Detection and analysis of power quality disturbances under faulty conditions in electrical

INTERNATIONAL JOURNAL OF ELECTRICAL ENGINEERING
International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME
& TECHNOLOGY (IJEET)
ISSN 0976 – 6545(Print)
ISSN 0976 – 6553(Online)
Volume 4, Issue 2, March – April (2013), pp. 25-36
IJEET
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DETECTION AND ANALYSIS OF POWER QUALITY
DISTURBANCES UNDER FAULTY CONDITIONS IN ELECTRICAL
POWER SYSTEM

Devendra Mittal1, Om Prakash Mahela2, Rohit Jain3
1
Assistant Professor, Dept. of Electrical Engg., Jagannath University Jaipur, India
2
Graduate Student Member IEEE & Junior Engineer-I, RRVPNL, Jaipur, India
3
Professor, Department of Physics, JNIT, Jaipur, India

ABSTRACT

The electrical power of good quality is essential for proper operation of many
electronic equipment, power electronics based loads and microprocessor based controlled
loads. Malfunction of equipment may lead to loss of production or disruption of critical
services resulting in huge financial and other losses. The power quality disturbances decrease
the efficiency of power system equipments such as generators. Therefore the issue of power
quality is very important to both the consumers and the utility of electric power. There are
many facets of power quality disturbances and each has its own source and mitigation
techniques. The first step towards any solution for a disturbance is to recognize the presence
of a particular type of disturbance and locate its source. This paper deals with detection,
analysis and travel of power quality disturbances under faulty conditions in electrical power
system. A four bus system having two load and two generator buses is modeled in
MATLAB/Simulink environment. A fault is created near the load bus and power quality
disturbances are detected near the generator bus.

Keywords: power system, power quality, power system faults, power quality disturbance.

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1. INTRODUCTION

An electrical power system is expected to deliver undistorted sinusoidal rated voltage
and current continuously at rated frequency to the end users [1]. Poor quality of electric
power is normally caused by power line disturbances, such as impulses, notches, glitches,
momentary interruption wave faults, voltage sag, swell, harmonic distortion and flicker
resulting in misoperation or failure of end user equipment [2]. The meaning of power quality
is different in views of utility, equipment manufacturers, and customers. Utilities treat PQ
from the system reliability point of view. Equipment manufacturers, on other hand, consider
PQ as being that level of power supply allowing for proper operation of their equipment.
Customer considers good PQ that ensures the continuous running of processes. A number of
papers have been published during the last several years on detections and classification of
power quality disturbances. The approach of neural networks has been used by [3] for the
purpose of PQ disturbance detection. The use of continuous wavelet transform (CWT) to
analyse non-stationary harmonic distortion has been proposed by [4]. Studies on PQ
assessment by using a dynamic orthogonal wavelet were carried out by [5]. An improved
Hilbert-Huang method for analysis of time varying waveforms in power quality has been
proposed by [6]. The discrete wavelet transform and S-transform based neural classifier
scheme for time series data mining of power quality events occurring due to power signal
disturbances has been proposed by [7].
Most of papers published on power quality are concerned with the customer related
issues. This paper aims to detect power quality disturbances in the faulty conditions of the
power system. The four bus system with two load and two generator buses is simulated in
MATLAB/Simulink environment. The Power Quality disturbances are detected at generator
bus in the healthy condition and with LG fault, LL fault, LLG fault, LLL fault and LLLG
fault on the load bus. The results obtained after simulation demonstrate the nature of different
disturbances during faulty conditions in the power system.

2. POWER QUALITY DISTURBANCES IN POWER SYSTEM

The term power quality (PQ) is generally applied to a wide variety of electromagnetic
phenomena occurring within a power system network. Power quality is predominately a
customer issue [8]. The power quality problem can be defined as any problem manifested in
voltage, current or frequency deviations that result in failure or mal-operation of customer
equipment [9]. It covers several types of problems of electricity supply and power system
disturbances. According to IEEE standard 1159-1995 [10], the PQ disturbances include wide
range of PQ phenomena namely transient (impulsive and oscillatory), short duration
variations (interruption, sag and swell), power frequency variations, long duration variations
(harmonics, notch, flicker etc.) with time scale ranges from tens of nanoseconds to steady
state. Inigo Monedero et al. [11] presented a classification of PQ disturbances, which is given
in Table.I, based on the UNE standard in Spain which defines the ideal signal as a single-
phase sinusoidal voltage signal of 230 Vrms and 50 Hz. A number of causes of power quality
transients can be identified: lightning strokes, planned switching actions in the distribution or
transmission system, self-clearing faults or faults cleared by current limiting fuses, and the
switching of end-user equipment. Transient phenomena are extremely critical since they can
cause over voltages leading to insulation breakdown or flashover. These failures might trip
any protection device initiating a short interruption to the supplied power. Excess current

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produced by transients may lead to complete damage to system equipment during the
transient period. Moreover, if such disturbances are not mitigated, they can lead to failures or
malfunctions of various sensitive loads in power systems and may be very costly [12].

TABLE I
TYPES OF DISTURBANCES
Range
Type of
Disturbance subtype Time
disturbance Max.
Min. Value
Value
Slight deviation 49.5 Hz. 50.5 Hz.
Frequency 10 s
Severe deviation 47.0 Hz. 52.0 Hz.
Average voltage 10 min 0.85 Un 1.1 Un
Flicker - - 7%
Short 10ms-1s
Sag Long 1s-1min 0.1 U 0.9 U
Long-time disturbance >1min
Voltage
Short <3min
Under Voltage 0.99 U
Long >3min
Temporary Short 10ms-1s
Swel Temporary Long 1s-1min 1.5 KV
1.1 U
l Temporary Long-time >1min
Over-voltage <10 ms 6 KV
Harmonics and
Harmonics - THD>8%
other
information Included in other
signals Information signals -
disturbances

A lot of research works have been carried out in the classification of power quality
events and recognition and identification of power quality disturbances. A wavelet based
fuzzy reasoning approach to power quality disturbance recognition and identification has
been presented in [13]. Wavelet transform can be used in conjunction with Kalman filter for
online real time detection and classification of voltage events in power system [14]. Dash
P.K. et al. [15] used S-transform for detecting, localizing, and classifying PQ problems.
Haibo He et al. [16] proposed an energy difference of multi-resolution analysis (EDMRA)
method for power quality disturbances analysis. At each wavelet decomposition level, the
squared value of the detail information is calculated as their energy to construct the feature
vector for analysis. Following the criteria proposed in this paper, different kinds of power
quality disturbances can be detected, localized, and classified effectively.

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3. THE PROPOSED POWER SYSTEM MODEL

For detections of power quality disturbances during faulty conditions in the power
system, the one line diagram of experimental set up consisting of four buses is shown in Fig.
1. The buses 1 & 2 are taken as generator buses and buses 3 & 4 are taken as load buses. The
line length of all the four π sections are taken as 100 Km. For simplicity the voltage levels at
all points of the system are taken as 33 KV. The fault is located at bus no. 4 in all faulty
conditions considered in the study. All the measurement of the voltage signals are taken on
bus no. 1 at generating station.

Fig. 1 Proposed model of Power System for detection of PQ disturbances in faulty conditions

4. DETECTION AND ANALYSIS OF PQ DISTURBANCES IN FAULTY
CONDITIONS

In the power system, faults are abnormal events which are not part of normal
operation and unwanted by the network operator. After fault occurs in the power system, a
non-linear signal of transient travelling wave is generated and runs along faulted transmission
line to both ends of the line. Those travelling waves contain information about fault nature.
The fault initial travelling wave has a wide frequency spectrum from DC component to high
frequencies. When such fault travelling wave arrives at the substation bus bar, it will change
incisively, i.e. travelling wave head will present the sudden change in the time-frequency
diagram. In that way, travelling wave arrival to the measuring point (usually the busbar
voltage transformers) is exactly a moment of sudden change recorded on measuring
substation [17].
MATLAB is a user friendly software and used in many field for research. For
experimental detections of power quality disturbances during faulty conditions in the
proposed model of power system, the MATLAB simulation is performed in healthy
conditions as well as in faulty conditions.

4.1 Power System in Healthy Conditions

The power system model shown in Fig. 1 is simulated in MATLAB/Simulink
environment in healthy condition. The Voltage signal of phase-A and Fourier Signals on
phase-A are shown in Fig. 2 and Fig. 3 respectively. In healthy conditions the signals on all

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the three phases are similar. In healthy conditions the voltage in all the three phases are
identical. The symmetrical wave of 50Hz frequency is obtained. The fourier analysis of the
voltage signals also shows the symmetry in healthy conditions.

Fig. 2 Voltage signal on Phase-A in healthy condition at bus-1

Fig. 3 Fourier analysis of signal on Phase-A in healthy condition at bus-1

4.2 LG Fault on Power System

environment with line to ground fault at bus no. 4 on phase-A. The voltage signal of phase-A,
voltage signal of phase-B and Fourier Signals on Phase-A at bus no. 1 are shown in Fig. 4,
Fig. 5 and Fig. 6 respectively. The multiple voltage spikes of magnitude of the order 106 are
obtained on the faulty phase and that of 105 are obtained on the healthy phases. The presence
of multiple voltage spikes is also validated by the fourier analysis of signals.

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Fig. 4 Voltage signal on Phase-A at bus-1 with LG fault on phase-A at bus-4

Fig. 5 Voltage signal on Phase-B at bus-1 with LG fault on phase-A at bus-4

Fig. 6 Fourier analysis of signal on Phase-A at bus-1 with LG fault on phase-A at bus-4

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4.3 LL Fault on Power System

environment with double line (LL) fault at bus no. 4 on phases A & B. The voltage signal of
phase-A, voltage signal of phase-C and Fourier Signals on phase-A at bus no. 1 are shown in
Fig. 7, Fig. 8 and Fig. 9 respectively. The multiple voltage spikes of the magnitude of order
107 are detected on the faulty phases and voltage of power frequency is detected on the
healthy phases. The presence of multiple voltage spikes of high magnitude is confirmed by
the fourier analysis of voltage signal.

Fig. 7 Voltage signal on Phase-A at bus-1 with LL fault on phases A & B at bus-4

Fig. 8 Voltage signal on Phase-C at bus-1 with LL fault on phases A & B at bus-4

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Fig. 9 Fourier analysis of signal on Phase-A at bus-1 with LL fault on phases-A&B at bus-4

4.4 LLG Fault on Power System

environment with double line to ground (LLG) fault at bus no. 4 on phases A & B. The
voltage signal of phase-A, voltage signal of phase-C and Fourier Signals on Phase-A at bus
no. 1 are shown in Fig. 10, Fig. 11 and Fig. 12 respectively. The multiple voltage spikes of
the magnitude of order 108 are detected on the faulty phases and that of order of 107 is
detected on the healthy phase. The presence of multiple voltage spikes of high magnitude is
confirmed by the fourier analysis of voltage signal.

Fig. 10 Voltage signal on Phase-A at bus-1 with LLG fault on phases A & B at bus-4

32


Fig. 11 Voltage signal on Phase-C at bus-1 with LLG fault on phases A & B at bus-4

Fig. 12 Fourier analysis of signal on Phase-A at bus-1 with LLG fault on phases-A&B at
bus-4

4.5 LLL fault on Power System

environment with three phase (LLL) fault at bus no. 4. The voltage signal of phase-A and
Fourier Signals on phase-A at bus no. 1 are shown in Fig. 13, and Fig. 14 respectively. The
voltage swell is detected on all the phase voltages of the system. The presence of voltage
swell in the system voltage because of LLL fault on the system is confirmed by the fourier
analysis of voltage.

Fig. 13 Voltage signal on Phase-A at bus-1 with LLL fault bus-4

33


Fig. 14 Fourier analysis of signal on Phase-A at bus-1 with LLL fault at bus-4

4.6 LLLG Fault on Power System

environment with three phase fault including ground (LLLG) fault at bus no. 4. The voltage
signal of phase-A and Fourier Signals on phase-A at bus no. 1 are shown in Fig. 15, and Fig.
16 respectively. The multiple voltage spikes of high frequency persist for long time in case of
LLLG fault on the system. The magnitude of voltage spike is detected of the order of 106.
The presence of high frequency voltage swell is confirmed by the fourier analysis of voltage
signal.

Fig. 15 Voltage signal on Phase-A at bus-1 with LLLG fault bus-4

Fig. 16 Fourier analysis of signal on Phase-A at bus-1 with LLLG fault at bus-4

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5. CONCLUSION

An efficient but simple technique has been developed to detect the power quality
disturbances during faulty conditions in the electrical power system. The proposed model of the four
bus system is simulated in the MATLAB/Simulink environment. The results show the relative
severity of impacts of power quality disturbances during different types of faults on the power system.
The voltage spikes are detected in all types of unsymmetrical faults. The LL and LLG faults are more
severe and develop voltage spikes of high magnitude and frequency as compared to the LG fault. In
the symmetrical fault (LLL) condition voltage swell of high frequency is observed and voltage swells
are converted to the voltage spikes when ground is involved in LLLG fault conditions.

REFERENCES

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[14] Perez E., Barros J., “A proposal for on-line detection and classification of voltage events in
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International Journal of Electrical Engineering & Technology (IJEET), Volume 3,
Issue 1, 2012, pp. 79 - 87, ISSN Print : 0976-6545, ISSN Online: 0976-6553 Published
by IAEME.

BIOGRAPHIES

Devendra Mittal was born in Bhusawar in the Rajasthan state of India, on March
17, 1980. He studied at IET, Alwar, and received the electrical engineering degree
from Rajasthan University, Jaipur, in 2003. He received M.Tech.(Power system)
from MNIT, Jaipur, in 2007. He is currently pursuing Phd from Jagannath
University, Jaipur.
From 2003 to 2008, he was Lecturer with Shankara Institute of Technology,
Jaipur. From 2008 to 2009, he was Lecturer with UDML Engineering College. Since
2009, he has been Assistant Professor with Jagannath University, Jaipur, India. His special fields of
interest are, Power Electronics and Power System.

Om Prakash Mahela was born in Sabalpura (Kuchaman City) in the Rajasthan
state of India, on April 11, 1977. He studied at Govt. College of Engineering and
Technology (CTAE), Udaipur, and received the electrical engineering degree from
Maharana Pratap University of Agriculture and Technology (MPUAT), Udaipur,
India in 2002. He is currently pursuing M.Tech. (Power System) from Jagannath
University, Jaipur, India.
From 2002 to 2004, he was Assistant Professor with the RIET, Jaipur. Since
2004, he has been Junior Engineer-I with the Rajasthan Rajya Vidhyut Prasaran Nigam Ltd., Jaipur,
India. His special fields of interest are Transmission and Distribution (T&D) grid operations, Power
Electronics in Power System, Power Quality and Load Forecasting. He is an author of 18 International
Journals and Conference papers. He is a Graduate Student Member of IEEE. He is member of IEEE
Communications Society. He is Member of IEEE Power & Energy Society. Mr. Mahela is recipient of
University Rank certificate from MPUAT, Udaipur, India, in 2002.

Dr. Rohit Kumar Jain is Professor, Department of Physics, JaganNath Gupta
Institute of Engineering & Technology, Jaipur. He has an experience of teaching
engineering physics for more than 15 years. He received his Ph.D. degree from
University of Rajasthan Jaipur in the field of metallic glasses. He has more than 15
research publications in National and International journals. He has published two
books, Hand Book of Engineering Practical Physics-I & II from Vardhan Publisher
& Distributor, Jaipur and Engineering Physics, Vol. I & II from Vigyan & Takniki
Prakashan, Jaipur.

36

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