Comparision of pi, fuzzy & neuro fuzzy controller based multi converter unified power quality

International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 –
INTERNATIONAL JOURNAL OF ELECTRICAL ENGINEERING
6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME
& TECHNOLOGY (IJEET)

ISSN 0976 – 6545(Print)
ISSN 0976 – 6553(Online) IJEET
Volume 4, Issue 2, March – April (2013), pp. 136-154
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COMPARISION OF Pi, FUZZY & NEURO-FUZZY CONTROLLER
BASED MULTI CONVERTER UNIFIED POWER QUALITY
CONDITIONER

B.RAJANI1, Dr.P.SANGAMESWARA RAJU2
1
Phd.Research Scholar,S.V.University.College of Engineering, Dept.of Electrical Engg
Tirupathi, A.P INDIA
2
Professor, SV University, Tirupathi, Andhra Pradesh, INDIA

ABSTRACT

Multi converter -Unified power quality conditioner (MC-UPQC) is one of the new
power electronics devices that are used for enhancing the PQ. This paper presents a new
unified power-quality conditioning system (MC-UPQC), capable of simultaneous
compensation for voltage and current in multibus/multifeeder systems. In this configuration,
one shunt voltage-source converter (shunt VSC) and two or more series VSCs exist. The
system can be applied to adjacent feeders to compensate for supply-voltage and load current
imperfections on the main feeder and full compensation of supply voltage imperfections on
the other feeders. In the proposed configuration, all converters are connected back to back on
the dc side and share a common dc-link capacitor. sharing with one DC link capacitor. The
discharging time of DC link capacitor is very high, and so it is the main problem in MC-
UPQC device. To eliminate this problem, an enhanced Neuro-fuzzy controller (NFC) based
MC-UPQC is proposed in this paper. NFC is the combination of neural network (NN) based
controller and fuzzy logic controller (FLC). Initially, the error voltage and change of error
voltage of a nonlinear load is determined. Then the voltage variation is applied separately to
FLC and NN-based controller. In order to regulate the dc-link capacitor voltage,
Conventionally, a proportional controller (PI) is used to maintain the dc-link voltage at the
reference value. The transient response of the PI dc-link voltage controller is slow. So, a fast
acting dc-link voltage controller based on the energy of a dc-link capacitor is proposed. The
transient response of this controller is very fast when compared to that of the conventional
dc-link voltage controller. By using fuzzy logic controller instead of the PI controller the
transient response is improved. The DC capacitor charging output voltage is increased and

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the response is fast when compared with fuzzy by using the Neuro –Fuzzy logic controller
and hence, the PQ of the system is enhanced. The proposed controller is tested and the results
of tested system and their performances are evaluated & the Voltage and current harmonics
(THD’s) of MC-UPQC with different intelligence techniques are calculated and listed
Therefore, power can be transferred from one feeder to adjacent feeders to compensate for
sag/swell and interruption. The performance of the proposed configuration has been verified
through simulation studies using MATLAB/SIMULATION on a two-bus/two-feeder system
show the effectiveness of the proposed configuration.
KEYWORDS: power quality (PQ), matlab/simulation multi converter unified power-quality
conditioner (MC-UPQC), (VSC), fuzzy logic controller (FLC), neural network (NN) based
controller, neuro-fuzzy controller (NFC), harmonics.

1. INTRODUCTION
Power quality is the combination of voltage quality and current quality. Voltage
quality is concerned with the deviation of actual voltage from ideal voltage. Current quality is
the equivalent definition for the current. Any deviation of voltage or current from the ideal is
a power quality disturbance. Any change in the current gives a change in the voltage and the
other way around. Voltage disturbance originate in the power network and potentially affect
the customers, where as current disturbance originate with customer and potentially affect the
network [1]. As commercial and industrial customers become more and more reliant on high
quality and high-reliability electric power, utilities have considered approaches that would
provide different options or levels of premium power for those customers who require
something more than what the bulk power system can provide insufficient power quality can
be caused by failures and switching operations in the network, which mainly result in voltage
dips, interruptions, and transients and network disturbances from loads that mainly result in
flicker (fast voltage variations), harmonics, and phase imbalance. Momentary voltage sags
and interruptions are by far the most common disturbances that adversely impact electric
customer process operations in large distribution systems. In fact, an event lasting less than
one-sixtieth of a second (one cycle) can cause a multimillion-dollar process disruption for a
single industrial customer. Several compensation [3] devices are available to mitigate the
impacts of momentary voltage sags and interruptions. When PQ problems are arising from
nonlinear customer loads, such as arc furnaces, welding operations, voltage flicker and
harmonic problems can affect the entire distribution feeder [2]. Several devices have been
designed to minimize or reduce the impact of these variations. The primary concept is to
provide dynamic capacitance and reactance to stabilize the power system. This is typically
accomplished by using static switching devices to control the capacitance and reactance, or
by using an injection transformer to supply the reactive power to the system. Now a days,
voltage based converter improving the power quality (PQ) of power distribution systems. A
Unified Power Quality Conditioner (UPQC)[4] can perform the functions of both D-
STATCOM and DVR. The UPQC consists of two voltage source converters (VSCs) that are
connected to a common dc bus. One of the VSCs is connected in series with a distribution
feeder, while the other one is connected in shunt with the same feeder. The dc-links of both
VSCs are supplied through a common dc capacitor. It is also possible to connect two VSCs to
two different feeders in a distribution system is called Interline Unified Power Quality
Conditioner (IUPQC) This paper presents a new Unified Power Quality Conditioning system
called Multi Converter Unified Power Quality Conditioner (MC-UPQC) [5].

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CIRCUIT CONFIGURATION

As shown in this Fig.1 two feeders connected to two different substations supply the
loads L1 and L2. The MC-UPQC is connected to two buses BUS1 and BUS2 with voltages
of ut1 and ut2, respectively. The shunt part of the MC-UPQC is also connected to load L1
with a current of il1. Supply voltages are denoted by us1 and us2 while load voltages are ul1
and ul2. Finally, feeder currents are denoted by is1 and is2 and load currents are il1 and il2.
Bus voltages ut1 and ut2 are distorted and may be subjected to sag/swell. The load L1 is a
nonlinear/sensitive load which needs a pure sinusoidal voltage for proper operation while its
current is non-sinusoidal and contains harmonics. The load L2 is a sensitive/critical load
which needs a purely sinusoidal voltage and must be fully protected against distortion,
sag/swell and interruption. These types of loads primarily include production industries and
critical service providers, such as medical centers, airports, or broadcasting centers where
voltage interruption can result in severe economical losses or human damages

Figure- 1. Single - line diagram of MC-UPQC connected distribution system

2. MC–UPQC STRUCTURE

The internal structure of the MC–UPQC is shown in Figure-2. It consists of three
VSCs (VSC1, VSC2, and VSC3) which are connected back to back through a common dc-
link capacitor. In the proposed configuration, VSC1 is connected in series with BUS1 and
VSC2 is connected in parallel with load L1 at the end of Feeder1. VSC3 is connected in
series with BUS2 at the Feeder2 end.

Figure- 2 Typical MC-UPQC used in a distribution system.

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Reactor and high-pass output filter as shown in Figure-3. The commutation reactor (Lf) and
high- pass output filter (R f, C f) are connected to prevent the flow of switching harmonics
into the power supply. Each of the three VSCs in Figure-2 is realized by a three-phase
converter with a commutation

Figure-3. Schematic structure of a VSC

As shown in Figure-2. all converters are supplied from a common dc-link capacitor
and connected to the distribution system through a transformer. Secondary (distribution) sides
of the series-connected transformers are directly connected in series with BUS1 and BUS2,
and the secondary (distribution) side of the shunt-connected transformer is connected in
parallel with load L1. The aims of the MCUPQC are: 1) To regulate the load voltage (ul1)
against sag/swell, interruption, and disturbances in the system to protect the Non-
Linear/sensitive load L1. 2) To regulate the load voltage (ul2) against sag/swell, interruption,
and disturbances in the system to protect the sensitive/critical load L2. 3) To compensate for
the reactive and harmonic components of nonlinear load current (il1) In order to achieve these
goals, series VSCs (i.e., VSC1 and VSC3) operate as voltage controllers while the shunt VSC
(i.e., VSC2) operates as a current controller.

3. CONTROL STRATEGY

As shown in Figure-2, the MC-UPQC consists of two series VSCs and one shunt VSC
[6]-[8] which are controlled independently. The switching control strategy for series VSCs
and the shunt VSC are selected to be sinusoidal pulse width-modulation (SPWM) voltage
control and hysteresis current control, respectively. Details of the control algorithm, which
are based on the d-q method [12], will be discussed later.
Shunt-VSC: Functions of the shunt-VSC are: 1) To compensate for the reactive
component of load L1 current; 2) To compensate for the harmonic components of load L1
current; 3) To regulate the voltage of the common dc-link capacitor.

Figure-4. Control block diagram of the shunt VSC.

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Figure-4. shows the control block diagram for the shunt VSC. The measured load current (il-
dqo
abc) is transformed into the synchronous reference frame by using

Where the transformation matrix is shown in (2),

By this transform, the fundamental positive-sequence component, which is transformed into
dc quantities in the axes, can be easily extracted by low-pass filters (LPFs). Also, all
harmonic components are transformed into ac quantities with a fundamental frequency shift

Where il-d and il-q are d-q components of load current, il_d and il_q are dc components, and il˜d
and il˜q are the ac components of il-d, and il-q.
If is is the feeder current and ip f is the shunt VSC current and knowing is =il - ipf , then d–q
components of the shunt VSC reference current are defined as follows

Consequently, the d–q components of the feeder current are

This means that there are no harmonic and reactive components in the feeder current.
Switching losses cause the dc-link capacitor voltage to decrease. Other disturbances, such as
the sudden variation of load, can also affect the dc link. In order to regulate the dc-link
capacitor voltage, a proportional–integral (PI) controller is used as shown in Fig. 4. The input
of the PI controller is the error between the actual capacitor voltage (udc) and its reference
value (udc ref). The output of the PI controller (i.e., delta idc) is added to the component of the
shunt-VSC reference current to form a new reference current as follows:

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As shown in Fig. 4, the reference current in (6.11) is then transformed back into the abc
reference frame. By using PWM hysteresis current control, the output-compensating currents
in each phase are obtained.

Series-VSC: Functions of the series VSCs in each feeder are:
1 To mitigate voltage sag and swell;
2 To compensate for voltage distortions, such as harmonics;
3 To compensate for interruptions (in Feeder2 only).

Figure-5. Control block diagram of the series VSC.

The control block diagram of series VSC is shown in Figure.5.The bus voltage (ut-abc) is
detected and then transformed into the synchronous dq0 reference frame using

ut1p, ut1n and ut10 are fundamental frequency positive-, negative-, and zero-sequence
components, respectively, and uth is the harmonic component of the bus voltage. According
to control objectives of the MC-UPQC, the load voltage should be kept sinusoidal with
constant amplitude even if the bus voltage is disturbed. Therefore, the expected load voltage
in the synchronous dqo reference frame (u l-dqoexp) only has one value

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Where the load voltage in the abc reference frame (u l-abcexp) is

The compensating reference voltage in the synchronous dqo reference frame (ul-dqoexp) is
defined as

This means ut1p-d in (12) should be maintained at Um while all other unwanted components
must be eliminated. The compensating reference voltage in (15) is then transformed back into
the abc reference frame. By using an improved SPWM voltage control technique (sine PWM
control with minor loop feedback)[8], the output compensation voltage of the series VSC can
be obtained

4. NEURO-FUZZY CONTROLLER (NFC):

A neuro-fuzzy system is a fuzzy system that uses a learning algorithm derived from or
inspired by neural network theory to determine its parameters (fuzzy sets and fuzzy rules) by
processing data samples.NFC is the combination of Fuzzy Inference System (FIS)and NN.
The fuzzy logic is operated based on fuzzy rule and NN is operated based on training dataset.
The neural network training dataset are generated from the fuzzy rules. The function of NFC
is explained in the below section.

4.1 FUZZY LOGIC CONTROLLER

Fuzzy control system is a control system based on fuzzy logic –a mathematical
system that analyzes along input values in terms of logical variables that take on continuous
values between 0 and 1. Controllers based on fuzzy logic give the linguistic strategies control
conversion from expert knowledge in automatic control strategies. Professor Lotfia Zadeh
at University of California first proposed in 1965 as a way to process imprecise data its
usefulness was not seen until more powerful computers and controllers were available . In
the fuzzy control scheme, the operation of controller is mainly based on fuzzy rules, which
are generated using fuzzy set theory. Fuzzy controller plays an important role in the
compensation of PQ problem the steps involved in fuzzy controller are fuzzification, decision
making, and defuzzification. Fuzzification is the process of changing the crisp value into
fuzzy value. The fuzzification process has no fixed set of procedure and it is achieved by
different types of fuzzifiers. The shapes of fuzzy sets are triangular, trapezoidale and more.
Here, a triangular fuzzy set is used. The fuzzified output is applied to the decision making
process, which contains a set of rules. Using the fuzzy rules, the input for bias voltage
generator is selected from FIS. Then, the defuzzification process is applied and the fuzzified
calculated voltage (Vdc )is determined. The structure of designed FLC is illustrated as
follows.

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Figure-6. Block diagram of a fuzzy logic controller

and the steps for designing FLC are pointed below .
• Fuzzification strategy
• Data base building
• Rule base elaboration
• Interface machine elaboration
• Defuzziffication strategy

In addition, design of fuzzy logic controller can provide desirable both small signal
and large signal dynamic performance at same time, which is not possible with linear control
technique. The development of fuzzy logic approach here is limited to the des design and
structure of the controller. .The inputs of FLC are defined as the voltage error, and change of
error.Fuzzy sets are defined for each input and out put variable. There are seven fuzzy levels
(NB-negative big, NM-negative medium, NS-negative small Z-zero, PS-positive small, PM-
negative NS positive PM
positive medium, PB-positive big) the membership functions for input and output variables
positive
are triangular. The min-max method interface engine is used. The fuzzy method used in this
max
FLC is center of area. The complete set of control rules is shown in Table.1. Each of the 49
control
control rules represents the desired controller response to a particular situation. Figure.6
shows the block diagram of a fuzzy logic controller .The block diagram presented in Figure-
.The
7..shows a FLC controller in the MATLAB simulation. The simulation parameters are shown
in Table1. The performance of degree of member ship functions are shown in Fig Figure-8.

Figure-7. The block diagram presented in Figure above shows a FLC controller in the
MATLAB simulation

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Figure-8. Performance of Membership Function (i) Error Voltage, (ii) Change of Error
Voltage and (iii)Output Voltage.

Table 1. Fuzzy rule table
Change in Error
Error
NB NM NS Z PS PM PB

NB NB NB NB NB NM NS Z

NM NB NB NB NM NS Z PS

NS NB NB NM NS Z PS PM

Z NB NM NS Z PS PM PB

PS NM NS Z PS PM PB PB

PM NS Z PS PM PB PB PB

PB Z PS PM PB PB PB PB

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4.2 DESIGNING & TRAINING OF ANN

An artificial neural network (ANN), often just called a "neural network" (NN), is a
mathematical model or computational model based on biological neural networks. It consists
of an interconnected group of artificial neurons and processes information using a
connectionist approach to computation. In most cases an ANN is an adaptive system that
changes its structure based on external or internal information that flows through the network
during the learning phase. In more practical terms neural networks are non-linear statistical
data modeling tools. They can be used to model complex relationships between inputs and
outputs or to find patterns in data. NN is an artificial intelligence technique that is used for
generating training data set and testing the applied input data . A feed forward type NN is
used for the proposed method. Normally, the NN consist of three layers: input layer, hidden
layer and output layer. Here, the error, change of error, and the regulated output voltage are
denoted as Ve ,V∆e,VDCNN respectively. The structure of the NN is described as follows.

Figure-9.. Structure of the NN for Capacitor Voltage Regulation.

In Figure-9., the input layer, hidden layer and output layer of the network are (H11,
H12), (H21 ,H22…..H2N), and H31 respectively. The weight of the input layer to hidden
layer is denoted asw11, w 12,w1N ,w21, w22 ,and w2N . The weight of the hidden layer to output
layer is denoted as w 211,w221 ,w2N1 . Here, the Back Propagation (BP) training algorithm is
used for training the network. Figure-10. Shows the Proposed System NN Structure. Figure-
11.shows the NN Performance Plots (i) Regression Analysis, (ii) Network Validation
performance and (iii)Training State.

Figure-10. Proposed System NN Structure.

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Figure-11. NN Performance Plots (i) Regression Analysis, (ii) Network Validation
performance and (iii)Training State.

5. SIMULATION STUDIES

The performance of the simulation model of MC-UPQC in a two-feeder distribution
system as in figure.1 is analyzed by using MATLAB/SIMULATION The supply voltages of
the two feeders consists of two three-phase three-wire 380(v) (RMS, L-L), 50-Hz utilities.
The BUS1 voltage (ut1) contains the seventh-order harmonic with a value of 22%, and the
BUS2 voltage (ut2) contains the fifth order harmonic feeder1 load is a combination of a
three-phase R-L load (R = 10 Ohms, L =30µ H) and a three-phase diode bridge rectifier
followed by R-L load on dc side (R = 10 Ohms, L = 100 mH) which draws harmonic current.
Similarly to introduce distortion in supply voltages of feeder2 , 7th and 5th harmonic voltage
sources, which are 22 % and 35% of fundamental input supply voltages are connected in
series with the supply voltages VSC1 and VSC3 respectively. In order to demonstrate the
performance of the proposed model of MC-UPQC simulation case studies are carried out.
The simulink model for distribution system with MC-UPQC is shown in Figure 12.

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Figure-12. Simulink model of distribution system with MC-UPQC

5.1 COMPENSATION OF CURRENT AND VOLTAGE HARMONICS

Simulation is carried out in this case study under distorted conditions of current in
feeder1 and supply voltages in feeder1. Figure-13. represents three-phase load, compensation
and source currents and capacitor voltage of feeder1 before and after compensation with PI
controller in figure.13 and with Fuzzy in figure 14. It is to be noted that the shunt
compensator injects compensation current at 0.1s as in Fig13. The Effectiveness of MC-
UPQC is evident from Fig. 13. as the source current becomes sinusoidal and balanced from
0.5 s. The Total Harmonic Distortion (THD) of load and source currents is identical before
compensation and is observed to be 28.5%. After compensation the source current THD is
observed to be less than 5 %. The THD values of sourcevoltage and current are listed in table
-2 , the dc voltage regulation loop has functioned properly under all disturbances, such as
sag/swell in both feeders. Thus a significant improvement in the frequency spectrum and
THD after compensation is clearly

Table.2 Voltage and current harmonics (THD’s) of MC- UPQC

Order of WITHOUT WITHOUT MCUPQC MCUPQC MCUPQC MCUPQC MCUPQC MCUPQC
harmonics MCUPQC MCUPQC with PI with PI with with with with
utility side utility side controller controller FUZZY FUZZY NEURO- NEURO-
voltage current utility side utility side controller controller FUZZY FUZZY
voltage current utility side Utility controller controller
voltage side utility side Utility
current voltage side
current

5th & 7th 0.92 1.276 0.7201 0.42 0.5401 0.2573 0.22 0.0409

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Figure-13.Simulation Result for Nonlinear load current, compensating current, Feeder1
current, and capacitor voltage with PIcontroller

current, and capacitor voltage with FUZZYcontroller

current, and capacitor voltage with NEURO-FUZZY

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Figure-16. Simulation Result for BUS1 voltage, series compensating voltage, and load
voltage in Feeder1

Figure-17. Simulation Result for BUS2 voltage, series compensating voltage, and load
voltage in Feeder2

From the simulation results as shown in the above figure.11 and figuer.12 distorted
voltages of BUS1 and BUS2 are satisfactorily compensated for across the loads L1 and L2
with very good dynamic response .

5.2 COMPENSATION OF VOLTAGE HARMONICS, VOLTAGE SAG/SWELL

The BUS1 voltage(ut1) contains seventh-order harmonics with a value of 22%, The
BUS1 voltage contains 25% voltage sag from 0.1s to 0.2s and 20% voltage swell from 0.2s to
0.3s. and the BUS2 voltage (ut2) contains the fifth order harmonic with a value of 35%. The
BUS2 voltage contains 35% sag from 0.15s to 0.25s and 30% swell from 0.25s to 0.3s The
nonlinear/sensitive load L1 is a three-phase rectifier load which supplies an RL load of 10
and 30µH. The MC–UPQC is switched on at t=0.02s. The BUS1 and BUS2 voltages, the
corresponding compensation voltages injected by VSC1,and VSC3 and finally load L1 and
L2 voltages are shown in figure.15 figure.16 and figure. 17 respectively.

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5.3 UPSTREAM FAULT ON FEEDER2

When a fault occurs in Feeder2 in any form of L-G, L-L-G, and L-L-L-G faults, the
voltage across the sensitive/critical load L2 is involved in sag/swell or interruption. This
voltage imperfection can be compensated for by VSC2. In this case, the power required by
load L2 is supplied through VSC2 and VSC3. This implies that the power semiconductor
switches of VSC2 and VSC3 must be rated such that total power transfer is possible. The
performance of the MC-UPQC under a fault condition on Feeder2 is tested by applying a
three- phase fault to ground on Feeder2 from 0.3s to 0.4 s. Simulation results are shown in
figure.18

Figure-18. simulation results for an upstream fault on Feeder2, BUS2 voltage, compensating
voltage, and loads L1 and L2 voltages.

5.4. SUDDEN LOAD CHANGE
To evaluate the system behavior during a load change, the nonlinear load L1 is
doubled by reducing its resistance to half at 0.5 s. The other load, however, is kept
unchanged. In this case load current and source currents are suddenly increased to double and
produce distorted load voltages (Ul1 and Ul2) the performance of the MC-UPQC is tested
when sudden load change occurs in feeder-1 at nonlinear/sensitive load with PI ,Fuzzy and
with neuro-Fuzzy controller as shown in figure.19 ,figure .20 and figure-21.respectively

Figure-19.Simulation results for load change: nonlinear load current, Feeder1 current, load
L1 voltage, load L2 voltage, and dc-link capacitor voltage with PI controller

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L1 voltage, load L2 voltage, and dc-link capacitor voltage with FUZZY

L1 voltage, load L2 voltage, and dc-link capacitor voltage with NEURO-FUZZY

5.5. UNBALANCED SOURCE VOLTAGE IN FEEDER-1.

The MC-UPQC performance is tested when unbalance source voltage occurs in
feeder-1 at nonlinear/sensitive load without and with MC-UPQC. The control strategies for
shunt and series VSCs, Which are introduced and they are capable of compensating for the
unbalanced source voltage and unbalanced load current. To evaluate the control system
capability for unbalanced voltage compensation, a new simulation is performed. In this new
simulation, the BUS2 voltage and the harmonic components of BUS1 voltage are similar.
However, the fundamental component of the BUS1 voltage (Ut1fundamental) is an
unbalanced three-phase voltage with an unbalance factor (U- /U+) of 40%.The simulation
results show that the harmonic components and unbalance of BUS1 voltage are compensated
for by injecting the proper series voltage. In this figure, the load voltage is a three-phase
sinusoidal balance voltage with regulated amplitude. The simulation results for the three-
phase BUS1 voltage series compensation voltage, and load voltage in feeder-1 are shown in
Figure.22.

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Fig 22.BUS1 voltage, series compensating voltage, and load voltage in Feeder1 under
unbalanced source voltage.

6. CONCLUSION

A new custom power device named as MC-UPQC, to mitigate current and voltage
harmonics, compensate reactive power and to improve voltage regulation. The compensation
performance of shunt and a novel series compensator are established by the simulation results
on a two-feeder, multibus distribution system. The proposed MC-UPQC can accomplish
various compensation functions by increasing the number of VSCs. This paper illustrates
compensating ac unbalanced loads and a dc load supplied by the dc-link of the compensator
is presented. The transient response of the MC-UPQC is very important while compensating
fast varying loads. When there is any change in the load it will directly effects the dc-link
voltage .The transient response of the conventional dc-link voltage controller is very slow.
So, an energy based dc-link voltage controller is taken for the fast transient response. The
conventional Neuro-fuzzy logic controller gives the better transient response and also DC
capacitor Voltage magnitude increased as shows in the results than that of the conventional PI
and fuzzy controller. which are discussed above. The efficacy of the proposed controller is
established through a digital simulation. It is observed from the above studies the proposed
neuro-fuzzy logic controller gives the fast transient response for fast varying loads when
compared with PI and FUZZY logic controllers. the response of Neuro-Fuzzy controller is
faster and the THD is minimum for the both the voltage and current which is evident from the
plots and comparison Table .2 Proposed model for the MC-UPQC is to compensate input
voltage harmonics and current harmonics caused by non-linear load. The performance of the
MC-UPQC is evaluated under various disturbance conditions like the supply voltage and load
current imperfections such as sags, swells, interruptions, voltage imbalance, flicker, and
current unbalance. Voltage and current harmonics (THD’s) of MC- UPQC with different
intelligence techniques have been verified and among them Neuro-Fuzzy controller shows
better result when compared with Pi and Fuzzy .The MC-UPQC is expected to be an
attractive custom power device for power quality improvement of multibus/multi-feeder
distribution systems in near future.

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[13] A.Padmaja, V.S.Vakula, T.Padmavathi and S.V.Padmavathi, “Small Signal Stability
Analysis Using Fuzzy Controller and Artificial Neural Network Stabilizer”, International
Journal of Electrical Engineering & Technology (IJEET), Volume 1, Issue 1, 2010,
pp. 47 - 70, ISSN Print : 0976-6545, ISSN Online: 0976-6553.

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AUTHORS BIOGRAPHY

B.Rajani received B.Tech degree in Electrical & Electronics Engineering
from S.I.S.T.A.M college of Engineering, Srikakulam 2002 and M.E degree
in Power Systems and Automation from Andhra university,Visakhapatnam in
the year 2008.she presently is working towards her Ph.D degree in
S.V.University, Tirupathi. Her areas of interest are in power systems
operation &control and stability.

Dr. P.Sangameswarararaju received Ph.D from Sri Venkateswara
Univerisity, Tirupathi, Andhra Pradesh. Presently he is working as professor
in the department of Electrical & Electronics Engineering, S.V. University.
Tirupati, Andhra Pradesh. He has about 50 publications in National and
International Journals and conferences to his credit .His areas of interest are
in power system operation &control and stability.

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Comparision of pi, fuzzy & neuro fuzzy controller based multi converter unified power quality

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