International Journal of Advanced Engineering Research and Technology (IJAERT) Volume 4 Issue 6, June 2016, ISSN No.: 2348 – 8190
223
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A New Stability Enhanced Power System Based on Adaptive Controller and
Space Vector Technique
Abeena A*, Faris K K**
* (PG Scholar, EEE Department, Al-Ameen Engineering College, Shornur
** (Assistant Professor, EEE Department, Al-Ameen Engineering College, Shornur
Abstract
Most of the wind energy conversion systems are deployed or
integrated into the grid using Double Fed Induction
Generators. This paper proposes a wind energy conversion
system using permanent magnet synchronous generator
along with pulse width modulated current source inverter. It
forms a good alternative because of its high reliability and
efficiency. The proposed system can be made adaptive to
varying wind speed providing an adaptive control strategy
with an aid of PI controller which is self-tuned based on
linear approximations and also by a maximum power point
tracking system. The pulse width modulation can be
achieved by the algorithm of space vector modulation
technique that may control the power output of the inverter.
Keywords: Adaptive PI control, permanent magnet synchronous
generator, Maximum power point tracking, pulse width
modulated current source inverter, space vector modulation
I. INTRODUCTION
Most of the wind turbines for on-land
emplacements use double fed induction generators due to
their economic advantages (i.e., high efficiency, improved
controllability and reduced rating of the converter). The
challenges of making the wind energy conversion system
adaptive to varying wind speed can be met by a combination
of non-conventional energy conversion systems and
improved adaptive control strategies. One of the most
promising of them is the permanent magnet synchronous
generator (PMSG) which has clear advantages in terms of
efficiency and power density. Integration into the grid of this
type of generators requires a full rated AC/AC converter.
The possible type of converter is the pulse-width modulated
current source converter (PWM-CSC) which has potentially
more advantages for medium size wind turbines. It is
capable of controlling the DC current according to the wind
velocity independently of the DC voltage. This characteristic
is exploited to create an adaptive control which does not
require measure of the rotational speed. In addition, it
permits the use of a full bridge diode rectifier in the side of
the machine and hence, efficiency and reliability are
improved.
The adaptive control techniques that perform
identification and control of dynamic systems can be
adapted to highly-complex dynamic systems in order to
auto-adjust the controller parameters. However, these
methods require an adequate initialization of the controller
parameters and detailed system data. Adaptive control
allows the integration of wind resources as plug-and- play
devices in electric power systems. As a result, this type of
control is a key technology in smart-grids and electric
energy systems with non-dispatchable generating sources.
The PI controls has been widely used for control of
power systems, but the tuning of these controllers is a highly
demanding task when the parameters of the controlled
process either are poorly known or vary during normal
operation. An adaptive PI control can be designed in order to
achieve high-performance control systems. However, during
normal operation where the controlled process are almost
time invariant, a fixed PI control may have similar
performance in terms of reference tracking. Additionally,
since the process is nonlinear, by using linear estimators it is
possible to obtain a time varying linear approximation which
can be used to self-tune the controller.
Thus proposed a new adaptive control strategy for a
wind energy conversion system based on a permanent
magnet synchronous generator and a pulse-width modulated
current source converter. The proposed conversion system is
a good alternative due to its high efficiency and reliability.
The control strategy uses an adaptive PI which is self-tuned
based on a linear approximation of the power system and a
desired closed loop response.
F
II. WIND ENERGY CONVERSION SYSTEM
The increasing number of renewable energy sources
and distributed generators requires new strategies for the
operation and management of the electricity grid in order to
maintain or even to improve the power-supply reliability and
quality. In addition, liberalization of the grids leads to new
management structures, in which trading of energy and
power is becoming increasingly important. The power-
electronic technology plays an important role in distributed
generation and in integration of renewable energy sources
into the electrical grid, and it is widely used and rapidly
expanding as these applications become more integrated with
the grid-based systems. The proposed energy conversion system is based on
PMSG. This type of machine has three main features which
are relevant for wind power applications: there are no
significant losses generated in the rotor; magnetization
provided by the permanent magnets allows soft start; and
there is no consumption of reactive power. The first
characteristic implies an improvement in efficiency while the
second and third effect the power electronic converter which
does not require bidirectional power capability. Hence, a full
bridge diode rectifier is enough for the AC/DC conversion. In
addition, PMSGs allow smaller, flexible and lighter designs
as well as lower maintenance and operating costs. A gear box
is not required if it is designed appropriately with a high
number of poles.
A PMSG requires a full rated converter which is
usually a back-to-back configuration with voltage source
converters as shown in Fig. 1(a). This type of converter is
International Journal of Advanced Engineering Research and Technology (IJAERT) Volume 4 Issue 6, June 2016, ISSN No.: 2348 – 8190
224
www.ijaert.org
efficient for integrating induction generators since it controls
reactive power in the rectifier as well as in the inverter.
However, a PMSG does not require reactive power and hence
the rectifier can be replaced by a diode rectifier [11].
Nevertheless, the DC voltage in a VSC must remain within
certain limits in order to maintain stability. As a consequence
of this, a DC/DC boost converter is required for controlling
the power in the electric machine as depicted in Fig. 1(b).
The use of a three-phase diode rectifier improves the
efficiency and reliability of the energy conversion system but
the boost converter could have an opposite effect.
Three main possible configurations of PMSG are:
Fig 1(a): back to back converter with VSC’s
Fig 1(b): diode bridge rectifier and diode converter
Fig 1(c): proposed conversion system
Variation on the DC voltage is not a limitation on
the PWMCSC; hence the power can be controlled directly
by the inverter. In addition, a PWM-CSC does not require an
electrolytic capacitor as the VSC. This impacts the
reliability of the systems since 30% of failures on AC
converters are related to the electrolytic capacitor.
PWM-CSC technology has been applied
successfully in a wide range of applications such as motor
drives, power quality conditioners and HVDC transmission
for offshore wind generation. Unlike the line commutated
converter a PWM-CSC is based on forced commutation and
consequently it is able to control active and reactive power.
In addition, it has an inherent short-circuit protection
capability.
A PWM-CSC requires semiconductor devices with
reverse voltage blocking capability. This can be added to a
standard insulated-gate bipolar transistor (IGBT) using a
diode connected in series as shown in Fig. 2
Fig 2: pulse width modulated CSC
Another alternative is the new type of
semiconductor devices such as reverse blocking IGBTs
(RB-IGBT) or integrated gate commutated thyristors
(IGCTs). The latter alternative is promising for PWM-CSCs.
The DC current is directly controlled by the
converter. This feature is especially important for low wind
velocities when voltage in the machine is greatly reduced.
While a voltage source converter requires a constant voltage
on the DC side, a PWM-CSC is able to adapt its voltage
according to the wind velocity. Efficiency is improved due
to this capability. The unity power factor is achieved by the
modulation itself. This can be done by using space vector
modulation. In addition, output voltage presents low
harmonic distortion and the performance for weak grids is
guaranteed.
Nevertheless, PWM-CSC has some challenges related to the
control of the converter. The filter placed in the AC side can
create resonances with the grid so that active damping
techniques are required. However, these techniques reduce
the band width of the control. In addition, the voltage on the
DC side must be controlled according to the wind velocity in
order to improve efficiency and guarantee stability.
III. PROPOSED CONVERSION SYSTEM
Fig 3: proposed hierarchical strategy with adaptive control and SVM
technique
International Journal of Advanced Engineering Research and Technology (IJAERT) Volume 4 Issue 6, June 2016, ISSN No.: 2348 – 8190
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1. Maximum Power Point Tracking (MPPT)
The power generated by a wind turbine is
proportional to the cube of the wind velocity.
Maximum power transference is achieved by an optimal
value of
Consequently the rotational speed must be proportional
to the wind velocity and hence, power must be proportional
to the cube of the rotational speed.
On the other hand, the PMSG is modelled on the
rotor reference frame (dq) as follows:
The voltage UDC on the diode rectifier is proportional to the
voltage in the terminals of the machine which in turn is
given where a proportional constant.
UDC(pu) = s
A speed sensor is not required when using this
expression since the voltage UDC is measured. The generated
power is given by UDC . IDC (PMSG losses are ignored). As a
result, the optimal IDC to achieve maximum tracking
IDC(t) = G . (UDC(t))2
This equation establishes a set point for current IDC as given
in Fig. 4
Fig.4: Reference for using a maximum tracking point algorithm
A low pass digital filter (LPF) is required to
smooth voltage. The cut-off frequency is set below
commutation frequency. On the other hand, the dynamics of
IDC depends on the inductance LDC as follows:
The modulation of the converter depends on the
current IDC which varies according to the wind velocity but
cannot be zero.
Where Px is the power delivered by the converter which in
turn depends on the modulation index m as follows:
where is the angle of the output current. This angle must
be equal to the angle of the grid voltage in order to achieve a
unity power factor. A phase locked loop is required as
illustrated in Fig. 7.1. Therefore, the only control variable is
m
The output power beyond the capacitive filter is
approximately equal to Px. Usually, the control in current
source converters is made in two stages, one controlling the
active power and the other controlling the voltage in the AC
side. This approach directly controls the active power and
the reactive power is maintained by the modulation itself.
Therefore, the possible resonances on the controls are
reduced.
2. Adaptive PI Controller
By adaptive control any control strategy which uses
parameter estimation of the plant in real time by using
recursive identification. The adaptive controller to be
designed is based on the certainty equivalence principle:
design the controller as long as the plant parameters are
known. However, since these are unknown at time tk, they
are replaced by an estimate given by an online identifier.
This adaptive controller is easy to implement, since
for the controlled plant, only the output signal is needed for
feedback. An adaptive PI control is designed where the plant
parameters are estimated by an online identifier, as shown in
Fig. 5
Fig. 5: Adaptive control and identifier
In continuous time, a PI controller can be defined as
International Journal of Advanced Engineering Research and Technology (IJAERT) Volume 4 Issue 6, June 2016, ISSN No.: 2348 – 8190
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being u(t) the control signal, and e(t) the error signal
(represented by the difference between the reference and the
output signals). In this case, these variables are given as
follows:
-
In discrete time, the PI controller can be defined as
Being the sample time h=tk-tk-1, e(tk)and ei(tk) the error and
the integral error at time tk respectively, and ei(tk-1) the
integral error at time tk-1. By defining a delay operator q-
1such as y(tk-1)=q
-1y(tk) . Equation can be rewritten as
follows:
Therefore, the control signal at time tk can be expressed as
Obtaining the following expression for the PI controller in
discrete time
where the parameters and of the PI controller in continuous
time can be related to the controller in discrete time, as
follows:
Since the process to be identified is nonlinear, the identified
model is a linear approximation of the nonlinear model at
time instant tk. A simplified first order model is selected,
described by a discrete transfer function, as
Equations by using the transformation as follows:
and
By using equations it is possible to formulate the block
diagram of Fig. 5
Fig. 6: Diagram block using transformation
From this figure it is possible to obtain the closed loop
transfer function, as follows:
If defining desired closed loop poles, given by
Pd (z) = (1- 1z-1
) (1- 2-2
)
where 1 and 2 are the discrete time roots of (34), which
can be related to the continuous time roots 1 and 2 by
using
1=es1h
2=es2h
It is possible to obtain the controller parameters by
comparing the closed loop poles with the desired closed
loop poles as follows:
Therefore, the controller parameters can be obtained as
where it is evident that c1 and c2 are related to the linear
approximation model of the nonlinear process, represented
by the discrete transfer function. When the projection
International Journal of Advanced Engineering Research and Technology (IJAERT) Volume 4 Issue 6, June 2016, ISSN No.: 2348 – 8190
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algorithm is applied in for the estimation the following
actualization rule is obtained:
where a1’(tk) and b0’(tk) are the estimated parameters at time
tk, and a1’(tk-1) and b0’(tk-1) are the estimated parameters
at time tk-1. Since the controller parameters are dependent on
and according a1’ to b0’, a time varying parameters for each
can be obtained as follows:
where c1(tk) and c2(tk) are automatically tuned according to
the desired closed loop poles.
Finally, the controller parameters KP and KI can be
calculated by
Therefore, the resultant controller is an adaptive PI
controller calculated for each tk. The behaviour of the
controller can be determined by the selection of the desired
closed loop poles and the sample time h.
3. Model Reference Adaptive Control
Reference current Iref is modified during a short
circuit in order to improve the short circuit behaviour of the
converter. A slightly different current Iref in which the
desired output is generated by a linear reference model is
proposed. The reference model can be selected with an order
less than or equal to the order of the process. In this work, a
zero order model is used in pre-fault (I’ref=Iref), no control
during the fault and a first order model after the fault as
follows:
where 0 must be selected as a stable root ( | 0 | < 1 ) ,
where it is clear that the reference model must be selected as
a stable model with unitary gain. However, the selection of
the reference model and the pole placement technique are
separate problems, so it is evident that by using a reference
model the flexibility of the control system in the assignment
of the closed loop poles is increased. The fault condition is
detected using the voltage Ux.
IV. RESULTS
Wind velocity for 15-s simulation is performed. Base wind
velocity is 12 m/s. A gust is simulated in order to
demonstrate the maximum tracking point capability of the
proposed control. Wind velocity profile was created using a
detailed model which considers stochastic behaviour.
Rotational speed and voltage are plotted. The linear
approximation given in (5) is more accurate for low wind
velocities. At high wind velocities, the generated power
increases the current and hence, the voltage drop on the
inductance influences the generated voltage.
The linear approximation is accurate enough from
a practical point of view and maximum tracking is achieved.
High inertia of the set turbine-generator produces a delay in
the rotational-speed tracking capability but also a smoothing
effect. This is expected in almost all type of controls for
wind energy. Generated power. Wind velocity is again
shown in this figure. An almost perfect tracking
characteristic is achieved. The control strategy changes
dynamically according to the wind conditions. If a time
invariant PI control is used the performance could be similar
at least at nominal wind velocity. In that case, the proposed
algorithm can be used as a tuning technique. Three-phase
voltages and currents in the PWM-CSC. Small harmonic
distortions are present in three-phase voltages due to the
commutation process. They are attenuated by the
transformer and hence, the voltage in the point of common
coupling is completely sinusoidal. A smoother waveform
can be achieved by increasing the switching frequency at the
expense of higher switching losses.
Transient behaviour of the proposed control was
also tested in the same distribution feeder. Wind velocity
was maintained constant in 12 m/s. A three-phase short
circuit at Node 3 was simulated. The voltage on the grid
dropped to almost zero. Current increased due to the drop on
the grid voltage in Node 3. The converter still worked in this
condition maintaining the unity power factor. The reference
model enter into operation by maintaining. This allows for
energy storage in three-phase voltages due to the
commutation process. They are attenuated by the
transformer and hence, the voltage in the point of common
coupling is completely sinusoidal. A smoother waveform
can be achieved by increasing the switching frequency at the
expense of higher switching losses.
Transient behaviour of the proposed control was
also tested in the same distribution feeder. The reference for
changes smoothly since it depends on the wind velocity. The
modulation index increases up to the point of over-
modulation. Consequently, the parameters of the control
decreases. These parameters return to their normal values
after the fault is cleared. Notice that the voltages and
International Journal of Advanced Engineering Research and Technology (IJAERT) Volume 4 Issue 6, June 2016, ISSN No.: 2348 – 8190
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currents after the fault are within the maximum limits due to
the introduction of the reference model.
Fig.7: Wind velocity provided to the system having 300 varying wind
speeds for 0-15 sec
Fig 8: Output of Stator voltage and Stator Current (with fault time from
0.6-0.7 sec)
Fig. 9: Output of DC Voltage and Current (with fault time between 0.6-0.7
sec)
Fig.10: Output of Modulation Index(m), DC Current(Idc), Reference
Current(Iref), Total Power(P)(with fault time 0.6-0.7 sec)
Fig. 11: Output of PWM-CSC (with fault) showing the decrease in Voltage
and increase in Current at 0.6-0.7 sec
Fig. 12: Output of Grid showing the Voltage zero and high Current with
fault time 0.6-0.7 sec
International Journal of Advanced Engineering Research and Technology (IJAERT) Volume 4 Issue 6, June 2016, ISSN No.: 2348 – 8190
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Fig 13: FFT Analysis with fault
V. CONCLUSION
Thus a new stability enhanced power system was
implemented based on adaptive controlling technique and
space vector modulation. Both the control and the type of
converter increase the flexibility of the wind turbine. They
are able to operate in critical conditions such as short circuit
and fast changes in wind velocity. Measurements of wind
velocity or rotational speed are not required. A reference
model is used to improve the transient behaviour of the
control after critical faults. For systems with time invariant
behaviour, the adaptive controller also behaves as a fixed
controller. Therefore, it can be seen that he adaptive
controller method can be used as a technique for self-tuning
the controller based on the desired response.
The extension of this project can be performed
moving form generation side towards transmission side.
Transmission of power is a high demanding task. It require a
thorough analysis and procedure to reduce the losses
involved. The best option on extending the project is
focusing on to transmission side using HVDC links that
shows high priority in reduced power loss transmission.
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