fed induction generator (1.5 MW) is modelled
which supplies electrical power to a weak power system. A three phase fault is
introduced to an electrical system at t=1.2 s resulting in voltage sag of 85%
dip in normal voltage. The simulation output is compared for the above
electrical system, the proposed control system moderates the fault periods and
the response during and after fault periods seems to be good which shows that this control system can make
the DFIG to successfully overcome the fault. The parameters of the electrical
system are given in the Table II, III.
from good ride through capability of DFIG, Rotor Side Converter is continuously
being active throughout the fault period and after the fault period thereby
supplies reactive power to the grid, which is useful for balancing the voltage
caused by three phase fault. By the rapid recovery system of proposed control
system the need for large amount of reactive power from the DFIG during faulty
conditions can be reduced. DFIG along with proposed control system supplies the
required amount of reactive power to the grid which maintains the ac voltage of
PARAMETERS OF DFIG (1.5 MW)
OF THE AC GRID
circuit ratio at the PPC
5.Rotor Current with controller
Figure 6. DC Voltage with
7. Rotor Current without controller
8. DC Voltage without controller
1 1.1 1.2 1.3 1.4
1.5 1.6 1.7 1.8 1.9
9. Response of the system with controller
Improved LVRT capability grid connected
DFIG has been implemented with the absence of external hardware. This paper
explains, the DFIG could feed the electrical system during the fault and after
the fault period. It can be achieved through fuzzy controller by effectively
minimizing the rotor over current and dc link over voltages. This new enhanced
system makes our wind power generation system more stable with greater
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