a hybrid algorithm for fast detection and classification of

EUROPEAN TRANSACTIONS ON ELECTRICAL POWEREuro. Trans. Electr. Power 2011; 21:555–564Published online 1 June 2010 in Wiley Online Library (wileyonlinelibrary.com). DOI: 10.1002/etep.461

A hybrid algorithm for fast detection and classification ofvoltage disturbances in electric power systems

*CyE-

Co

Edris Pouresmaeil1, Mudathir Funsho Akorede2*,y and Mojgan Hojabri3

1Center of Technological Innovation in Static Converters and Drives (CITCEA), Polytechnic University of

Catalonia, Barcelona, Spain2Electrical Engineering Department, University of Ilorin, Ilorin, Nigeria

3Electrical & Electronic Engineering Department, Universiti Putra Malaysia, UPM Serdang, Selangor,

Malaysia

SUMMARY

Tominimize the adverse impacts of power quality disturbances on the electric power supply as well as on thecustomer equipment, there is clearly a need for detection and classification of such problems. In this paper, afast detection algorithm for power quality disturbances is presented. The proposed method is a hybrid of twoalgorithms, abc–0dq transformation and 908 phase shift algorithms. The proposed algorithm is fast andreliable in detecting most voltage disturbances in power systems such as voltage sags, voltage swells,interrupts, flicker, harmonics, etc. In the proposed approach, the three-phase utility voltages are sensedseparately by each of the algorithms. These algorithms are combined to explore their individual strengths fora better performance. When a disturbance occurs, both algorithms work together to recognize this distortionand send trip signals to static transfer switches. This control method can be used for critical loads protectionin case of utility voltage distortion. Simulation and analysis results obtained in this study illustrate highperformance of the strategy in different single-phase and three-phase voltage distortions. Copyright# 2010John Wiley & Sons, Ltd.

keywords: power quality; voltage disturbance; detection algorithm; sag; swell; abc–0dq transformation

1. INTRODUCTION

Nowadays, the increasing number of nonlinear loads and power electronic devices of electric power

utility and customers are becoming sources of degradation to electric power quality [1]. These

appliances generate disturbances, in the form of impulsive transients, sags, swells, harmonic distortion,

interruptions, etc., in the power systems. These disturbances distort the electric supply waveforms that

should normally maintain a constant amplitude and frequency. Apart from the aforementioned devices,

power quality disturbances could also be caused by faults, especially short circuit faults, on the utility

system.

Electric power of good quality is essential for proper operation of many appliances, particularly

sensitive electronic equipment such as computers and digital relays. Malfunction of such equipment

caused by power quality disturbances, could lead to loss of production or disruption of critical services

resulting in huge financial and other losses. It is therefore necessary that critical loads be supplied with

electricity of acceptable quality. Recognition of the presence of any possible deviations from the ideal

sinusoidal voltage is the first step in combating this problem. To compensate for voltage disturbances in

power systems, the first step is to detect the disturbance itself most accurately to facilitate accurate

deployment of appropriate mitigation algorithm. The importance of this detection stage is very critical,

especially in cases of static transfer switches (STS), uninterruptible power supply (UPS), or where the

orrespondence to: Mudathir Funsho Akorede, Electrical Engineering Department, University of Ilorin, Ilorin, Nigeria.

mail: [email protected]

pyright # 2010 John Wiley & Sons, Ltd.

556 E. POURESMAEIL, M. F. AKOREDE AND M. HOJABRI

utility supply must be disconnected as part of compensation. Simulation results show that STS can

transfer critical loads from utility supply to ancillary supply within ¼ cycle, but critical loads can only

tolerate voltage disturbances for a maximum of ½ cycle [2]. However, bymeans of a fast algorithm, it is

possible to recognize voltage disturbances and send the trip signal to STS within less than ¼ cycles

after the disturbance. This would enable the critical loads, such as hospitals, telecommunication

companies, hotels, etc., to continue their operation without any interruption.

Several approaches have been reported on detection, localization and classification of voltage

distortions. Examples of these methods are the Fourier transforms [3], notch filter, or band pass filters

[4], p–q theory via the a� b transformation [5–7], synchronous reference frame methods [8,9],

extended phase-locked loop (PLL) methods [10,11] and wavelet transform algorithm [12–15]. Each of

these approaches could detect voltage disturbances, but then each has its drawbacks. For example,

Fourier transform and PLL are too slow in returning typical tracking information, and wavelet

transform usually returns results that can be difficult to interpret [16].

Further, the IEEE has proposed abc–0dq transformation algorithm as a voltage disturbance

recognizer. The most important advantage of this algorithm is its simplicity and its ability to detect

different voltage disturbances very quickly; however, this algorithm is unable to recognize balanced

three-phase voltage DC offset disturbance. Further, it takes a long time to recognize unbalanced

disturbances such as single-phase-to-earth fault [9]. Meanwhile, analysis of other algorithms’ results

show that 908 phase shift algorithm is able to detect balanced three-phase DC offset and many

unbalanced voltage disturbances very fast. Another important advantage of this algorithm is its ability

to recognize fault types and their characteristics [2]. Subsequently, by combining abc–0dq

transformation algorithm and 908 phase shift algorithm, a fast and accurate algorithm to recognize all

voltage disturbances and faults characteristics can be achieved. This explains the rationale behind the

proposed algorithm in this study.

The rest of this paper is structured as follows: a brief overview of abc–0dq transformation theory is

given in Section 2, while Section 3 presents the proposed detection algorithm. Section 4 is dedicated to

the evaluation of the algorithm. Simulation results are presented and discussed in Section 5, and the

conclusion to the paper is drawn in Section 6.

2. THE ABC–0DQ TRANSFORMATION THEORY

The abc–0dq transformation converts a three-phase signal, consisting of three different vectors into

two vectors in a two-dimensional frame of reference. The two axes are called the direct axis and the

quadrature axis. This theory is usually employed in the control of induction motors, known as field

orientated control (FOC). Here, the complex three-phase induction motor can be modelled as a DC

motor by performing simple transformations known as abc–0dq transformation [17].

Figure 1. abc–0dq Transformation.

Copyright # 2010 John Wiley & Sons, Ltd. Euro. Trans. Electr. Power 2011; 21:555–564DOI: 10.1002/etep

A HYBRID ALGORITHM FOR VOLTAGE DISTURBANCES 557

The relationship between abc and 0dq variables for the machine shown in Figure 1 were defined by

Park [18]. This relationship is given in Equation (1), and the voltage equivalent transformation is also

possible.

iabc ¼ ½P��1iodq (1)

where the transformation matrix

½P� ¼ffiffiffi2

3

r 1ffiffi2

p 1ffiffi2

p 1ffiffi2

p

cos u cos u � 2p3

� �cos u þ 2p

3

� �sin u sin u � 2p

3

� �sin u þ 2p

3

� �24

35 (2)

and u is the angle of the direct axis with respect to the a-phase – the reference axis.

Interestingly the q-axis is at an angle of 908 to the direct axis, and both are rotating with the same

angular velocity, v as the sinusoidal phase quantities.

3. THE PROPOSED ALGORITHM

Figure 2 shows the schematic block diagram of the proposed algorithm. With the aid of the control

circuit, the three-phase source voltage is continually monitored for any voltage disturbance detection.

The purpose of the control algorithm is to detect out of tolerance conditions and then issue a trip signal

to enable subsequent actions; compensation or disconnection. In cases where several voltage

disturbances are simultaneously present in the system, the proposed algorithm detects one based on its

amplitude and sends a trip signal to the switches which in turn disconnect the polluted source

immediately and switch the load to the backup power supply. This operation continues until normalcy

returns to the system, when the algorithm reverts the load back to the utility power supply.

Figure 3 illustrates the simulated block diagram of the proposed algorithm. In the figure, the utility

line input voltages (Va, Vb and Vc) are provided as inputs to both algorithms. The first algorithm is based

on the theory that allows a set of three-phase voltages to be represented as DC voltages in a d–q

synchronous rotating frame, as described in Section 2. In this case, the utility input voltages are sensed

and then converted to DC quantities in the d–q reference frame. Thus, any disturbance at the utility

input voltages will be reflected as disturbances in the d–q values. Similarly, by means of mathematical

equations in the second algorithm, the utility line voltages are converted to DC quantities, and

compared with reference line voltage (Vref), which is the nominal voltage of the supply source. These

comparisons give error signals shown as er, er1, er2 and er3 in Figure 3. These error signals pass through

low pass filters (LPFs) to eliminate unwanted transients (erd, erd1, erd2 and erd3) in the signals. The

comparison between erd and voltage tolerance etol issues a trip signal to enable subsequent actions.

When the disturbance begins, both algorithms are able to detect the voltage disturbance and send a trip

signal to their output at two different times. By means of an OR gate, only the first trip signal will be

given as the proposed algorithm’s output for rapid recognition of the voltage disturbance. Another

major advantage of this method is its ability to recognize fault type. This could be achieved bymeans of

908 phase shift algorithm. In addition, this hybrid control method can identify fault characteristics such

as amplitude and frequency.

Figure 2. The schematic block diagram of the proposed algorithm.


Figure 3. Simulated block diagram of the proposed algorithm.


4. ALGORITHM EVALUATION

When there is a fault in the system, all fault signals er1, er2 and er3 in Figure 3 are converted to constant

quantities after 90 electrical degrees shift (5milliseconds in 50Hz electrical systems), and depending

on fault types these signals are different from one another. Thus, by means of these three error signals,

it is possible to identify the fault type and its characteristics.

4.1. Single-phase-to-earth fault

Under normal operating conditions, the expressions in Equations (3)–(5) represent each single phase of

the utility three-phase line voltages:

Va ¼ V1 sinðvt þ ’Þ (3)

Vb ¼ V1 sinðvt þ ’þ 120Þ (4)

Vc ¼ V1 sinðvt þ ’� 120Þ (5)

On occurrence of a single-phase fault, Equations (3)–(5) transform to Equations (6)–(8),

respectively:

Va ¼V1ffiffiffi3

p sinðvt þ ’þ 150Þ (6)

Vb ¼ V1 sinðvt þ ’þ 120Þ (7)

Vc ¼V1ffiffiffi3

p sinðvt þ ’þ 90Þ (8)



From Figure 3, the 908 phase shift algorithm block diagram, when the fault is cleared before ¼

cycles (5milliseconds in 50Hz electrical systems), we have:

v1 ¼V1ffiffiffi3

p sinðvt þ ’� 150Þ sinðvt þ ’Þ þ V1 cos2ðvt þ ’Þ (9)

Then

er1 ¼ v1 � Vref ¼ V1

1

4þ 1

2cos2ðvt þ ’Þ þ 1

2ffiffiffi3

p cos2ðvt þ ’� 75Þ� �

(10)

If, however, the fault is cleared after ¼ cycles (5milliseconds in 50Hz electrical systems) then

Equation (11) can be obtained from Equation (9) as follows:

v1 ¼ � V1ffiffiffi3

p sinðvt þ ’� 150Þ sinðvt þ ’Þ � V1ffiffiffi3

p cosðvt þ ’� 150Þ cosðvt þ ’Þ (11)

Assuming vt ¼ p=2 and f ¼ 0, Equation (11) can be simplified as presented in Equation (12):

v1 ¼V1

2(12)

Similarly, Equation (13) is obtained from Equation (10):

er1 ¼V1

2� V1 ¼ �V1

2(13)

Also for Vb and Vc:

er2 ¼ 0 and er3 ¼ �V1

2(14)

In the same vein, fault types error signals can be calculated after ¼ cycles for other cases as presented

in Table I.

5. SIMULATION RESULTS AND DISCUSSION

5.1. Detection of voltage disturbances

The proposed algorithm is simulated in MATLAB/SIMULINK environment in order to detect various

power quality disturbances such as voltage sag, voltage swell, voltage interruption, voltage harmonic,

Table I. Error signals magnitudes in different short circuit situations.

Fault type er1

er2

er3

Single phase Phase a-n �V1=20 �V1=2

Phase b-n �V1=2V�1=2

0

Phase c-n 0 �V1=2�V1=2

Phase to phase Phase a and b �V1 �V1=4�V1=4

Phase b and c �V1=4�V1 �V1=4

Phase c and a �V1=4�V1=4

�V1

Phase to phase to earth Phase a and b–g �V1 �V1=2�V1=2

Phase b and c–g �V1=2�V1 �V1=2

Phase c and a–g �V1=2�V1=2

�V1

Voltage variety factor u for balanced faults (u� 1)V1 (u� 1)V1 (u� 1)V1

V1 is the amplitude of utility line voltage and u is voltage variety factor for balanced faults. For example, in a three-phase 30%voltage sag fault, u¼ 0.3.


0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.1-1

-0.8

-0.6

-0.4

-0.2

0

0.2

0.4

0.6

0.8

1

Time(sec)

Utility Line Voltage

Mag

nit

ude

(p.u

.)

Figure 4. Fifty per cent 3-’ sag on utility system.


voltage flicker and voltage DC offset. A phase-to-ground (Va–g) fault is initiated on phase a at

0.04 seconds and cleared after another 0.04 seconds in the utility line voltage. The results obtained

when applied to the proposed voltage disturbance detection algorithm are shown in Figure 4. Also,

Figure 5 shows the simulation results of the proposed voltage disturbance detectors. In the figure, 908phase shift algorithm detects a phase-to-ground fault in 0.0403 seconds with 0.0003 seconds time delay

while abc–0dq algorithm detects the same fault in 0.05439 seconds with a delay time of

0.01439 seconds. It could be observed that this time is more than ¼ cycles, whereas the proposed

algorithm shows only the minimum time delay in 0.0403 seconds to determine the instance of the

single-phase earth fault event. Figure 6 shows the error signals when a single-phase-to-earth fault on

phase a occurred on the three-phase utility line voltage. Considering Table I, error signals

er1¼ er3¼�0.5 pu, and er2¼ 0 pu, where V1 is equal to 1.0 pu. For other types of disturbances, error

signals can detect all voltage disturbances details and characteristics such as error amplitude and

frequency.

Figure 7(a) shows a single-phase utility voltage distorted by the fifth harmonic between 0.04 and

0.08 seconds applied to the proposed voltage disturbance detection algorithm. Simulation results in

Figure 7 shows 908 phase shift algorithm. As could be seen in the figure, (b) detects voltage harmonic

disturbance in 0.04253 seconds with 0.00253 seconds time delay and abc–0dq algorithm (c) detects the

same fault in 0.04087 seconds with 0.00087 seconds time delay, but the proposed algorithm (d) shows

only the minimum time delay of 0.04087 seconds to determine the instance of the voltage harmonic

disturbance event. Error signal (e) shows utility line voltage distorted by the 5th harmonic with 0.2 (pu)

Figure 5. Error signals for single-phase-to-earth faults (phase a–n–g).


Figure 6. Detection times of the voltage disturbance.


amplitude. The detection results of six disturbances are presented in Table II. From the table, it is seen

that there is very small time delay between real fault time and detection time.

It is equally observed in the figure that voltage flicker has two sets of detection times, because it

operates in both positive and negative tolerances. If it starts by positive tolerance, the abc–0dq

algorithm detects it faster than 908 phase shift algorithm, and vice versa if the flicker starts by the

negative tolerance. The worst case detection time for any disturbance is less than ¼ cycles.

5.2. Ride-through application for critical loads

The proposed detection algorithm is applied on a system with a critical load, as shown in Figure 8. The

figure demonstrates how a prompt detection of a voltage disturbance will switch the load supply from

0 0.02 0.04 0.06 0.08 0.1 0.12-2

0

2

Single-Phase Utility Line Voltage

(a)

0 0.02 0.04 0.06 0.08 0.1 0.120

0.5

1

X:0.04253(b)

0 0.02 0.04 0.06 0.08 0.1 0.120

0.5

1

X:0.04087

(c)

0 0.02 0.04 0.06 0.08 0.1 0.120

0.5

1

X:0.04087

(d)

0 0.02 0.04 0.06 0.08 0.1 0.12-0.2

0

0.2

Time (sec)

(e)

Figure 7. Detection times comparison of the algorithms: (a) single-phase voltage distorted by the fifthharmonic, (b) 908 phase shift algorithm, (c) abc–0dq algorithm, (d) proposed algorithm and (e) error signal.


Table II. Simulation results of begin/detection times of disturbances.

Disturbancetype

Begin time(seconds)

Detection time (seconds)

908 Phase shift algorithm abc–0dq Algorithm Proposed algorithm

Voltage sag 0.04 0.0403 0.04707 0.0403Voltage swell 0.04 0.04981 0.0404 0.0404Voltage interruption 0.04 0.0403 0.05439 0.0403Voltage harmonic 0.04 0.04253 0.04087 0.04087Voltage flicker 0.04 0.0403 0.04707 0.0403

0.04981 0.0404 0.0404Voltage DC offset 0.04 0.0453 0.0401 0.0401


the utility voltage source to the auxiliary voltage power supply via the proper operation of the solid

state switches labelled S1 and S2. Figure 9 shows harmonic distortion of voltage sag caused by

operation of an arc furnace – a nonlinear load – in a three-phase power system, while a

seamless transfer of the critical load voltages using the ride-through approach by the proposed

detection algorithm during a single-phase voltage sag on the same system could be appreciated in

Figure 10.

Figure 8. A ride-through application of the proposed algorithm.

0 0.02 0.04 0.06 0.08 0.1 0.12-1.5

-1

-0.5

0

0.5

1

1.5

Time (sec)

Utility Source Voltage

Mag

nit

ud

e (p

.u.)

Figure 9. Harmonic distortion in three-phase utility source voltage.


0.03 0.035 0.04 0.045 0.05 0.055 0.06-1.5

-1

-0.5

0

0.5

1

1.5

X: 0.04519

Y: 0.9982

Time (sec)

Total Time

Figure 10. Transfer of critical load to auxiliary source voltage.


6. CONCLUSION

This paper has presented a hybrid method for the detection and classification of various voltage

disturbances in power systems. The proposed algorithm combined abc–0dq transformation technique

and 908 phase shift method, thereby exploring the strengths of each of the techniques. The first

algorithm is based on the theory that allows a set of three-phase voltages to be represented as DC

voltages in a d–q synchronous rotating frame, while the second one converts utility line voltages to DC

quantity. This combination enables the resulting algorithm to be capable of mitigating voltage

disturbances, which are usually difficult to detect due to the extended variety of combinations in power

systems. The proposed algorithm, when tested with various simulations in MATLAB/SIMULINK,

demonstrated its capability to detect most voltage disturbances in power systems promptly

and accurately. Similarly, the approach was implemented on a ride-through system with

satisfactory results. Overall, the worst case detection time for voltage disturbances considered in

this study was obtained to be less than ¼ cycles (i.e. 5milliseconds in 50Hz electrical systems). The

additional advantage of the proposed method is its ability to recognize fault types and their

characteristics.

7. SYMBOLS AND ABBREVIATIONS

er :

Copyright

error signals

erd :
unwanted transient signals
etol :
voltage tolerance
LPF :
low pas filter
[P] :
transformation matrix
PLL :
phase-locked loop
S1, 2 :
switches
u :
voltage variety factor
Va,b,c :
a, b, c phase voltages
Vref :
reference voltage
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