OVERVIEW OF
POWER QUALITY ISSUES
[ By Offor Goodness (M.Eng) – Power Systems and Machines ]
1. Introduction
Distribution system is the third subsystem of power system network that distributes electric
power to consumer devices or loads. Distribution system can be classified into two;
primary and secondary systems, according to voltage levels. Primary Distribution system
receives bulk power from transmission subsystem and steps it down to 33kV by means of
stepped-down transformer. Further step-down to 11kV at secondary distribution
substation results in secondary distribution system (Theraja B. L. and Theraja B. K, 2005).
At any of the two levels of voltage, a step-down to 415/230V can be made to supply
consumer equipment. In power distribution system, equipment such as conductors,
transformers, switchgears etc serve the sole purpose of delivering power to consumer
loads. The load ranges from heavy machines and automation equipment such as electric
motors, programmable logic controllers (PLC) etc in industries to electronic and lighting
devices in homes and offices. Being large and complex, distribution system is prone to
reliability and power quality problems.
2. What is Power Quality?
Until early 20th century, the quality of power supply was not considered as important
factor in power delivery. Utility companies only focused on achieving a power delivery
state with little or no interruption. But with improvement in technology, paving way for
development of very sensitive loads, and coupled with customer awareness, power
system engineers were implored to consider power quality in electrical power delivery.
Power quality (PQ) as a term, defines a set of electrical boundaries within which a piece
of equipment can function as intended without significant loss of performance or life
expectancy (Sankaran C., 2002). It entails delivering electric power with minimal
distortions and therefore maintaining a near sinusoidal signal waveform at a frequency
of 50Hz and at required load voltage.
3. Power quality problems
Power quality problems are manifested in voltage, current or frequency (Zahir J. P.,
2011). Examples include: voltage swell and sag, voltage fluctuation, harmonic
distortions etc. Aside factors like power system faults, start up and shutdown of heavy
equipment, switching operations etc, non-linear loads are identified as major cause of
power quality problems (Joseph Seymour., 2011). Power quality problems, as global
issue exist in distribution systems of several countries including Nigeria, Lybia, India and
some developed countries. The effects of power quality problems are enormous; they
range from equipment failure to equipment damage.
The need to mitigate power quality problems and maintain power of good quality has
brought power system engineers, equipment manufacturers, researchers and statutory
bodies to a focal point of methodology development. Today, several methods are
developed to improve the quality of power to sustain the ever increasing applications of
sensitive and non-linear loads in distribution network. Conventionally, Synchronous
condenser, capacitor banks, static VAR compensators (SVCs), self-commutated VAR
compensators etc. are used to control reactive power and improve power factor, though
with drawbacks such as instability problems, generation of high transient during
connection and disconnection etc. (Irfan I. M., et al, 2013). More recently, Custom
power devices such as distribution static compensator (DSTATCOM), unified power
quality conditioner (UPQC), dynamic voltage restorer (DVR) etc are researched as better
methods for power quality improvement. However, their performance is dependent on
the type of controllers employed. Proportional integral (PI), proportional integral
differentiators (PID) etc are effective but slow in response and perform poorly under
parameter variations. Artificial intelligent (AI) controllers such as Artificial Neural
Network (ANN), fuzzy logic etc (Vinita V. R. et al, 2013) are proposed by researchers as
they offer better performance in terms of response time and operation under dynamic
loads.
4. Increased Concern on Power Quality
With the discovery of electricity over 400 years ago, power quality problems have been,
but not a concern as equipment in those times were not very susceptible to variations in
power system parameters. The rising concern in recent years is consequent to a number
of factors which include: rising use of equipment designed with no performance margin,
increase in electricity demand in homes and industries, and inter-connection of electrical
utility into complex grid (Sankaran, 2002). Other factors are customer awareness,
increased emphasis on overall power system efficiency (Roger C. D. et al, 2004),
increased use of embedded generation and renewable energy sources (Saxena D. K. et
al, 2010), and modification of consumer demand pattern (Zahir J. P., 2011).
5. Detection and Classification of PQ Disturbances
One of the most important issues in power quality has been to detect and classified
disturbance waveforms automatically, and in a more efficient way, as visual observations
have proved inefficient (Perumal C. and Vijayarajan K., 2010). Several techniques
employed to study the characteristics of signal and classify power quality disturbances
are critically analyzed by Saxena D. K. et al (2010). They also identified the challenges of
each method, and emphasized that intelligent approaches using digital signal
processing, expert systems, artificial intelligence and machine learning are better with
some unique advantages. According to Joseph Seymour (2011) power quality
disturbances are classified as transient, interruptions, swell/overvoltage, sag/undervoltage, waveform distortion, voltage fluctuation, frequency fluctuation and voltage
imbalance. The waveforms are shown in figure 2.1.
 Normal wave is a waveform of voltage or current signal with constant frequency,
phase and amplitude.
Figure 2.1a
Normal wave
 Transient is a sub-cycle disturbance in the AC waveform that is perceptible as a
sharp discontinuity of the waveform. It is a fast and short-duration event that
produces waveform distortions such as notching, ringing, and impulse (Sankaran
C., 2002).
Figure 2.1b
Transient
 Interruption is a complete loss of utility supply.
Figure 2.1c
Interruption
 Under-voltage is a reduction in RMS voltage over a range of 0.1–0.9 pu for a
duration greater than 10 ms but less than 1s.
Figure 2.1d
Undervoltage/sag
 Over-voltage refers to increase in RMS voltage over a range of 1.1–1.8 pu for a
duration greater than 10 ms but less than 1s (Chattopadhyay S., et al, 2011).
Figure 2.1e
Overvoltage/swell
 Waveform distortion includes dc offset, harmonics, inter-harmonics, notching and
noise etc. These are signal that transverse the ac power system with frequencies
different to the fundamental frequency.
Figure 2.1f
Waveform distortion
 Voltage fluctuation is the random change in voltage waveform usually of slight
percentage of nominal amplitude with frequency of 0 to 30 Hz.
Figure 2.1g
Voltage fluctuation
 Frequency variation is the deviation of power system frequency from nominal
value.
Figure 2.1h
Frequency variation
 Voltage imbalance occurs when the voltage magnitudes and/or phase angle
between the different phases in a three-phase system are not equal (Joseph
Seymour, 2011).
Figure 2.1i
Voltage unbalance
6. Sources and Effects of Power Quality Problems
Sources of PQ problems can be categorized into load sources, power system sources
(Chattopadhyay S., et al, 2011) or weather and environmental sources (PowerCet,
2010); (Shailesh M. D., 2013). The operation of most loads connected in distribution
system; especially by industrial and commercial users contribute substantially to power
quality disturbances. Non-linear loads like electronic power converters, uninterrupted
power supply (UPS), fluorescent lighting, etc, (Roger C. D., 2004), switching of heavy
loads such as electric motor (Philippe F, 2001) in industries are load related sources.
Power system related sources include: faults, energizing of transformer, utility switching
(Richard P. B., 1998), power system impedance (Michael J. R., 2000) etc. Examples of
weather and environmental source are lightning, wind, rain etc (PowerCet, 2010)
The sensitivity of today’s sophisticated equipment has significantly magnified the effects
of power quality problems. Some effects associated with power quality disturbances are
failure or mal-functioning of equipment, loss of data, data processing errors, over
heating in motors, flickering of lighting and screens etc (Joseph Seymour, 2011). In
distribution network, circuit breaker tripping, equipment malfunction and failure,
interference with communication, cable and transformer heating, data recording and
metering problems and insulation failures are common effects (Zahir J. P., 2011). In
more severe cases, power quality disturbances can lead to damage of any equipment
(Shailesh M. D. et al, 2013).
7. Power Quality Indices and Standards
WG Report (2004) dealt elaborately on power quality indices. As identified, power
quality indices include harmonics, flicker, unbalance voltage dip and long interruption
factors. This report also gave the limit values of these indices and standards of regulatory
bodies such as IEC, EN, ER etc. In addition, power factor (Alexander K., 2014) and total
harmonic distortion (Ir Martin, 2003) are also considered as power quality indices.
International standard organizations such as IEEE, IEC, ANSI etc have developed
standards to regulate power system parameters and power quality indices measured at
point of common coupling (PCC). Standards for current and voltage harmonics, and
limits for total harmonic distortion (THD) for different voltage levels and current rating
are given in (Khalid, 2011; www.mtecorp.com, 2015; Thomas M. et al 2006). Also,
frequency and power factor limits (Obi Patrick I. et al, 2013), voltage limits for service
and
utilization
voltages
(Entergy,
2008)
and
bus
voltage
limits
(www.naruc.org/international) are tabulated in the corresponding documents/papers.
8. Measurement and Monitoring of Power Quality
The use of sensitive devices or equipment has necessitated the demand for good power
quality. As such, the quality of power supply needs to be measured and monitored.
Power quality monitoring involves data acquisition by measuring instruments, manual or
automatic data analysis, and interpretation into useful information. The ultimate goal of
power quality measurement and monitoring is to improve quality power supply. Roger
discussed various issues relating to power quality monitoring including detailed
application of AI technique (Roger C. Dugan, 2004). Several instrument which include
harmonic analyzers, disturbance analyzers, energy monitors, wiring and grounding test
devices and oscilloscopes are used for measuring and monitoring quality of power
supply
9. Solutions to PQ problems
According to Barry W. (2000), solution of power quality problems can be achieve by
good design of equipment (electrical and electronic) and electrical systems,
determination of power quality causes and analysis of symptoms, identification of the
medium transmitting electrical disturbance, and use of power conditioning equipment.
As reviewed by Irfan I. M., et al, 2013 ; Mahmoud Z. et al, 2013), equipments such as
synchronous condensers, static VAR compensator, motor-generator set and ferro
resonance transformers, tap changing transformers, line voltage drop compensators,
shunt capacitors, Surge arresters, Passive filters etc are used to solve power quality
problems. However, these devices are characterized by many disadvantages. These
include: instability, harmonics or transient generation etc. Adequate power quality
improvement is achieved using filtering techniques such as passive filters, active filters,
hybrid filters etc (Irfan I. M., et al, 2013)
Active shunt, series or a combination of both, with passive filters are used as active
power conditioners. The development of active power conditioners are based on
instantaneous reactive power theory, synchronous reference frame theory, synchronous
detection method notch filter method (Bhim S. et al, 1999) or unit vector extraction
method (Saleha T. and Mouli C. B., 2012) control strategies. Active power conditioners
also referred to as custom power devices are; DTATCOM (series), DVR (shunt) and
UPQC (series and shunt) (Mahmoud Z. et al, 2013). Their structure, principle of
operation and applications are discussed in (Shairul W. and Alias Mohd, 2006; Geetha
R. and Aishwariya M. D., 2012; Prasad P. et al, 2013) and many others.
9.1
Custom power devices for PQ improvement
Several researchers have work on the use of custom devices to mitigate power quality
problems. In paper dealing with the design and simulation of DSTATCOM in
MatLab/Simulink, Mohit Bajaj (2013) modeled a DSTATCOM with PI controller. The
model was investigate under fault conditions such as single, and double line to ground,
and three phase faults with static non-linear loads. Result analysis showed satisfactory
performance of DSTATCOM in distribution network. Amed Mokhlari (2014) also
presented a study on DSTATCOM in controlling reactive compensation and maintaining
load voltage level using PI controller. Though excellent result was got, he recommended
further studies in the area of use of multilevel converters, use with dynamic loads, and
use of advance controllers, hysteresis current control and adaptive fuzzy controllers.
Harmonics and undervoltage (voltage sag) compensation using DVR was studied by
Sundarabalan and Selvi (2013). The ANN controller based on park’s transformation
strategy was trained offline with data from a proportional integral controller. According
to Jeevan J. et al (2014), UPQC can compensate for voltage sag and current imbalance.
This was presented in their paper which considered the design of UPQC and controller
base on p-q theory with converter pulse generated by hysteresis band controller. They
recommended a further study on UPQC for other power quality problems.
9.2
Custom devices controllers
Custom power devices though effective solution to power quality problems, are limited in
performance by the type of controllers applied. PI and PID controllers are applied in
custom devices for voltage control in order to mitigate steady state error. The limitations
of these controllers which include: slow response and unsatisfactorily performance under
dynamic load conditions (Ramchandra N. and Kalyanchakravarthi M., 2012), make
them inefficient for modern day distribution systems.
AI techniques are studied as effective techniques for developing optimal controllers for
custom power devices (Rathika P. and Devaraj D., 2010). Commonly used AI controllers
include: FL controllers and ANN controller (Vinita V. et al, 2013). Unlike the
conventional PI and PID, AI base controllers can learn, remember, and make decisions,
and have been proved to be more effective in terms of response and performance under
parameter variations (Ramchandra N. and Kalyanchakravarthi M., 2012). Authors such
as (Sundarabalan C. K. and Selvi K., 2013; Rajasekaran D. et al, 2013;
Seetharamanjaneyulu K. and Nagaraju G., 2014; Saleha T. and Mouli C., 2012;
Madhurantaka T. et al, 2013; Paladugula and Tella N., 2014) have studied the
performance of custom devices with ANN controller with simulation results in
MatLab/Simulink affirming the assertion of Ramchandra N. and Kalyanchakravarthi K.
(2012). Another study with fuzzy logic and PI controller in stabilizing the dc link voltage
of UPQC using p-q control strategy under condition like voltage sag, voltage swell,
voltage unbalance, etc, shows fuzzy logic controller perform better than PI controllers
(Rama R. and Subhransu S. D., 2011).