Journal of Signal Processing and Wireless Networks 2018, 3(3),91-96

91

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JSPWN

Journal of Signal Processing and Wireless Networks

Comparative Analysis of SMES based DVR with PI Controller and Fuzzy Logic

Controller to Improve Power Quality

S. Sunithra, R. Vijayakumar*

Department of Electrical and Electronics Engg., SNS College of Technology, Coimbatore, India,

*Corresponding Author email : r.vijayakumaepse@gmail.com

ABSTRACT Power quality has been an issue that is becoming pivotal in the point of view of electricity consumers in recent times.

The modern technologies employ sensitive power electronics devices, non-linear loads and control devices to increase

their system efficiency. The most common power quality problem due to the use of large number of this sensitive equipments is voltage disturbances. A custom power device Dynamic Voltage Restorer(DVR) has introduced to protect

the sensitive loads from voltage disturbances such as voltage sag/ swell. The performance of the DVR to compensate the

load voltage is based on the controller used to control the DVR. In this paper two different control strategies namely PI controller and Fuzzy Logic Controller(FLC) are proposed and compared based on THD of load voltage during

compensation and the DVR is supported by Superconducting Magnetic Energy Storage(SMES) which is characterized

with highly efficient energy storage and fast response. Using MATLAB/ Simulink the model of SMES supported DVR with PI controller and FLC are established and analysed. The simulation tests are performed to evaluate the system

performance.

ARTICLE HISTORY

Received 12 May 2018 Revised 07 September 2018 Accepted 17 September 2018

KEY WORDS Keywords: Power quality, Dynamic Voltage Restorer(DVR), PI controller, Fuzzy logic controller, SMES.

1. Introduction

In distribution system power quality and reliability had

gain interest and become an area of concern in its modern

industrial and commercial applications. Now-a-days the

increase in sophisticated manufacturing systems, precision

electronic equipments and industrial drives demands more

power quality and reliability of power supply in distribution

system. Wide range of phenomenon has increased problem in

power quality. Voltage sag/swell, flicker, harmonic

distortion, interruptions are few problems. The problems that

are associated with these disturbances are malfunction or

error to plant shut down. More than other power quality

problems voltage sag/ swell is most frequently occurs. This

problem is very important in distribution system [1].

By the IEEE 1159 the voltage sag or dip is defined as the

10% - 90% of decrease from its nominal RMS voltage level,

at power frequency for the duration from 0.5 cycle to 1

minute [2]. In IEC the voltage sag is termed as dip. The IEC

defines the voltage dip is the sudden reduction in voltage of

the electrical system at a point, then the voltage will be

recovered after short period, from 0.5 cycle to a few seconds

[3].

The IEEE 1159-1995 voltage amplitude of voltage sag is

the remaining voltage during the sag. To detect the start and

end of the voltage dip the dip threshold magnitude is

specified , which is defined as 0.9 pu by IEC 1000-4-03. In

general the dip is ranges from 0.1 to 0.9 pu [2,3]. It is usually

associated with system faults, energization of heavy loads

and starting of large motors. The duration of sag is divided as

instantaneous, momentary and temporary [4,5]. By the IEEE

1159 the voltage swell is defined as the increase in the RMS

voltage to 110% - 180% of its nominal voltage. By the IEEE

1159-1995 the amplitude of voltage swell is the remaining

voltage during swell. Swell occur by the temporary voltage

rise on healthy phase during fault like single line to ground.

The function of severity of voltage swell is fault location,

system impedance and grounding [4, 5].

The power quality is related with the economic

consequences that are associated with the equipment

therefore it should be evaluated by considering the point of

view of customers. So there is a need of solution detection to

every single customers with sensitive loads and the fast

response of voltage regulation is required. Furthermore the

domestic and industrial distribution are synthesized by

voltage sag and swell [7,8].

To compensate the power quality problems associated

with voltage sag/ swell the most prominent method used is

Dynamic Voltage Restorer(DVR). To establish the required

voltage level by the load, the DVR is an effective solution to

mitigate the voltage sag/ swell. Dynamic Voltage Restorer is

a custom power device which is connected in series with load

side of the distribution network. Its provide independently

controlled three phase voltage source by electronic

components, whose magnitude and phase are added with the

source voltage to restore the prescribed level of load voltage

[11]. Protection of sensitive loads from the voltage sag/ swell

which is arising in distribution network is the major function

of the DVR. It is generally connected between the supply and

sensitive load of the feeder in distribution network [12]. To

implement DVR; various circuit topologies and control

schemes are available.

This study proposes a comparison of SMES base DVR

with Fuzzy Logic Controller (FLC) based on feedback

92 S. Sunithra, R. Vijayakumar

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control and PI controller capable of compensating power

quality problems associated with voltage sag/ swell and

maintain a prescribed level of supply voltage at load

terminal. The simulation of the proposed SMES based DVR

is accomplished using MATLAB/ Simulink simpower

systems toolbox. The simulation result shown the proposed

DVR by mitigating both balance and unbalance voltage with

its efficiency.

2. Scheme of SMES

Due to the flow of direct current in superconducting

material below its cooled temperature the SMES stores

energy. By discharging the coil as required the stored energy

can be released. The coil can be maintained in its

superconducting state by immersing in a liquid helium in a

vacuum-insulated cryostat. The Fig. 1 shows the block

diagram representation of SMES.

Fig. 1 Scheme of SMES

A SMES comprised of more subsystem. The design must

be more careful to obtain a high performance compensation

device. The SMES has a large super capacitor coil at the

base. The basic system comprised of cold component with

refrigeration system. The equivalent circuit makes use of

lumped parameters represented by six segment model

comprising of self inductance (Li), mutual inductance (Mij),

AC loss resistance (Ri), skin effect related resistance (Rpi),

turn-ground (shunt-Cshi) and turn-turn resistance (series-

Csi). This model is responsible for electric system transient

studies. The frequency ranges from several thousand Hertz.

The surge capacitance insulation (Csg1 and Csg2) and a filter

capacitor are parallel with grounding balance resistor that

reduces the resonance effect. Between the DC/DC converters

the Metal Oxide semiconductor (MOV) is used that protects

against the transient voltage surge suppression.

The common specifications given for a SMES system are

the inductively stored energy and the rated power. These can

be expressed as follows

𝐸 =1

2𝐿𝐼2 (1)

𝑃 =ⅆ𝐸

ⅆ𝑡= 𝐿𝐼

ⅆ𝐼

ⅆ𝑡= 𝑉𝐼 (2)

Where ,

L - Inductance of the coil

I - DC current flowing through the coil

V - Voltage across the coil

3. DVR with SMES

A DVR based on Superconducting Magnetic Energy

Storage (SMES) structure is shown in Fig. 2. This structure

consists of SMES, capacitor bank, Voltage Source Inverter

(VSI), low pass filter and voltage injection transformer. On

the basics of simple principle the SMES is designed. The Fig.

3 shows the energy released circuit model.

Fig. 2 Basic structure of DVR based on SMES

The three operating states of circuit model is as follows

Energy-charging state

(K1, K3 are closed, K2 opened)

Energy-storing state

(K2, K3 are closed, K1 opened)

Energy discharge state

(K2 closed, K1, K3 are opened)

The solenoid coil is placed across the DC source when the

cycle of charging. When the required amount of energy is

stored in the coil, then there is a removal of DC source and

the short circuit of solenoid coil through the material called

superconductor.

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Fig. 3 SMES energy releasing circuit

Fig. 4 SMES supported DVR

In practical application to mitigate the simulated voltage

sag, a control scheme of PI controller and FLC with discrete

pulse width modulation is implemented as shown in Fig.4. To

maintain the constant voltage magnitude at system

disturbance is the main aim of the control scheme, Only the

RMS voltage at the load point is measured by control

schemes. Various phase faults such as voltage sag, swell and

interruption are created at load terminal as shown in Fig.4.

3.1 DVR with PI Controller

PI controller is a feedback controller. The per unit (p.u)

quantity of the load side voltage is passed through the

sequence analyzer. then the magnitude of the terminal

voltage and reference voltage is compared in comparator and

the error signal is fed into the PI controller. The PI controller

produces the modulation angle δ and fed it into PWM

generator as shown in Fig. 5, which produces the triggering

pulses to switch the switches in VSI of DVR and which is

triggered to generate 3, 50Hz sinusoidal voltage at load

terminal. In PWM generator the chopping frequency is few

kilo Hertz. To maintain 1 p.u voltage at load terminal the PI

controller controls the IGBT of VSI where the base voltage is

1 p.u. The voltage angle control of the DVR controls the

system as follows:

The error signal from the comparator is processed by the

PI controller and it generates the required angle δ. then the

angle δ (modulation angle) is fed to PWM generator which

generates phase A, for phase B and phase C the angle is

shifted by -120 ֠ and 120 ֠ as expressed below,

𝑉𝐴 = sin 𝜔𝑡 + 𝛿 (3)

𝑉𝐵 = sin 𝜔𝑡 + 𝛿 − 2𝜋/3 (4)

𝑉𝐵 = sin 𝜔𝑡 + 𝛿 + 2𝜋/3 (5)

The PI controller has the advantages of steady state error

to zero for a step input in the terms of integral. The actual

signal which is the difference of Vref and Vinput is the input

for PI controller. The angle δ is the output of the controller

block. The output of the error detector(comparator) is,

𝑉𝑟𝑒𝑓 − 𝑉𝑖𝑛 (6)

Where,

Vref - 1p.u voltage

Vin - Voltage in p.u at the load terminal

The controller output is the input of the PWM generator

which generates the desired firing sequence.

Fig. 5 PI controller

3.2 DVR with Fuzzy Logic Controller (FLC)

Fuzzy logic controller is a non-linear controller and it

does not require any mathematical calculations and models.

In can provide satisfactory performance under various fault

conditions. In uses linguistic variables rather than numerical

variables. In improve both transient and steady state

performance of the system. The four main functional blocks

of fuzzy controller comprises of rule base(knowledge base),

fuzzification, inference engine and defuzzification as shown

in Fig. 6. Fuzzification converts input data into linguistic

value. A knowledge base consists of linguistic definitions of

necessary data base. The rule base consists of rule set. A

defuzzification which converts the fuzzy output into crisp

control signal.

Fig. 6 Structure of fuzzy logic controller

The FLC used in this paper consists of error signal d and

error signal q. For these two error signals FL consists of 3

linguistic variables as, Negative (N), Zero (Z), Positive (P).

For change in error i.e. Δe there are 5 linguistic variables for

both d and q axis as, Negative Big (NB), Negative Small

94 S. Sunithra, R. Vijayakumar

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(NS), Zero (z), Positive Big (PB), Positive Small (PS). The

Mumdani type of inference method is used in the test system

of FLC. The crisp input and output variables are defuzzifies

into fuzzy triangular membership function. The fuzzy control

rule are the core of the controller, it is shown in table 1.

Table 1 Fuzzy associative memory table

4. Results and Discussions

In proposed system the simulation is carried out with

MATLAB/ Simulink simpower system toolbox. It performed

for the symmetrical fault for the time duration of 0.3sec to

0.5sec. The system specification is 11kV, 50Hz. This fed to

two distribution network as feeder1 and feeder2. With the

fault resistance of 0.44Ω and the fixed duration of 200ms

with the 588kA of SMES the system is tested. The system

with PI controller is shown in Fig.7. The system with fuzzy

logic controller is shown in Fig 8.

Fig. 7 DVR with PI controller

Fig. 8 DVR with fuzzy logic controller

The Fig. 9 shows that the compensated load voltage by

the control of PI controller. The fault is occurred at the

instant 0.3sec to 0.5sec. At that instant the DVR injects the

voltage to compensate the voltage dip occurred due to

symmetrical fault. The THD of this load voltage is 10.89% as

shown in Fig. 10.

Fig.9 Compensated voltage by DVR with PI controller

Journal of Signal Processing and Wireless Networks 2018, 3(3), 91-96

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Fig. 10 THD of load voltage compensated by DVR with PI

controller

The Fig. 1 shows that the compensated load voltage by

the control of fuzzy logic controller. The fault is occurred at

the instant 0.3sec to 0.5sec. At that instant the DVR injects

the voltage to compensate the voltage dip occurred due to

symmetrical fault. The THD of this load voltage is 7.72% as

shown in Fig. 12.

Fig. 11 Compensated voltage by DVR with Fuzzy logic

controller

Fig. 12 THD of load voltage compensated by DVR with

Fuzzy logic controller

5. Conclusion

In this paper simulation of SMES based DVR is

presented with PI controller and Fuzzy Logic Controller

(FLC). It shows that DVR can compensate the voltage dip

quickly and regulates the voltage efficiently. Comparing the

performance of the two controllers i.e. PI controller and

fuzzy logic controller presented here, the THD of load

voltage is 10.84% with PI controller and 7.% with fuzzy

logic controller. With this result it can be concluded that the

Fuzzy Logic Controller (FLC) is performing better than PI

controller.

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