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Power quality enrichment using enhanced adaptive control-detuned-LC
proposal in voltage source control conquered distributed generation with
hardware implementation
Article in Transactions of the Institute of Measurement and Control · October 2018
DOI: 10.1177/0142331218801157
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Article
Power quality enrichment using
enhanced adaptive control-detuned-LC
proposal in voltage source control
conquered distributed generation with
hardware implementation
Transactions of the Institute of
Measurement and Control
1–14
Ó The Author(s) 2018
Article reuse guidelines:
sagepub.com/journals-permissions
DOI: 10.1177/0142331218801157
journals.sagepub.com/home/tim
Moushumi Patowary1 , Gayadhar Panda1 and Bimal C Deka2
Abstract
This paper presents the collective operation and comparative assessment of artificial neural network (ANN)-based adaptive controller with detunedinductor capacitor (LC) filter facility in grid-tied voltage source control (VSC) system. In order to facilitate proper shaping of VSC outputs and to avoid
voltage surge or current surge issues that may occur during the synchronization, the controlling action should reflect importance of total impedance
(Zt) effect for: (i) accurate online weight updating, (ii) generation of correct references for proper shaping of VSC outputs, (iii) accurate assessment
and exclusion of current harmonics and (iv) robust in defending any system perturbation. This impedance is taken into consideration during the runtime weight updation process through extended control steps in order to pass over various losses that certainly occurs in transformers, filters, line
parameters and so forth. Performance of the system is well improved with an inclusion of total impedance (Zt) measured between the VSC and point
of common coupling (PCC). A detuned-LC filter is predominantly intended for reactive power compensation, power factor correction, prompt and
accurate alleviation of the harmonics. A comparative assessment in between enhanced and conventional adaptive controllers that are designed in
MATLAB/Simulink clarifies the robust performances of the proposed control design under sundry system turbulences. The verification of the proposed
enhanced controller is approved with the hardware results obtained using dSPACE RTI 1202 kit.
Keywords
Distributed generation (DG), artificial neural network (ANN), power quality (PQ) enrichment, adaptive current control, stability, filter design, dSPACE
Introduction
The distributed power generation (DG) and management
ideologies have almost covered a huge share in today’s marketplace (Su and Wang, 2012). Traditionally, distributed
power generation using renewable resources viz. photovoltaic
(PV) and wind farm reduces the concentration of greenhouse
gasses in an extensive way (ElMoursi et al., 2013; Sen, 2008;
Teodorescu et al., 2011). In a practical outset, as the terminal
voltage of DG models is reasonably low, numerous maximum
power point tracking (MPPT) control strategies are being
used to boost up the terminal voltage, reported in literature
(Azevedo et al., 2008; Benadli et al., 2015; Martin and
Vezquez, 2015; Zhou et al., 2008). Again, the key objective of
voltage source control (VSC) circuitry in DG application is to
exchange suitable active and reactive powers in between the
source and loads with minimum power losses (Freijedo et al.,
2011; Luo et al., 2013; Singh and Solanki, 2009; Verma et al.,
2012; Rocabert J et al., 2007). The grid synchronization techniques like phase lock loop (PLL) are widely used for fast and
accurate information collection of fundamental positive
sequence components (Blaabjerg et al., 2006; Hadjidemetriou
et al., 2013; Karimi-Ghartemani et al., 2004; Karimi-
Ghartemani and Iravani, 2004; Timbus et al., 2005). The unitvoltage-vector-template method can also be used for gridsynchronization process as a vector generally gives amplitude
as well as direction at the same time (Verma et al., 2013).
Different current and voltage control strategies are presented
in literature (Akagi et al., 2007; Conti et al., 2009; Fu et al.,
2016; Lin, 2007; Mattavelli, 2001). In Conti et al. (2009), a
comparison between conventional linear and non-linear current control techniques is put into a table. An RNN-identified
control scheme along with LCL filter for grid integrated 1phase converter model is projected in Fu and Li, 2016, where
the proposed control technique is compared with proportional integral (PI) and proportional resonant (PR)-based
conventional techniques. Another ANN-based adaptive grid1
Department of Electrical Engineering, NIT Meghalaya, India
Department of Electrical Engineering, Assam Engineering College, India
2
Corresponding author:
Moushumi Patowary, Department of Electrical Engineering, NIT
Meghalaya, Bijni Complex, Laitumkhrah, Shillong - 793003, Meghalaya,
India.
Email: [email protected]
2
Transactions of the Institute of Measurement and Control 00(0)
voltage sensorless integrating design for grid-tied VSC along
with deadbeat current control is proposed in Mohamed et al.
(2008), where interfacing parameters and the grid voltages are
estimated for low computational demand using ANN interfacing parameter identifier with an ANN grid-voltage estimator. Another control structure using recursive least square
estimator in active filter application is mentioned in Fallah M
et al. (2015). Another neural network-based control algorithm
is introduced for active power filter application in Garanayak
and Panda, 2016, where precise estimation of fundamental
harmonics, sub-harmonics and inter-harmonics of a polluted
current signal along with adaptive noise are demonstrated.
ANN-based control technology, namely leaky least-meansquare for frequency estimation and real-time harmonics
assessment in a distorted power signal, is reported in Ray
et al. (2016) and Subudhi et al. (2012), respectively. It is found
that current harmonics compensation capability is not significant in all the conventional linear current control techniques.
However, non-linear current control techniques are very popular for their dynamic responses and can dominantly mitigate
low-order current harmonics. Wherein, nonlinear current control techniques can maintain power quality (PQ) standards
but most of them exhibit complex control design structure.
Due to this complexity, it becomes hard to figure out the root
cause of any issue occurred during the run-time process. At
the same time, maintaining PQ standards and power factor
correction (PFC) are two most essential aspects in power systems that are applied to compensate foremost technical issues
and cost-effectual penalties (Basu and Bollen, 2005; Li et al.,
2007; Monteiro et al., 2015; Garanayak and Panda 2018).
Moreover, a harmonic filter used in power circuit can serve
for both harmonic alleviation and power factor rectification
(Fu and Li, 2016; Mohamed and Saadany, 2008). Observerbased harmonics estimation approach applied in power distribution system is explained in Ujile et al. (2015).
The aim of this paper is to design one enhanced intelligent
controller with few desired characteristics of (i) accurate
online weight updating, (ii) generation of correct references
for proper shaping of VSC outputs, (iii) accurate assessment
and exclusion of current harmonics and (iv) robustness in
defending any system perturbation. Performance of the system is well improved with an inclusion of total impedance (Zt)
measured between VSC and PCC, which is addressed during
the run-time weight updation process. When DGs are integrated to the utility grid, various losses that certainly occur in
transformer, filter circuitry, connecting wire, and so forth,
present in between VSC and PCC are to be addressed during
the control action to acquire proper shaping of VSC outputs.
In the existing literature, the utility grid is always demonstrated as a single 3-phase, 3-wire or 3-phase 4-wire source. It
may be a substation for some cases and there may arise many
synchronization issues that are not explicitly addressed in the
previous literature. From the point of practical field, an utility
grid can be modeled as a combination of many more electrical
sources, parameters, loads and so forth. Thus, total impedance (Zt) in between VSC and PCC has a significant effect
on: (i) extracting balanced sinusoidal references, (iii) removing
unbalances from current components and (iii) avoiding voltage or current surges during synchronization. Considering
theses effects, it is most important to introduce Zt in run-time
weight updating process through extended control steps. The
self-tuning facility of the proposed ANN, along with extended
design steps, also maintain desired PQ standards under various system disturbances. In order to achieve fast and accurate
convergence, emphasis is made to select an appropriate value
for convergence rate. In addition, a detuned-LC passive filter
is predominantly intended for reactive power adjustment,
PFC, and prompt and accurate alleviation of the harmonics.
A comparative study using enhanced and conventional adaptive current control techniques is also presented to crossverify control and system performances. Furthermore, the
verification of the proposed enhanced controller is confirmed
with hardware results obtained through dSPACE RTI 1202
kit.
System description
The circuit diagram shown in Figure 1 demonstrates the configuration of different power stages for DG-PV interfaced
grid-tied VSC controlled network. In a nutshell, the power
model is classified into two distinct areas: LV (low voltage) –
DG-end and HV (high voltage) – grid-end. A double-stage
power exchange (DC-DC and DC-AC) technologies are
incorporated for integration of DG-end to the grid-end
through VSC control operation. A steady DC-Link voltage is
necessary at VSC input which is maintained by using, (i) PIsthe outer loop voltage controllers and (ii) proposed enhanced
adaptive- the inner loop current controller.
Detuned LC filter
As the current harmonic compensation capability is not significant using conventional linear current control techniques,
there is a recent research focus in designing an enhanced adaptive current controller by considering few field problems. It is
also found that current harmonics compensation capability is
not significant in the conventional linear current control techniques. However, non-linear current control techniques are
very popular for their dynamic responses and can dominantly
mitigate low-order current harmonics. Keeping is in priority
too, a detuned-LC filter circuitry is modeled along with the
proposed controller in MATLAB/Simulink and the system
performances are analyzed under transient disturbances.
In order to deliver consistent and good quality of power
by the DG-PV-VSC system, a suitable filtering facility must
be connected in addition to the control circuit. The reactive
powers formed in power system may result in congestion in
transformer units, power losses, heavy transmission line
losses, heating of the lines, insulation issues etc. To omit these
post-intricacies, necessary amount of reactive powers has to
be compensated by the filter that are normally connected as
close as to the loads. In this paper, a detuned-LC passive filter
is proposed to eliminate the erroneous aspects of current harmonics. Basically, a reactor (L) that is associated in sequence
with the capacitor (C) helps in alleviating inrush currents or
voltages that may arise in capacitor bank. It also helps in filtering out voltage or current harmonics and improves quality
of delivered power. The existence of reactor increases primary
frequency voltages across the capacitor and this union is
Patowary et al.
3
Figure 1. Power and control blocks for grid-tied VSC interfaced PV (100kW) network.
Table 1. Association between relative impedance, tuning order, tuning
frequency and capacitor rated voltage.
Rel.
impedance
(%)
5.7
7
14
Tuning
order
4.2
3.5
2.7
Tuning
frequency
Network
in-service
voltage (V)
50 Hz
50 Hz
210
190
132
60Hz
250
230
160
60Hz
400
690
400
480
600
480
480
830
-
480
480
575
-
690
Figure 2. Two layer three input adaptive linear neuron.
tuned such that the detuned series resonant frequency is
always lower than system harmonic frequency. The associations between relative impedances expressed in % relative to
capacitive reactance, tuning order, tuning frequency and
capacitor rated voltage are listed in Table 1.
Neural network-based enhanced adaptive
current controller
ADALINE, which is termed as an adaptive linear neuron,
uses Widrow-Hoff innovation or least mean square (LMS)
algorithm to accustom wavering of the weights in a timeinvariant linear system in order to curtail the mean square
error. The basic block diagram for two layer three input
adaptive linear neuron is demonstrated in Figure 2.
According to conventional adaptive linear-LMS algorithm,
output Yk of a time-invariant linear system is expressed as
below
Yk = WTk Xk + b = W1 T X1 + W2 T X2 + W3 T X3
+ b; k = 1, . . . , n
ð1Þ
where Wk , Xk & b represent weight vectors, input vector and
a bias value, respectively. The weights Wk of inputs Xk are
varied in such a way that LMS error between desired vector
dk and output vector Y reaches to its minimum. The training
set is usually comprised of pairs of input Xk and target dk
such as (X1,d1), (X2,d2),.,(Xn, dn). The flow chart for the
proposed enhanced adaptive controller is shown in Figure 3a.
Applying Fourier series, 3-f load currents for phase-a can be
expressed as below
iLa ðtÞ =
n
X
In Sinðkvt + jk Þ = iDCa ðtÞ + iACa ðtÞ
ð2Þ
k=1
The DC current components of load current can further be
classified in the following way
4
Transactions of the Institute of Measurement and Control 00(0)
Figure 3. (a) Flowchart for enhanced adaptive current controller and (b) proposed enhanced adaptive current control diagram with voltage
controllers.
iDCa ðkÞ = I1 Cosj1 Sinvt + I1 Sinj1 Cosvt = Iat a ðkÞ + Irt a ðkÞ
ð3Þ
Substituting values iDCa ðkÞ in equation (2) yields
iLa ðkÞ = Iat a ðkÞ + Irt a ðkÞ + iACa ðkÞ = Iat a ðkÞ + Ixa ðkÞ ð4Þ
ixa ðkÞ = ILa ðkÞ Iat a ðkÞ = ILa ðkÞ Wat a ðkÞ:Uat a ðkÞ ð5Þ
where Ixa ðkÞ, Wat a ðkÞ and Uat a ðkÞ are termed as compensating current component, weight vector and unit voltage template of input voltages for phase-a, respectively. The purpose
of generating unit template vectors for extraction of accurate
current references is to make the system error-free as extensively as possible. For unit template calculation, grid voltages
(Vsa , Vsb , Vsc ) at PCC are sensed through the voltage sensors
and mostly considered as sinusoidal. Its amplitude is calculated as below
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
Vt = ½2=3(Vsa 2 + Vsb 2 + Vsc 2 )
ð6Þ
Sensed 3-f AC grid voltages are divided by their amplitude
(Vt ) to generate unit vector templates (Uat a, b, c ) for active
power components. Calculation of weights corresponding to
fundamental frequency d-axis and q-axis components of currents are computed as per the proposed adaptive enhanced
LMS control algorithm. This algorithm follows generation of
unit voltage vector templates to sustain minimum current
error (iLðKÞ WatðkÞ :UatðkÞ ) in the network. The estimation of
weights for active power components are derived as follows
Wat
a, b, cðk + 1Þ
= Wat
:Uat
a, b, cðkÞ
+ h:½iLa, b, cðKÞ Wat
a, b, cðkÞ
a, b, cðkÞ :Uat a, b, cðkÞ
ð7Þ
where h is the convergence factor that lies within the range
0\h\1. The error voltage calculated from sensed and
measured DC-Link voltages is fed to the VDC controller,
which will generate active power reference signal. Through
VDC, a conventional PI controller is being employed to
retain a smooth set-point tracking. In parallel, this will
also act as a voltage interruption elimination unit. The
load current harmonics might cause ripples in DC-link voltage, henceforth, a second-order low pass filter (LPF) is
inserted to nullify it, as shown in Figure 3b. The voltage
regulator on DC side (VDC) regulator is mainly used for
maintaining a steady DC-link voltage and its kth sampling
expression can be derived as follows
Iat
dcðkÞ
= Iat
dcðk1Þ
+ Kp
+ Ki
dc :½Vdc errorðkÞ
dc :Vdc errorðkÞ
Vdc
errorðk1Þ ð8Þ
where Ki dc and Kp dc are integral and proportional gains of
VDC regulator, respectively. For suitable tuning of the gains,
Zeigler-Nichols method is pursued. According to this tuning
process, the gain values for a PI controller are derived as
follows
Kp = 0:45 Ku
ð9Þ
Kp
Pu
ð10Þ
Ki = 1:2
where Ku is the maximum proportional gain until the circuit
starts to fluctuate and Pu is the oscillation period. Iat dcðkÞ ,
which is the loss part of active-power component of grid
current must be clubbed to the weight vectors for proper
run-time weight updating process. Therefore, corresponding
weight for kth sampling period for active-power component
of grid current can be expressed as below
Patowary et al.
Wat
eqðkÞ
5
= ½Iat
dcðkÞ
+ (Wat
aðkÞ
+ Wat
bðkÞ
+ Wat
cðkÞ )=3
Wrt
a, b, cðk + 1Þ
ð11Þ
As mentioned, the impedances measured in between
VSC and PCC have a significant impact in updating weights
for active as well as reactive power components to ascertain
pure sinusoidal references and also to minimize current or
voltage surges during the synchronization process. The total
impedance (Ztot) measured by considering choke coil impedance, transformer leakage impedance and line impedance
between those two points has to be amplified to the equivalent weight updating process. During estimation, introduction of Ztot in the weight updating process yields: (i)
extracting balanced sinusoidal references, (iii) removing
unbalances from current components and (iii) avoiding voltage or current surges during synchronization. The generation of accurate reference signals under any system
perturbation will ultimately deliver accurate on-off time
periods of the IGBT switches. Thus, PQ is maintained at
different power zones. The total impedance (Zt ) must be
injected in the weight updating process to reduce the voltage
or current spike while synchronizing. Thus, modified weight
updating expression will be as follows
Wat
eq propðkÞ
= Zt :Wat
ð12Þ
eqðkÞ
Thus, 3-f reference current corresponding to active power
components of grid current can be expressed in equation (13).
The generation of the unit voltage vector template for the
reactive power components can be calculated in equations
(14)–(16)
is
at a, b, cðkÞ
= Wat
eq propðkÞ :Uat a, b, cðkÞ
ð13Þ
= Irt
a, b, cðkÞ
a, b, cðkÞ
ð18Þ
Wrt
eqðkÞ
= ½Irt
acðkÞ
(Wrt
aðkÞ
+ Wrt
bðkÞ
+ Wrt
cðkÞ )=3
ð19Þ
With an introduction of Zt , the modified weight for reactive power components is formulated in (20). Therefore, 3phase reference currents for reactive-power components of
the grid current are estimated in (21)
Wrt
is
eq propðkÞ
rt a, b, cðkÞ
= Wrt
= Zt :Wrt
eqðkÞ
eq propðkÞ :Urt a, b, cðkÞ
ð20Þ
ð21Þ
The total reference currents are generated for each phase
by adding respective active and reactive reference current
components. The error differences between reference and
sensed grid currents are then amplified and compared to flat
frequency (5kHz) triangular carrier wave to produce 6-pulses
for 3-leg VSC operation, as shown in Figure 3b.
Convergence and stability analysis
The control algorithm proposed above ensures that the assessment for h determines rate of convergence of controller and
the correctness in the evaluation process. Higher the value of
h, better is the convergence but it tends to lower the accuracy
level. Therefore, emphasis has been given for proper selection
of an appropriate h value. It has a vital role towards the stability also. The generalized expression for estimation of the
weights shown in equation (7) can be written as below
Wðk + 1Þ = WðkÞ + h:2ðkÞ :UðkÞ
ð22Þ
The expectation of this weight vector is derived as below
Urt b = Uat c
Uat a
+
=3
=3
ð15Þ
Substituting 2(k) = (dK -Yk ) and Yk = Wk T Xk = XTk Wk
in equation (25), we get
Urt c = Uat a
Uat b
+
=3
=3
ð16Þ
E½Wðk + 1Þ = E½WðkÞ + hfE½dðkÞ :UðkÞ E½UTðkÞ WðkÞ :UðkÞ g
acðk1Þ
+ Kp
+ h:½iLa, b, cðkÞ Wrt
a, b, cðkÞ :Urt
ð14Þ
E½Wðk + 1Þ = E½WðkÞ + h:E½2ðkÞ :UðkÞ + Ki
ac :Vac
ac ½Vac errorðkÞ
Vac
ð23Þ
E½Wðk + 1Þ = E½WðkÞ + h:fh R:E½WðkÞ g
Similarly, using VAC regulator, which is also a conventional PI regulator, the error difference between the calculated
and sensed AC voltages at grid end is applied to produce qaxis reference. The output of VAC regulator for q-axis reference is formulated as below
acðkÞ
a, b, cðkÞ
Uat b
Uat c
+
=3
=3
Urt a = Irt
= Wrt
:Urt
errorðk1Þ ð17Þ
errorðkÞ
where Ki ac and Kp ac implies integral and proportional gains
of VAC, respectively. The estimation of weights for reactive
power components for three different phases are calculated in
(18). The equivalent weight for reactive-power components of
grid current at kth sampling time is calculated in (19)
E½Wðk + 1Þ = ðI h:RÞ:E½WðkÞ + h:h
ð24Þ
where,
h = E½d
h
i ðkÞ :UðkÞ , R = autocorrelation matrix
=E UTðkÞ :UðkÞ , E is the expected value, UðkÞ is the unit voltage vector for kth iteration and UTðkÞ is the transpose of unit
voltage vector for kth iteration. If eigen-values of the network
matrix ðI h:RÞ falls within unit-circle, then we can say that
the system has conversed. Thus, it can be written that
jeigðI h:RÞj = jeigð1 h:gi Þj\1
ð25Þ
where gi (i=1,2, ..) indicates eigen-values of
autocorrelation-matrix R. As gi . 0, ð1 h:gi Þ\1, therefore,
convergence criterion is derived as 0\h\1=gmax . The
6
Transactions of the Institute of Measurement and Control 00(0)
Table 2. System parameter specification.
System Parameters
Values
System parameters
Values
Series module
Parallel module
VDC gains (Kp, Ki)
VAC gains (Kp, Ki)
Filter RL
Detuned-LC
5
66
0.3, 2.5
0.9, 1
1mO, 5.6mH
2e3 (QL), 55e3(Qc)
DC-link & AC-ref voltage
Transformer R and L
MPPT sw. frequency
Current controller sw. frequency
Grid voltage and frequency
Convergence factor
600V & 20kV
0.006O, 0.02H
5kHz
5kHz
22kV & 50Hz
0.008
convergence factor ðhÞ has one more significance, which is
the controller stability. For a time-unaltered system, the proposed adaptive controller will converge to the mean square
error if, and only if, the following criterion is fulfilled
0\h\
1
3:trace½R
ð26Þ
P
where, trace½R= ðdiagonal elements of RÞ. Using proper
value of h, the proposed controller converges the disturbances
in error function and sets it to a minimum global value, W .
Thus, the expected value for steady-state criteria of the proposed algorithm can be derived as below. The solution for the
equation (28) establishes the stability criteria of the controller
and is solved in equation (29)
E½Wðk + 1Þ = ðI h:RÞ:E½WðkÞ + h:R
ð27Þ
E½Wss = ðI h:RÞ:E½Wss + h:h
ð28Þ
E½Wss = R1 :h = W*
ð29Þ
Results and discussion
To understand the importance of cumulative action of the
proposed enhanced controller and detuned-LC filtering circuitry in grid-tied DG-PV interfaced VSC controlled power
system, demonstrated in Figure 1 and designed in MATLAB/
Simulink environment is analyzed under various system perturbance. System specifications are listed in Table II. A comparative performance analysis in between the proposed
enhanced adaptive controller and the conventional one has
also been carried out and established below.
Evaluation under varying irradiance with transient
loads
Non-linear loads are the prime component for introducing
current harmonics in power systems. Testing of the proposed
enhanced controller’s performances under varying loads and
varying irradiance is the most practical case to check controllers’ robustness and its acceptance level. A varying irradiation
level from 1000W/m2 to 700W/m2 during t=0.5 s to t=0.7 s
and a varying load from linear (5kW & 1kVAr) to linear+ non-linear loads (3-phase rectifier induced inductive load
with resistances and inductances of 25O & L=250mH,
respectively) are taken into consideration for testing purpose.
The DC-Link voltage is maintained at 600V for both the controllers and is seen with a dip during the deviation in irradiation level shown in Figure 4a. Both the d-axis and q-axis
references are exposed in Figure 4b. During the addition of
non-linear loads to linear loads from t=0.7 sec to t=0.75 sec,
it is observed that the proposed controller performs superior
than the conventional one to annul the harmonic contents
inspite of introducing 20% of total harmonics. It is wavy and
unbalanced in case of conventional controller, as observed
from the comparative diagrams, depicted in Figures 4c-d. The
real and reactive powers supplied by the DG-PV, consumed
by the loads and delivered to the utility grid are depicted in
Figures 4e–f. The proposed enhanced adaptive current controller has turned out irresistible in supplying good quality of
current to utility grid with a total harmonic distortion (THD)
level of 1.54% whereas it is 3.31% with conventional controller, shown in Figure 3g and in Table 3.
Evaluation under Single L-G fault at PCC
Under this section, a single L-G fault is made to happen in
phase-a at PCC through a fault impedance Zf (Rg=0.01O &
Ron=0.001O). This fault lasts for a time period of t=0.5-0.6
s. In the meantime, high amplitude faulted current striking
phase-a can be witnessed. Accordingly, behavior of DC-Link
voltage, filtered inverter current and grid current for both the
proposed and conventional controllers are observed in Figure
5a and Figures 5c–d, respectively. It is witnessed that conventional controller fails to generate balanced and sinusoidal
waveforms whereas with the addition of Zt to weight updating process, the proposed controller could shape all the current output waveforms as sinusoidal and balanced one. The
performances of both the controllers are witnessed from the
perfect tracking of d-axis and q-axis references, presented in
Figure 5b. A comparative result for the real and reactive
power exchanges and THD calculations of currents measured
at three different power zones are demonstrated in Figures
5e–g, respectively.
Evaluation under voltage sag
In order to justify the control as well as system performances,
few grid side disturbances such as voltage sag due to overloading, source voltage harmonics due to the presence of
transformers or non-linear devices and variation in system
frequency due to the difference in active powers should be
considered. During a voltage sag, initiated at t=0.5-0.6 s,
Patowary et al.
7
Figure 4. Comparative system dynamic performances under transient loads and varying irradiance: (a) tracking of DC-Link voltage (Volt), (b) d-axis
(Id) & q-axis (Iq) ref. (A (c) ph-a filtered inverter (A), (d) phase-a injected grid current (A), (e) exchange of real power (kW), (f) exchange of reactive
power (kVAr), (g) %THD of current measured at inv-filter-end, load-end and PCC-end (left to right).
corresponding increase in filtered inverter current and grid
current are observed and plotted in Figures 6c–d. Parallely,
an increase in the voltage Vdc from t=0.5-0.6sec is witnesed
in Figure 6a. It is observed that the Vdc takes approximately
2 s to get stabilize to its reference point once the sag in is
over. The effect of volatge sag is also seen in both d-axis and
q-axis references, revealed in Figure 6b. The d-axis and q-axis
power exchanges in between DG-PV, load and utility grid are
presented in Figures 6e–f. The THD study of inverted-filtered
current, load and grid currents are presented in Figure 6b.
Hence, it is witnessed that the proposed controller along with
detuned-LC filter can mitigate odd-order harmonics to a
8
Transactions of the Institute of Measurement and Control 00(0)
Table 3. THD analysis of current waveforms at different power zones for conventional and enhanced current controllers under various power
scenarios.
Case study
Constant irradiation with RL load
Varying irradiance with transient loads
(linear to non-linear)
Single L-G fault at PCC
Grid voltage distortion
Voltage sag
Frequency deviation
Current controller
Conventional
Enhanced
Conventional
Enhanced
Conventional
Enhanced
Conventional
Enhanced
Conventional
Enhanced
Conventional
Enhanced
large extend as compared with the conventional controller
and thus it achieves acceptable system performances in gridtied DG-PV application.
It is observed that with an extended design steps (Zt) for
active or reactive power components in the control design
aspects, low-order current deformation for the currents waveforms measured at different power zones can be eliminated
even under polluted grid condition, thus fulfilling the IEEE519 standards. In Table 3, an analysis on THD for three different currents measured at three different power zones is
recorded for both the enhanced and conventional adaptive
linear current controllers. It can be summarized that the ability to annul the transient disturbances and the possibility of
mitigating the low-order current harmonics are well witnessed
in the proposed control scheme in comparison to the conventional one.
Hardware results
To verify system performances and robustness of the proposed control scheme, a prototype model has been set-up
and presented in Figure 7 with hardware parameters tabulated in Table 4. The prototype model is comprised of an
inverter power module (IPM), which is coupled in parallel
to the local 3-phase linear or non-linear loads through the
detuned-LC filters. The input to the IPM is a firm DC supply achieved by a combination of 3-phase supply with a rectifier circuit through an auto-transformer to emulate the
characteristics of a DG-PV system. One more 3-phase supply is asserted to grant supply to grid-side linear loads using
an auto-transformer, as shown in Figure 7. dSPACE RTI1202 kit is used to interface the hardware parts to the software part to validate the proposed controller functioning
that is implemented in Matlab/Simulink software. Extra
hardware apparatus of the prototype model includes halleffect voltage and current (LV25-P and HE025T01) sensors,
3-phase linear/non-linear PCC and local loads, one MCB of
16A (performing as synchronizing switch), two power analyzers (Fluke-made), a Tektronix mixed domain oscilloscope
%THD of current measured at
Inv.-filter-end
Load-end
PCC-end
2.77
0.66
3.47
1.99
3.62
1.55
3.63
1.85
3.50
1.81
2.37
1.85
1.38
0.84
20.10
20.05
6.21
5.25
3.34
2.76
2.76
2.53
5.00
3.05
2.61
0.58
3.31
1.54
3.05
1.14
2.14
1.45
2.99
1.74
2.17
1.70
(MDO3024) and a KEYSIGHT mixed signal oscilloscope
(MSOX2002A, 70MHz, 2GSa/s), which are being used to
analyze and trace the performance of the prototype. Ten
hall-effect sensors are occupied to take out the real-time
feedback signals essential for the proposed controller’s function, which are 3-phase grid-side voltages/currents, 3-phase
load currents and the DC-Link voltage. Those feedback signals are inserted to the proposed controller through an analog IOs (AIOs) of dSPACE Microlab box. Six digital I/Os
(DIOs) of Microlab box are applied to bring-back the produced 6-pulses to the IPM module with a triangular carrier
of 5kHz and a dead-zone time span of 3ms.
Proposed controller performances
The assessment of the proposed control scheme has been carried
out in an islanded mode with the subsequent variations in loads.
The real-time analog feedback signals collected from the voltage/
current sensors, which act as different inputs to the proposed controller, are depicted in Figures 8a–d. This represents the screen
capture of the oscilloscope (MDO3024), which monitors the 3phase grid voltages (Vgabc) and grid currents (Igabc), 3-phase load
currents (ILabc) and DC-Link voltage (Vdc). The controller performances are defensible with the hardware results measured for
three phase reference signals (Iref_abc), phase-a switching pulse,
inverter output line voltage (Vinv_ab) and line current (Iinv_ab),
demonstrated in Figures 9a–c.
System performances with transient linear loads
The step changes in local loads of rating 5A is functional on
the model to examine and validate the performance of the
proposed control scheme in an off-grid mode in order to stabilize load voltage to its rated value. Primarily, a fixed linear
(resistive) load of 2A is applied to the model and the corresponding phase-a load line voltage (the top waveform in
zoomed scale) and load line current (purple colored waveform) consumption are shown in Figure 10a. In Figure 10b,
phase-a supplied load line voltage (the bottom waveform in
Patowary et al.
9
Figure 5. Comparative system dynamic performances under single L-G fault at PCC: (a) tracking of DC-Link voltage (Volt), (b) d-axis (Id) & q-axis
(Iq) ref. (A), (c) ph-a filtered inverter (A), (d) phase-a injected grid current (A), (e) exchange of real power (kW), (f) exchange of reactive power
(kVAr), (g) %THD of current measured at inv-filter-end, load-end and PCC-end (left to right).
zoomed scale) and load line current (the bottom waveform in
zoomed scale) for a step changes in load from 1A to 2A and
then to 3A are shown are depicted. The THD of the supplied
load current with this load is revealed in Figure 10c. It is
experimented so that the load gets unbiased and sinusoidal
voltages/currents irrespective of the load characteristics and
hence it shows functional robustness of the proposed
enhanced control scheme.
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Transactions of the Institute of Measurement and Control 00(0)
Figure 6. Comparative system dynamic performances voltage sag: (a) tracking of DC-Link voltage (Volt), (b) d-axis (Id) & q-axis (Iq) ref. (A), (c) ph-a
filtered inverter (A), (d) phase-a injected grid current (A), (e) exchange of real power (kW), (f) exchange of reactive power (kVAr), (g) %THD of
current measured at inv-filter-end, load-end and PCC-end (left to right).
System performances with transient non-linear loads
The next set of experimental analysis utilizes a 3-phase fullycontrolled bridge rectifier with linear loads (R=25O and
L=25mH) to justify the proposed controller performances in
off-grid mode. The experimental results depicts satisfactory
performance of the enhanced control scheme under transient
non-linear loads also. The overall model is approved for
unbiased and sinusoidal load voltage/current for both
Patowary et al.
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Table 4. Design data for laboratory-based hardware setup.
Parameters
Values
Parameters
Values
DC-link voltage
VDC (Kp , Ki )
VAC (Kp , Ki )
RL Filter
50V
0.3, 1.13
0.9, 1.02
1mO, 3mH
AC-ref.
Current controller sw. frequency
Grid frequency
Detuned-LC
70V
5kHz
50Hz
2mH, 4uF
Figure 7. Prototype setup (a) functional diagram and (b) real-time interface with dSPACE RTI-1202.
Figure 8. Feedback signals: (a) unbiased 3-phase grid voltages Vgabc (20V/div), (b) unbiased 3-phase grid currents Igabc (2V/div ), (c) unbiased 3-phase
load currents ILabc (2V/div ), (d) DC-Link voltage Vdc (50V/div).
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Transactions of the Institute of Measurement and Control 00(0)
Figure 9. Proposed control scheme performances : (a) 3-phase reference signals Iref_abc (1V/div), (b) switching pulses of phase-a (2V/div), (c) VSC
output line voltage for phase-ab Vinv_ab (25V/div ), (d) VSC output line current for phase-ab Iinv_ab (2V/div).
Figure 10. Load voltage (top waveform in zoomed scale, 10V/div) and load current (bottom waveform in zoomed scale, 1V/div) for phase a under:
(a) constant linear loads, (b) varying loads (linear to linear), (c) THD of load current under linear loads.
Patowary et al.
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Figure 11. Load voltage (top waveform in zoomed scale, 10V/div) and load current (bottom waveform in zoomed scale, 1V/div) for phase a under:
(a) constant non-linear loads, (b) varying loads (linear to linear + non-linear), (c) THD of load current under non-linear loads.
constant non-linear load as well as for load transition from
linear to non-linear, pragmatic in Figure 11a–b. This verifies
the sound operation of the proposed enhanced adaptive controller along with detuned-LC filter under diverse real-time in
service phenomenon. THD of the load current shown in
Figure 11b is displayed in Figure 11c and found satisfactory.
Conclusion
As the current harmonic compensation capability is not significant using conventional linear current control techniques,
there is a recent research focus in designing an enhanced adaptive current controller by considering a few field problems. A
grid-tied PV interfacing VSC controlled system with detunedLC filter circuitry is modeled via MATLAB/Simulink and
analyzed under various operating scenarios. The proposed
controller is designed in view of a few practical cause and
effects that can exhibit robust operation under various operating scenarios so that a probable solution can be figured out
easily by the field engineers. The results thus found establishing sound control scheme with an accurate, faster and robust
control mechanism. During estimation, introduction of Zt in
the weight updating process yields generation of accurate reference signals under any system perturbation that will
ultimately deliver accurate on-off time periods of IGBT
switches. Thus, PQ is maintained at different power zones.
Stability and convergence criterion for the proposed controller are also derived. The comparative performance assessment
using enhanced and conventional controller is also presented
and it is endorsed with the competency of the proposed control scheme in terms of THD under assorted system dynamics.
Hardware results establish acceptable performance of the proposed control scheme and henceforth it justifies the deployment of the proposed cumulative control scheme real-time
application.
Declaration of conflicting interest
The authors declare that there is no conflict of interest.
Funding
This research received no specific grant from any funding
agency in the public, commercial, or not-for-profit sectors.
ORCID iD
Moushumi Patowary
007
https://orcid.org/0000-0001-6166-6
14
Transactions of the Institute of Measurement and Control 00(0)
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