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Improved SMS islanding detection method for grid-connected converters
Article  in  IET Renewable Power Generation · February 2010
DOI: 10.1049/iet-rpg.2009.0019 · Source: IEEE Xplore
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Published in IET Renewable Power Generation
Received on 1st March 2009
Revised on 12th June 2009
doi: 10.1049/iet-rpg.2009.0019
ISSN 1752-1416
Improved SMS islanding detection method for
grid-connected converters
F. Liu Y. Kang Y. Zhang S. Duan X. Lin
College of Electrical & Electronic Engineering, Huazhong University of Science & Technology, Wuhan 430074,
People’s Republic of China
E-mail: fangruihust@163.com
Abstract: Islanding detection is a mandatory function for grid-connected converters. The popular slip mode
frequency shift (SMS) and auto phase shift active islanding detection methods are investigated and an
improved (IM)-SMS strategy is proposed in this study. In the proposed method, additional phase shift is
introduced to help in stimulating the action of the islanding detection and the algorithm is simplified as well.
When the utility grid is disconnected, the algorithm keeps the frequency of the converter output voltage
deviating until the frequency protection relay is triggered. The working principle of the method is introduced
and the guidance of parameters selection and optimisation is also provided. The islanding detection
performance is evaluated through theoretical analysis and verified by digital simulation and experimental
results. The IM-SMS method exhibits features of simplicity, easy implementation and high reliability.
1 Introduction
Owing to the increasing energy consumption around the
world and the eminent exhaustion of fossil energy
resources, more attention can be noticed on the renewable
energy resources such as solar power, wind power and fuel
cell. They are usually utilised to generate electric power and
transferred to utility grid through grid-connected
converters. And such converters are required to present an
effective islanding detection function for protection purpose
[1–9]. Islanding phenomena of grid-connected converters
refer to their independent operation when the utility is
disconnected. The local section is isolated from the power
system but still energised by the converters [1]. It causes a
number of undesirable effects, such as the danger to utility
maintenance personnel and equipment malfunction [3].
In the recent years, a large number of islanding detection
methods have been developed [3–9]. These algorithms can
be classified into two major approaches: passive and active.
The passive islanding approach mainly detects the voltage
abnormality at the point of common coupling (PCC)
including frequency, phase shift and harmonics to identify
an islanding [3, 7]. An over voltage relay, an under voltage
relay, an over frequency relay (OFR) and an under
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frequency relay enable the grid-connected converter the
basic islanding detection capability. Althoughthis method
is simple, the relays failed to detect the islanding when the
converter output power closely matches with the connected
loads. Considerable phase difference is expected for the
phase jump detection method to identify an islanding.
However, this method fails when the load power factor is
unity [1]. Owing to the presence of non-linear load, it is
nearly impossible to select an appropriate harmonic
threshold for the voltage harmonic detection method. Such
method is shown to be impractical [3].
The basic under/over voltage, under/over frequency and
phase jump passive islanding detection methods usually
suffer comparatively large none detection zone (NDZ),
which is well evaluated in [4] with power mismatch space
(DP against DQ).
In order to improve the islanding detection capability, the
active methods have been developed. These methods
introduce perturbations into the converters’ output.
Additional current harmonics besides the intrinsic ones [10]
may be generated. The power quality was inevitably
degraded. Therefore the NDZ of the active methods should
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doi: 10.1049/iet-rpg.2009.0019
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be well reduced and the influence on power quality should be
as low as possible [3].
Among all the active detection techniques, active
frequency drift with positive feedback (AFDPF) method
[3, 5, 6] is an effective way to detect the islanding by
forcing the frequency of PCC voltage to drift up or down.
However, zero intervals usually exist in the converter output
current waveforms, resulting in a lower output power
quality. Slip mode frequency shift (SMS) method alleviates
such problem by introducing phase shift perturbation [3, 6,
11]. An additional problem with SMS method is that it
relies on an uncontrollable, externally supplied perturbation
[3] to trigger the action of the algorithm. The islanding
may not be detected within the specified time (e.g. IEEE
Std 929-2000 [1]). By introducing an initial value in the
phase shift perturbation, auto phase shift (APS) detection
method well solved this problem [12]. However, several
parameters are presented in the phase shift algorithm,
contributing to the parameters selection and optimisation
problems. Both reactive power and active power
perturbations are employed in [13] to provide a robust way
for islanding detection, while degradation in the converter
output quality is inevitably exacerbated. Although grid
impedance detection strategy [14] provides an effective
solution, it has a high requirement for hardware to
implement the algorithm.
In this paper, both SMS and APS methods are
investigated and an improved (IM)-SMS method is
proposed. The working principle of the strategy is
introduced and the parameters selection guidance is also
provided. The islanding detection performance is evaluated
through theoretical analysis, digital simulation and
experiment. The IM-SMS method exhibits features of
simplicity, easy implementation and high reliability.
2 Analysis of SMS and APS
methods
In the SMS method, the phase angle of grid-connected
converter output current is controlled as a function of the
PCC voltage frequency. The converter output current can
be expressed as [3]
iCON ¼ I sin(2pft þ uSMS) (1)
where f is the PCC voltage frequency and uSMS is the phase
angle for SMS method. This phase angle is set as a sinusoidal
function of the grid nominal frequency fg
uSMS ¼
2p
360
um sin
p
2
f � fg
fm � fg
 !
(2)
where um is the maximum phase angle in degrees and fm is
the frequency at which um occurs.
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From (2), uSMS is almost zero when the utility frequency
is at its rated value. Once the grid is disconnected, the
SMS algorithm is solely stimulated by an uncontrollable,
externally supplied perturbation caused by noise,
measurement inaccuracy and quantisation errors in practice
[3]. If such perturbation is small enough, this method may
fail to detect the islanding within the time specified by
IEEE Std 929-2000.
APS method solves such problem by introducing an initial
value to the phase angle uAPS as (3) [12]. A permanent phase
perturbation is therefore existing in the converter output
current
uAPS[k] ¼
1
a
f [k� 1]� 50
50
� �
360o þ u0[k] (3)
where a is a constant and f [k 2 1] is the measured PCC
voltage frequency in the previous cycle. u0[k] is the
additional phase shift and can be expresses as
u0[k] ¼ u0[k� 1]þ Du sign(Df ) (4)
where Du is a constant and sign(Df ) is determined by the
PCC voltage frequency of the previous two cycles as
sign(Df ) ¼
1, f [k� 1] . f [k� 2]
0, f [k� 1] ¼ f [k� 2]
�1, f [k� 1] , f [k� 2]
8<
: (5)
Owing to the additional phase shift, the islanding detection
speed is accelerated, while large phase shift perturbations
are introduced in the converter output current. Moreover,
the APS algorithm has difficulties to select and optimise
the parameters.
3 IM-SMS islanding method
In order to overcome the disadvantages of the SMS and APS
methods, the IM-SMS islanding detection strategy with a
simplified phase shift is proposed as
uIM-SMS ¼ n(f � fg)þ F (f � fg)u0 (6)
where n and u0 are constants and F( f 2 fg) is defined as the
sign of the frequency error
F (f � fg) ¼
1, f � fg
�1, f , fg
�
(7)
Compared with (2), additional phase shift F( f 2 fg)u0 is
introduced in the IM-SMS algorithm. When the grid
frequency is at its nominal value fg, the additional phase
shift still exists and helps to stimulate the frequency
positive feedback. Therefore the reliability of this islanding
detection method is improved. As the current noise and
harmonics and measure inaccuracy can also contribute to
the perturbation in islanding detection, only a small value
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of coefficient u0 can serve this purpose. Moreover, the
algorithm is simplified comparing with (2) and (3) and can
be easily implemented into the digital signal processor.
It is worth mentioning that although the proposed IM-
SMS algorithm mimics that of AFDPF [3], IM-SMS
exhibits severe advantages over AFDPF. IM-SMS injects
disturbances in the converter output current phase. The
difference between two consecutive frequencies of the
utility line is usually small. From (6), the phase angle
during consecutive voltage cycles changes little no matter
how much the frequency deviates from its nominal value.
The current distortion introduced by IM-SMS is therefore
pretty small. However, the converter output current is
always discontinuous with AFDPF.
When the utility is disconnected, the phase difference
between the converter output voltage and current is
determined by the load. A parallel RLC load is usually
employed to investigate the islanding detection [1] and the
corresponding phase angle of the current leading the
voltage can be expressed as [15, 16]
uload ¼ tan
�1 R vC �
1
vL
� �� �
¼ tan�1 Qf
f
f0
�
f0
f
� �� �
(8)
where Qf and f0 are the RLC load quality factor and resonant
frequency, respectively. The quality factor Qf in a parallel
RLC circuit can be defined as [1]
Qf ¼ R
ffiffiffiffi
C
L
r
(9)
Fig. 1 shows the SMS and IM-SMS frequency response and
the load phase response as frequency changes.
The load is assumed to have a resonant frequency as the
grid frequency. The intersections between the load phase
curve and the SMS response are indicated by A, B and
C. It can be seen that point C besides A and B may be a
possible stable operating point. With the introduction of
additional phase shift F( f 2 fg)u0, the potential stable
operating point C can be eliminated for the IM-SMS
Figure 1 SMS, IM-SMS and parallel RLC load phase
response curves
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algorithm. Furthermore, the algorithm is well simplified for
analysis and implementation.
The aim of IM-SMS algorithm is to ensure no stable
operation point inside the frequency threshold once the
utility is disconnected. Therefore the phase angle of the
converter should increase faster than the angle of
the parallel RLC load with resonant frequency around the
utility frequency to make sure that the IM-SMS method
could work successfully at such worst case [15, 16]. Thus,
the following equation has to be guaranteed for f ¼ f0 ¼ fg
duload
df
����
f ¼f0
�
duIM-SMS
df
����
f ¼fg
(10)
Neglecting the additional phase shift and substituting (6) and
(8) into (10), the following equation can be obtained
n �
360Qf
pfg
(11)
According to [1], Qf � 2.5 appears to cover all reasonable
distribution line configurations. Qf ¼ 2.5 is therefore
substituted in (11), n can be chosen as 6.
The load parameter space [16] based on the values of the
quality factor and resonant frequency of the local load (Qf
against f0) was utilised to evaluate the NDZ of the improved
SMS method, and the relationship between resonant
frequency and islanding frequency fIS was governed by
f0 ¼
fis
2Qf
� tan uinv(fis)þ
ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi
tan2 uinv(fis)þ 4Q
2
f
q� �
(12)
where uinv is the phase angle between the converter current and
voltage (leading).
Substituting the frequency protection threshold
(50 + 0.5 Hz) and (6) into (12), the NDZ can be
described by Fig. 2 without considering u0. The area
within the curves is the NDZ. It can be seen that the
NDZ is reduced as parameter n increases. The phase angle
between converter output current and voltage is increased
as well, resulting in larger perturbations. The load quality
factor is generally less than 2.5 [1] and the proposed
method theoretically has no NDZ with n ¼ 6.
Equation (10) provides a basic parameter selection
principle for the IM-SMS algorithm. It is worth
mentioning that further improved SMS can be developed
with such rule. The trace of IM-SMS2 in Fig. 1 shows a
piecewise slope islanding detection algorithm. A smaller
slope (n) but still with satisfaction of (10) is chosen to
reduce the influence on the converter’s output power
quality, whereas a bigger slope can be assigned once the
system frequency beyond a certain range but still within the
protection limit to accelerate the detection speed.
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If more than one converter operating in parallel, all
equipped with IM-SMS but with different values of n and
u0, the algorithm would also work. The phase angle of
each converter output current is only dependent on the
frequency of PCC voltage. It is known that the sum of
sinusoids with same frequency but different angles is also a
sinusoid, while the frequency remains unchanged with an
effective phase angle as the result [12]. Owing to the same
PCC voltage, the frequency positive feedback will keep this
effective phase angle deviating.
4 Simulation and experimental
results
To illustrate the design feasibility of the proposed IM-SMS
islanding method, a MATLAB/SIMULINK model for the
Figure 2 NDZ of the IM-SMS method
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grid-connected converter system is developed to perform a
digital simulation and verify the effectiveness of the proposed
IM-SMS method. The simulation diagram is shown in
Fig. 3 and the system specifications are listed in Table 1.
The PCC voltage is measured to obtain the frequency
which will be used for synchronisation and phase
perturbation calculation. In the SMS method, the phase
perturbation is realised by (2) with a trigonometric
operation, whereas the phase shift calculation is achieved by
(6) with a simple algebraic operation in the IM-SMS
method. This phase perturbation is then substituted into
(1) to obtain the reference current.
When the converter output equals the power demand of
a local parallel RLC load with quality factor of 2.5 and
resonant frequency of 50 Hz, the system typical waveforms
with the proposed islanding detection method are shown in
Fig. 4. The utility grid is disconnected at 0.1 s. It can be
seen that the voltage frequency exceeds the upper limit
(50.5 Hz) at 0.3 s and the gating signal is therefore disabled.
Under the same working conditions, the system waveforms
with the SMS islanding detection method are shown in
Fig. 5. From (2), the perturbation is pretty small, resulting
in a low detection speed. The frequency changes less than
0.1 Hz in 0.2 s, resulting in a pretty lower detection speed.
Comparing Fig. 4 with Fig. 5, because of the additional
phase shift in the IM-SMS method, the frequency positive
feedback is reliably triggered and the islanding can be
quickly identified.
The islanding detection ability of the IM-SMS algorithm
is also examined for two converters operating in parallel. Both
Figure 3 MATLAB/SIMULINK model of a single phase grid-connected converter
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converters are operated in the current control mode [17, 18]
and supply half of the active power that the local load
demands as shown in Fig. 6.
The parameter n is 6 in one converter and 7 in the other.
Although the phase shifts in both converters are different, the
total converter current is still sinusoids with same frequency.
The grid is disconnected in 0.1 s and the frequency can be
drifted out of the threshold within 0.16 s. The islanding
can be successfully identified and the detection process is
shown in Fig. 6.
The operation of the proposed islanding detection
algorithm has been verified by experiment as well. A local
parallel RLC load with L ¼ 48 mH and C ¼ 210 mF was
chosen for the islanding detection testing. The converter
output current command is set as 6.3 A. The resistor of the
local RLC load is tuned as 35 V to ensure the active power
match between the converter output and the local load
Table 1 System specifications for digital simulation
utility grid 220 V, 50 Hz
converter rated
power
3 kW
LC filter parameters 3 mH, 4.7 mF
frequency threshold 50.5 Hz (upper), 49.5 Hz (lower)
voltage threshold 242 V (upper), 193.6 V (lower)
SMS parameters um ¼ 108, fm ¼ 53 Hz
IM-SMS parameters n ¼ 6, u ¼ 0.58
local parallel RLC
load
R ¼ 16.1 V L ¼ 20.54 mH,
C ¼ 493 mF
Figure 4 Converter output voltage, current and frequency
with IM-SMS islanding detection method and a local
parallel RLC load (Qf ¼ 2.5, f0 ¼ 50 Hz)
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demand. The load quality factor is about 2.35 and the
islanding detection process is shown in Fig. 7. Owing to
the active power match, the PCC voltage changes little and
the islanding can be identified through the over frequency
protection within 0.24 s.
The local parallel load resonant frequency is known to
affect the islanding detection. The closer, the resonant
frequency approaches the grid frequency; the more difficult
to identify the islanding. In order to accurately acquire the
load resonant frequency, the active detection function and
frequency protection relays are disabled to measure the
islanding system frequency. The converter output voltage
and current waveforms, and the PCC voltage are shown in
Fig. 8 after the grid disconnection. The output of a DSP
I/O port after a RC filter is employed to indicate the
frequency. The islanded system frequency is 50.05 Hz.
Figure 5 Converter output voltage, current and frequency
with SMS islanding detection method and a local parallelRLC load (Qf ¼ 2.5, f0 ¼ 50 Hz)
Figure 6 Waveforms of two converters parallel operation
with IM-SMS islanding detection method
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The performance of the proposed algorithm is also
examined with higher quality factor load. The converter
output current is 5.7 A, the local resistive load is set as
40 V and the load quality factor is 2.54. The PCC voltage,
frequency and the converter current waveform are shown in
Fig. 9.
Owing to the closely match of the local load and the
converter output, there is little variation in the PCC
voltage magnitude after the grid disconnection. The
proposed method persistently perturbs the converter output
current phase angle to drift the system frequency out of the
limit. The system frequency (trace 3 of Fig. 9) can be seen
arising from 50 Hz (2 V) to 50. 5 Hz (3.3 V) and the OFR
is triggered. The islanding can be detected in 0.27 s. It
meets the requirement of 2 s specified by IEEE Std 929-
2000.
Figure 7 PCC voltage and the converter output current with
a local parallel RLC load (Qf ¼ 2.35, f0 ¼ 50.05 Hz)
Figure 8 Islanded system voltage (trace 1, 100 V/div),
current (trace 2, 10 A/div) and frequency (trace 3)
Renew. Power Gener., 2010, Vol. 4, Iss. 1, pp. 36–42
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5 Conclusion
In this paper, the working principle of the popular SMS and
APS active islanding detection methods are investigated and
the improved SMS method is proposed. Owing to the
introduction of additional phase shift, the frequency
positive feedback can be reliably triggered and the islanding
detection effectiveness is guaranteed in the proposed IM-
SMS strategy. Moreover, the phase shift angle is
accomplished with linearised frequency positive feedback.
The algorithm is simplified and can be easily implemented.
The working principle and the NDZ of the IM-SMS
method are analysed. The guidance of parameters selection
is provided as well. The feasibility and effectiveness of the
proposed algorithm is verified with theoretical analysis,
digital simulation and experimental results. The IM-SMS
method exhibits features of simplicity, easy implementation
and high reliability.
6 Acknowledgment
The authors acknowledge the financial support provided by
the National Basic Research Program of China with Grant
2009CB219701 for this paper.
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Figure 9 PCC voltage (trace 1, 100 V/div) and frequency
(trace 3) and the converter output current (trace 2, 10 A/
div) with a local parallel RLC load (Qf ¼ 2.54, f0 ¼ 50.05 Hz)
41
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IET Renew. Power Gener., 2010, Vol. 4, Iss. 1, pp. 36–42
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https://www.researchgate.net/publication/224100218