Fault Detection and Power Quality Compensation Using Fuzzy Logic

Based Dynamic Voltage Restorer

Kumari Santosh

, Seema Agrawal

and Tapesh Yogi

Department of Electrical Engineering, Rajasthan Technical University Kota, Kota, India

Keywords: Power Quality, Dynamics Voltage Restorer, Fuzzy Logic, Voltage Sag, PI, PID, Voltage Swell.

Abstract: The current vitality situation faces a significant challenge in power quality. With the increasing use of

sensitive hardware, power quality has become a crucial aspect, particularly in terms of input power supply.

Power quality issues can lead to the failure of advanced devices due to unusual current and voltage

frequencies. The primary concern lies in voltage enlargement and dips. A specific system is proposed to

address this issue to prevent voltage enlargement and dips. Modified power equipment, such as Dynamic

Voltage Restorers (DVRs), are employed to resolve this issue. DVRs are advanced, customized control

devices used in power distribution systems, offering advantages like compact size, low cost, and excellent

dynamic response to disturbances. This study presents MATLAB 2021 results for a model based on Fuzzy

Logic (FL) and DVR controllers. FL-based DVR controllers are used in the suggested method to improve the

composite microgrid system's performance. The goal is to develop a faster and more efficient controller than

traditional procedures. The performance will be evaluated using MATLAB simulation tools.

1 INTRODUCTION

Now a days Power distribution lines are crucial for

transmitting electricity over long distances to

consumers. However, these lines are vulnerable to

various hazards, including harsh weather, mechanical

damage, and insulation failure.

Faults in a power system refer to any abnormal

condition that disrupts the normal flow of electrical

current. These faults can occur due to various reasons

such as equipment failure, human error, natural

disasters, or aging infrastructure. Faults can be

classified into several types, including symmetrical

faults, such as three-phase faults, and unsymmetrical

faults, such as phase-to-phase faults, phase-to-ground

faults, and open circuit faults. When a fault occurs, it

can cause a short circuit, leading to an increase in

current flow, which can damage equipment and pose

a risk to human safety. Therefore, it is essential to

detect and clear faults quickly to prevent damage and

ensure the reliable operation of the power system.

This is typically achieved through the use of

protective devices, such as circuit breakers and fuses,

which can detect abnormal conditions and interrupt

the flow of current to prevent further damage.

(Khandakar, Rabbi, et al. , 2024). Fault detection in

power systems is a critical concern for maintaining

system reliability. Consequently, numerous

techniques have been proposed to address this

challenge(Manglik, Li, et al. , 2016).

Increasing power quality by addressing voltage

sags, a prevalent issue within power systems. To

mitigate sags arising from diverse fault scenarios, the

use of a Dynamic Voltage Restorer (DVR) with a

Proportional-Integral (PI) controller is suggested in

the study (Srinivas., Amarendar, et al. , 2024). Power

quality indicators and employs a detection system to

pinpoint faults within distribution networks. The

study emphasizes the system's efficacy in improving

power quality, enhancing fault identification

accuracy, and ultimately bolstering the overall

reliability of power supply (Wanru, He., et al. , 2023).

Dynamic Voltage Restorers (DVRs) are versatile

power devices that can effectively address various

voltage quality issues. By being connected in series

with the power system, DVRs can inject or absorb

reactive power to regulate voltage levels. This paper

provides a comprehensive exploration of DVR

implementation and simulation, with a particular

emphasis on the crucial aspect of switching control

strategy. A pulse width modulation (PWM) scheme is

employed to regulate the output voltage of the DVR,

and detailed results demonstrating its effectiveness

are presented (Rajesh, Mishra, et al. , 2023).

106

Santosh, K., Agrawal, S. A. and Yogi, T.

Fault Detection and Power Quality Compensation Using Fuzzy Logic Based Dynamic Voltage Restorer.

DOI: 10.5220/0013609500004664

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 3rd International Conference on Futuristic Technology (INCOFT 2025) - Volume 3, pages 106-113

ISBN: 978-989-758-763-4

DVRs are specialized power devices designed to

counteract voltage sags, swells, and harmonics within

distribution networks. Their construction involves a

combination of power electronic components, control

systems, and energy storage elements. By

strategically injecting or absorbing reactive power,

DVRs effectively mitigate voltage quality issues,

ensuring reliable and efficient power delivery.

Dynamic Voltage Restorers (DVRs) are versatile

power electronic devices used to improve voltage

quality in power systems (Abas, Dilshad, et al. ,

2020). They are particularly effective in addressing

voltage sags, swells, and harmonics, which can

negatively impact the performance of sensitive

equipment. By injecting or absorbing reactive power,

DVRs can maintain voltage levels within acceptable

limits, ensuring reliable and efficient power delivery.

This is especially important in modern power grids

with increasing penetration of renewable energy

sources and sensitive electronic loads (AppalaNaidu,

2016).Fuzzy logic controllers (FLCs) have gained

significant attention from researchers due to their

simplicity and effectiveness in various control

applications, including power converters, motor

drives, and process control. Compared to other

intelligent control techniques(Thaha and Prakash,

2020). FLCs are relatively straightforward to

integrate into systems. This simplicity, coupled with

their ability to provide superior performance

compared to conventional controllers, has made

FLCs a popular choice for a wide range of control

tasks (Elkhateb, Rahim, et al. , 2014).Dynamic

Voltage Restorers (DVRs) often employ Proportional

Integral (PI) controllers to regulate their output.

While effective, PI controllers can be further

optimized by integrating fuzzy logic. Fuzzy logic

enhances the PI controller's adaptability by adjusting

its error and rate of error parameters. This intelligent

approach enables the DVR to perform more

effectively under diverse operating conditions,

surpassing the capabilities of traditional PI controllers

(Saha and Biswas, 2021), (Bhatnagar and Yadav,

2020). A Type-2 fuzzy logic controller is developed

from a Type-1 fuzzy logic controller optimized using

Bee Colony Optimization for engine speed control

(Gurjar, Yadav, et al. , 2020). A shunt active power

filter with a self-tuned harmonic filter and fuzzy logic

controller for harmonic mitigation, reactive power

compensation, and power factor correction (Agrawal,

Sharma, et al. , 2017).

2 PROPOSED DVR

ARCHITECTURE

In a power system, faults can be broadly classified

into two main categories: symmetrical faults and

unsymmetrical faults. Symmetrical faults occur when

all three phases are involved equally, such as a three-

phase fault, which is the most common type of

symmetrical fault. Unsymmetrical faults, on the other

hand, occur when one or two phases are involved.

These include phase-to-ground faults, which occur

when one phase comes into contact with the ground,

phase-to-phase faults, which occur when two phases

come into contact with each other, and phase-to-

phase-to-ground faults, which occur when two phases

come into contact with each other and with the

ground. Additionally, open circuit faults can also

occur, which involve the disconnection of one or

more phases. Each type of fault has distinct

characteristics and effects on the power system, and

understanding these differences is crucial for the

design and operation of protective devices and

systems to detect and clear faults quickly and

efficiently.

Now a days Power distribution lines are crucial

for transmitting electricity over long distances to

consumers. However, these lines are vulnerable to

various hazards, including harsh weather, mechanical

damage, and insulation failure. These factors can lead

to short circuits or shunt faults. Shunt faults can be

classified as symmetrical or unsymmetrical, and

further categorized into ten main types based on the

phases involved (LG, L-L-L, L-L-L-G, L-L). In a

typical power system, faults occur when there is an

abnormal flow of current in an electrical circuit, often

leading to disruptions in power supply and potential

damage to equipment. Accurate and timely detection

of these faults is essential to prevent power outages

and protect connected equipment. Power systems

employ various protection devices, such as relays,

circuit breakers, and fuses to mitigate the impact of

faults. These devices are designed to detect faults,

isolate the affected area, and restore power to the rest

of the system. (Khandakar, Rabbi, et al. , 2024).

Figure 1: Classification of fault in power system

Power System

Fault

Open Circuit

Fault

Short Circuit

Fault

One Conductor

Open

Two Conductor

Open

Three Conductor

Open

Symmetrical

Fault

Unsymmetrical

Fault

Single Line-to-

Ground-Fault

Double Line-to-

Ground Fault

Line-to-Line

Fault

Three Phase

Short Circuit

Fault

Three Phase to

Ground Fault

Fault Detection and Power Quality Compensation Using Fuzzy Logic Based Dynamic Voltage Restorer

107

2.1 Dynamic Voltage Restorer (DVR)

A DVR typically consists of four main components:

an energy storage unit, an injection transformer, a

voltage source inverter, and a filtering section.

The

provided image illustrates the operational principle of

a Dynamic Voltage Restorer (DVR), a power

electronic device used to improve voltage quality in

power systems. The DVR consists of several

components, including a source voltage, impedance,

series injection transformer, the DVR itself, a voltage

source converter (VSC), a harmonic filter, and a load.

Figure 2: Schematic Layout of DVR

The DVR system comprises several key

components. These include a storage device for

energy, an injection transformer to interface with the

power system, a voltage source inverter to control

power flow, and a filter to mitigate harmonic

distortion. As given in Figure 1.Power system

disturbances, such as voltage sags and swells, can

significantly impact the reliability and quality of

power supply. Dynamic Voltage Restorers (DVRs)

are a type of Flexible AC Transmission Systems

(FACTS) device that are designed to mitigate these

voltage fluctuations. This paper delves into the

principles of operation, control strategies, and

applications of DVRs in power systems. The paper

also discusses the advantages and limitations of

DVRs, as well as future trends and challenges in their

implementation (Abas, Dilshad, et al. , 2020).

2.2 Block diagram

Figure 3: Circuit diagram of DVR

The given diagram illustrates a 2-level converter

system, which is a key component in various power

electronic applications. The system comprises a

series R branch, a 2-level converter, and a DC supply.

The series R branch consists of a resistor, which is

crucial for controlling the current flow within the

circuit. The 2-level converter is a power electronic

circuit that converts DC power into AC power,

enabling the efficient transfer of energy.

The DC supply provides the necessary input

voltage for the converter. The diagram also includes

a block labelled "g," which likely represents a control

signal that regulates the operation of the 2-level

converter. The numbered blocks (1, 2, 3) might

indicate different switching states of the 2-level

converter, influencing the output waveform.

Overall, this diagram provides a simplified

representation of a 2-level converter system,

highlighting its key components and their

interactions.

2.3 Operation of DVR

Figure 4: Operation of DVR

The Dynamic Voltage Restorer (DVR) operates

on a fundamental principle: it compensates for

voltage disturbances by injecting a compensating

voltage to maintain the desired load voltage.

Specifically, whenever the source voltage

experiences unbalance or distortion, the DVR injects

a voltage of appropriate magnitude to restore the

load-side voltage to its desired amplitude. In essence,

the primary function of the DVR is to continuously

regulate the load voltage waveform. In the event of a

voltage sag or swell, the DVR injects the necessary

voltage to maintain the desired load voltage at the

point of common coupling. Mathematically, the

principle of DVR operation can be represented by the

following equation, which must always be satisfied.

𝑉

𝑆𝑜𝑢𝑟𝑐𝑒

 𝑉

𝐷𝑉𝑅

𝑉

𝐿𝑜𝑎𝑑

(1)

INCOFT 2025 - International Conference on Futuristic Technology

108

A DVR consists of a voltage source inverter

(VSI), a coupling transformer, and a control system.

The VSI generates a voltage waveform that is injected

into the power system through the coupling

transformer to compensate for voltage fluctuations.

The control system monitors the system voltage and

generates the necessary control signals to regulate the

output voltage of the VSI (Rajesh, Mishra, et al. ,

2023). DVR control strategies involve detecting

voltage sags/swells and injecting compensating

voltages. Common techniques include proportional-

integral (PI) control for its simplicity, and

synchronous PI decoupling for improved linearity.

The control circuit determines the magnitude,

frequency, and phase shift of the injected voltage,

generated by the power circuit. DVRs can

compensate for both balanced and unbalanced

voltage disturbances, ensuring load voltage remains

within acceptable tolerances. Various control

schemes exist, including energy-optimal, in-phase,

and pre-sag compensation, depending on the specific

requirements and load characteristics.

2.4 Control strategies of DVR

DVR control strategies involve detecting voltage

sags/swells and injecting compensating voltages.

Common techniques include proportional-integral

(PI) control for its simplicity, and synchronous PI

decoupling for improved linearity. The control circuit

determines the magnitude, frequency, and phase shift

of the injected voltage, generated by the power

circuit. DVRs can compensate for both balanced and

unbalanced voltage disturbances, ensuring load

voltage remains within acceptable tolerances.

Various control schemes exist, including energy-

optimal, in-phase, and pre-sag compensation,

depending on the specific requirements and load

characteristics (Bhatnagar and Yadav, 2020). DVRs

combined with fuzzy logic offer a robust and

adaptable solution for power quality improvement.

Fuzzy logic controllers excel at handling

uncertainties and non-linearity inherent in power

systems, making them ideal for DVR control. By

employing fuzzy logic, DVRs can effectively

mitigate voltage sags and swells, dynamically adjust

compensation levels based on real-time system

conditions, and improve overall system stability. This

integration enhances the reliability and efficiency of

power distribution networks, safeguarding sensitive

loads and ensuring uninterrupted power

supply(Thaha and Prakash, 2020).

3 PROPOSED METHODOLOGY

3.1 Fuzzy logic internal circuit

Fuzzy logic controllers (FLCs) have gained

significant attention among researchers due to their

ease of integration with various systems and their

ability to deliver superior performance compared to

conventional controllers. FLCs are particularly well-

suited for applications such as converter control,

motor drives, and process control, where their ability

to handle uncertainty and provide flexible control

strategies is advantageous.

Figure 5: Circuit diagram of fuzzy logic

The test framework suggested in this paper is to

simulate the model for the FL Controller as shown in

Fig.4. The figure illustrates a control system for a

power converter, likely a three-phase inverter.

The system appears to employ a fuzzy logic

controller to regulate the output voltage. The control

system includes a reference generation block, a

Discrete Virtual PLL, a fuzzy controller, and a

transformation block to convert between the abc and

dq reference frames.

The Fuzzy Logic Controller (FLC) operates by

evaluating two inputs at every sampling interval:

error and error derivative. These inputs are then

fuzzified using fuzzy set membership functions and

processed through a set of 'if/then' rules to generate

linguistic or verbal variables. The output of the FLC

is a control signal for each phase, which is defuzzied

and used to regulate the signals. These regulated

signals are then compared with a generated carrier

signal to produce gating pulses for the VSI inverter

(Thaha and Prakash, 2020).

Figure 6: Circuit diagram inside fuzzy logic controller 1

Fault Detection and Power Quality Compensation Using Fuzzy Logic Based Dynamic Voltage Restorer

109

The diagram illustrates a basic feedback control

system. The system starts with an "Error" signal,

which is the difference between the desired output

and the actual output. This error signal is then fed into

a summing junction, where it's combined with

another input signal (not explicitly shown). The

resulting combined signal is then processed by a

Fuzzy Inference System (FIS).

Figure 7: Circuit diagram inside fuzzy logic controller 2

Fuzzy logic controllers (FLCs) have gained

significant attention among researchers due to their

ease of integration with various systems and their

ability to deliver superior performance compared to

conventional controllers. FLCs are particularly well-

suited for applications such as converter control,

motor drives, and process control, where their ability

to handle uncertainty and provide flexible control

strategies is advantageous (Elkhateb, Rahim, et al. ,

2014).

3.2 Fuzzy Logic Control

Fuzzy logic provides a robust and flexible

approach to fault detection in power systems.

Figure 8: MATLAB/SIMULINK fuzzy logic base editor

By employing linguistic terms and fuzzy rules, it

can effectively identify fault conditions, such as short

circuits, open circuits, and unbalanced loads, even in

noise and uncertainties. Fuzzy logic-based systems

can analyse parameters like voltage, current, and

power flow to detect anomalies and trigger

appropriate protective actions. Additionally, it can

handle complex fault scenarios and adapt to changing

system conditions, making it a valuable tool for

ensuring the reliability and safety of power systems

(Gurjar, Yadav, et al. , 2020).

Table 1: Rule matrix

The proposed strategy utilizes linguistic variables

like " negative medium (NM)," "negative small

(NS)," "positive small (PS)," "positive medium

(PM),” Zero (ZE)”, "Big negative (BN)," and "Big

positive (BP)" to define the error and its derivative.

These linguistic variables are associated with

membership functions, which are curves that assign a

membership value between 0 and 1 to each point in

the input space (Elkhateb, Rahim, et al. , 2014).

3.3 Power Quality

Dynamic Voltage Restorers (DVRs) are a

powerful tool for improving power quality in

distribution systems. They rapidly inject voltage

waveforms to compensate for voltage sags,

swells, and interruptions, ensuring a stable and

reliable power supply to sensitive loads. DVRs

are particularly effective in mitigating voltage

fluctuations caused by faults, load switching,

and system disturbances. By rapidly responding

to voltage deviations, DVRs significantly

improve the system's overall power quality,

protecting sensitive equipment and improving

the reliability of power supply (Rajesh, Mishra,

et al. , 2023).

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110

4 SIMULATION

To simulate the system, a step load disturbance was

introduced at time 0 to 0.5 second. The simulation

was conducted using MATLAB 2021b-Simulink

software on a computer equipped with an Intel i3 11th

generation processor clocked at 3.00 GHz and 8 GB

of RAM, running Windows 11.

Figure 9: Block diagram of model without DVR

The image depicts a power system with a 3-phase

supply connected to a 3-phase transformer. An LLG

(Line-Line-Ground) fault has occurred somewhere in

the system, represented by the "Fault" block. This

fault creates a direct connection between two phase

conductors and the ground, causing a significant

increase in fault current. The fault disrupts the normal

operation of the loads connected to the system,

including the 3-phase series RLC load and the 3-

phase parallel RLC load. LLG faults can lead to

various consequences, such as damage to equipment,

voltage imbalances, and potential system instability.

Power systems employ various protection schemes,

such as distance protection, differential protection,

overcurrent protection, and ground fault protection, to

detect and isolate LLG faults quickly, minimizing

their impact on the system and ensuring the continuity

of power supply.

Figure 10: Block diagram of model with DVR and fuzzy

logic

The image depicts a power system with a 3-phase

supply connected to a 3-phase transformer. An LLG

(Line-Line-Ground) fault has occurred somewhere in

the system, represented by the "Fault" block. This

fault creates a direct connection between two phase

conductors and the ground, causing a significant

increase in fault current. The fault disrupts the normal

operation of the loads connected to the system,

including the 3-phase series RLC load and the 3-

phase parallel RLC load.

Additionally, the system includes a 12-terminal 3-

phase transformer and a DVR (Dynamic Voltage

Restorer). The DVR is a device used to mitigate the

impact of voltage sags and swells on the system. In

the event of an LLG fault, the DVR can be used to

inject voltage into the system to compensate for the

voltage drop caused by the fault. This can help to

maintain the voltage level at the load and prevent

system instability.

Power systems employ various protection

schemes, such as distance protection, differential

protection, overcurrent protection, and ground fault

protection, to detect and isolate LLG faults quickly,

minimizing their impact on the system and ensuring

the continuity of power supply.

Table 2: Simulink Modelling Parameters

AC Source f

= 50 Hz, R

= 0.2 ohm, L

= .5mH

X-mer 50Hz 11000/400V

Simulation

time

0 to 0.5sec.

RLC Load P= 4.42000 W

= (positive var): 100

(

ative var

)

: 0

Three-Phase

Breaker (link)

Switching times : [0.12 0.14]Sec

: 0.01 Ohm, R

: 1e6 Ohm, C

inf(f)

Block

Parameters:

3-ph

Transformer

12 Terminals

[Three-phase rated power(VA)

Frequency (Hz) = [1.5e3 50]

Winding 1: [V

(Vrms) R(pu)

X(pu)]:

[10 0.00001 0.0003]

Winding 2: [V

(Vrms) R(pu)

X(pu)]:

[100 0.00001 0.0003]

Magnetizing branch: [Rm(pu)

)

]: [200 200]

Three-ph

Source (mask)

(link)

Specify internal voltages for each

phase

: 11000 V

rms

Phase angle of phase A : 0 degrees

Frequency (Hz): 50

5 GRAPHICAL RESULTS AND

DISCUSSION

Experimental and simulation results validate the

effectiveness of the proposed system in mitigating

Fault Detection and Power Quality Compensation Using Fuzzy Logic Based Dynamic Voltage Restorer

111

voltage sags within power systems. Under LG, LLG,

and LLLG fault conditions, the integrated DVR and

PI controller consistently demonstrate rapid and

accurate voltage compensation. Voltage profiles are

swiftly restored to acceptable levels, ensuring the

protection of sensitive loads from disruptions. The PI

controller plays a critical role in optimizing the

DVR's response, dynamically adapting to diverse

fault scenarios through a finely tuned compensation

strategy. The system's ability to maintain stability

during fault occurrences is a significant achievement,

highlighting its reliability for practical applications.

The results section will present the outputs

generated by the simulation under various fault

conditions. These outputs have been integrated into a

single body of work to address the simulation's scope

comprehensively.

5.1 With LLG fault

Figure 11: L-L-G Fault Current & Voltage Waveform

5.2 With LLL fault

Figure 12: L- L-L Fault Current & Voltage Waveform

5.3 With LG fault

Figure 13: L-G Fault Current & Voltage Waveform

This power system model focuses on an L-G fault,

representing a single-line-to-ground fault. To

enhance waveform readability, the simulation

duration is set. Assuming a 50 Hz sampling

frequency, the system base voltage for the three-

phase source. Three 3-phase VI measurement blocks

are incorporated within the system. Upon fault

occurrence, the differential relay, with both inputs

connected to the current parameter, detects the abrupt

current surge. This triggers the circuit breaker to

open, isolating the fault i.e., a transient condition. The

waveforms in both figures exhibit a characteristic

spike during the fault. As is well-known, generators

operate asynchronously. However, a rapid fault leads

to an increase in speed and a corresponding current

rise. Concurrently, a significant voltage drop,

approaching zero, and waveform interruptions are

observed during the fault. Similar behaviour is

expected for other fault types.

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6 CONCLUSION

This presented work focuses on fault identification

and detection using MATLAB Simulink for a 3-bus

power system employing a fuzzy logic controller and

dynamic voltage regulator (DVR). Considering LG,

LLG and LLL faults, a Simulink model is made and

waveforms are obtained.The major problem of power

quality disruptions in modern power networks,

namely voltage swells and sags. Strong solutions

must be used to ensure a consistent and dependable

power supply due to the growing dependence on

delicate electronic devices. In order to do this, this

study suggested a novel method that makes use of

Dynamic Voltage Restorers (DVRs) controlled by

Fuzzy Logic (FL) in a composite microgrid system.

The efficiency of the suggested FL-based DVR

controller in reducing voltage disturbances was

shown by the simulation results produced with

MATLAB 2021. The FL controller performed better

in terms of speed and efficiency than conventional

control techniques. The intrinsic capacity of FL to

manage the uncertainties and nonlinearities present in

actual power systems is responsible for this improved

performance.

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