INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
MANAGEMENT & APPLIED SCIENCE (IJLTEMAS)
ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue X, October 2025
www.ijltemas.in Page 900
Power Quality Improvement in Distribution Networks Using
Advanced Power Electronic Transformer Topologies
1 Nikhil Mudgal, 1 Arvind Kumar, 1 Sharad Kumar, 2 Vikas Sharma
1 School of Engineering & Technology, Shri Venkateshwara University, Gajraula , U.P. India
2 Department of Computer Applications, SRM Institute of Science and Technology, Delhi NCR Campus, Ghaziabad, U.P.
India
DOI: https://doi.org/10.51583/IJLTEMAS.2025.1410000109
Abstract—The growing integration of renewable energy sources, nonlinear loads, and distributed generation has posed
significant challenges to maintaining power quality in modern distribution networks. Conventional transformers, though reliable,
lack the flexibility to mitigate issues such as voltage sag/swell, harmonics, unbalance, and reactive power disturbances. This
paper presents a comprehensive study on the application of Advanced Power Electronic Transformer (PET) topologies for
enhancing power quality in distribution systems. The proposed PET architecture incorporates multi-level converter stages with
bidirectional power flow control, enabling dynamic voltage regulation, harmonic compensation, and load balancing. Simulation
models are developed in MATLAB/Simulink to evaluate the performance of modular PET configurations under varying load and
grid conditions. Comparative analysis with traditional transformer systems demonstrates significant improvements in voltage
profile, total harmonic distortion (THD), and system efficiency. The study highlights the potential of PET-based solutions as a
next-generation approach for intelligent, reliable, and sustainable distribution network operation.
Keywords—Power Electronic Transformer (PET), Distribution Networks, Voltage Regulation, Harmonic Compensation,
Reactive Power Control, Multilevel Converters, MATLAB/Simulink Simulation, Smart Grid.
I. Introduction
The modern power distribution network is undergoing a paradigm shift due to the rapid proliferation of distributed energy
resources (DERs), electric vehicles, and nonlinear electronic loads. These developments, while enhancing the overall efficiency
and flexibility of power systems, have also introduced significant challenges related to power quality (PQ). Issues such as voltage
fluctuations, harmonic distortion, flicker, and unbalanced loading have become more prevalent, affecting both end-user
equipment and grid reliability. Traditional distribution transformers, although robust and widely deployed, are inherently limited
by their passive magnetic structure and inability to respond dynamically to fast-changing load and supply conditions.
Consequently, there is a growing need for intelligent and adaptive power conversion devices that can simultaneously perform
voltage regulation, isolation, and power conditioning functions to ensure improved power quality and system stability. In this
context, Power Electronic Transformers (PETs)—also referred to as Solid-State Transformers (SSTs)—have emerged as a
revolutionary advancement in modern power systems. Unlike conventional transformers that rely solely on magnetic coupling for
voltage transformation, PETs employ high-frequency power electronic converters to achieve voltage conversion, galvanic
isolation, and bidirectional power flow control. This enables them to operate not only as voltage step-up/step-down devices but
also as active power quality conditioners. The incorporation of high-frequency isolation significantly reduces size and weight
while improving system response and controllability. Moreover, PETs can be integrated with communication and control
modules, enabling smart functionalities such as grid monitoring, fault detection, and real-time voltage compensation, which are
crucial for the operation of smart grids and microgrids. One of the most critical aspects of PET technology is its ability to
mitigate power quality disturbances effectively. By utilizing advanced converter topologies—such as dual-active bridge (DAB),
modular multilevel converter (MMC), and cascaded H-bridge (CHB)—PETs can perform harmonic elimination, reactive power
compensation, and voltage stabilization. These converters, when controlled through optimized modulation and feedback
strategies, ensure sinusoidal current injection and balanced voltage profiles at both grid and load sides. Furthermore, PETs
facilitate seamless integration of renewable energy sources such as photovoltaic (PV) systems and wind turbines by providing a
stable interface that manages voltage fluctuations and harmonics inherent in renewable power generation. This capability makes
PETs an essential enabler for achieving a sustainable, efficient, and resilient power distribution network. The ongoing research on
PET topologies has shown promising results in improving system performance and efficiency. The modular design of PETs
allows for scalability and redundancy, which enhances fault tolerance and ease of maintenance. Their ability to decouple the
primary and secondary sides enables independent control of power flow and voltage levels, contributing to improved voltage
stability, power factor correction, and energy efficiency shown in Fig. 1. Additionally, PETs can actively filter out unwanted
harmonic components and compensate for load unbalances, thus minimizing stress on other grid components.
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue X, October 2025
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Fig. 1. Power Distribution Network Architecture
The control algorithms associated with PET operation—such as model predictive control (MPC) and adaptive hysteresis current
control—further refine the dynamic response and enhance system robustness under transient conditions. This paper focuses on
the analysis, design, and performance evaluation of advanced PET topologies for power quality enhancement in distribution
networks. It explores various converter configurations, control techniques, and simulation models to demonstrate the potential of
PETs in mitigating common PQ issues. Using MATLAB/Simulink-based modeling, the paper examines the operational
characteristics of modular PET architectures under diverse load and grid scenarios. A comparative assessment is presented
between conventional transformer-based and PET-based systems in terms of total harmonic distortion (THD), voltage regulation,
and overall system efficiency. The study emphasizes the crucial role of PETs in achieving reliable, adaptive, and intelligent
distribution systems that meet the growing demands of modern energy infrastructures.
II. Literature Review
Power quality improvement in modern distribution networks has gained significant research attention with the growing integration
of distributed generation, electric vehicles, and nonlinear loads. Numerous studies have explored advanced control strategies,
optimization techniques, and power electronic topologies to enhance voltage stability, reduce losses, and mitigate harmonic
distortions. Peng and Xiao [1] investigated the impact of power quality degradation in rural distribution networks and proposed an
analytical approach to simultaneously enhance network efficiency and minimize losses. Their study emphasized optimizing
reactive power and controlling voltage variations, showing that coordinated compensation strategies significantly improve both
voltage stability and loss reduction in low-voltage rural grids. Du et al. [2] provided a comprehensive review of advancements
in power quality analysis for electrical distribution systems, emphasizing the role of signal processing and artificial intelligence in
identifying disturbances. Their work highlighted the integration of real-time monitoring and data-driven models for effective fault
detection and mitigation, paving the way for adaptive control systems in modern smart grids. Guan et al. [3] proposed a distributed
energy optimization framework for improving multi-dimensional power quality. Their approach integrated renewable energy
resources and distributed energy storage, focusing on optimizing energy flow and voltage profiles. Simulation results demonstrated
a marked improvement in harmonic suppression and load balancing through intelligent distributed energy coordination. Vikas et al.
[4] introduced a hybrid deep belief network optimized with a Harris Hawks algorithm for intrusion detection in wireless sensor
networks. Although primarily applied in cybersecurity, their hybrid optimization technique demonstrates potential applicability
in intelligent fault detection and anomaly monitoring within distribution networks. Lari et al. [5] presented a seven-level common
ground inverter topology designed to improve power quality in distribution systems. Their proposed multilevel inverter
configuration significantly reduced total harmonic distortion (THD) and improved DC-link voltage utilization, providing a practical
foundation for implementing power electronic transformers in distribution networks. Recent developments in artificial intelligence
have further influenced power system optimization. A 2025 study on graph neural network optimization for real-time intrusion
detection [6] showcased how adaptive AI models can enhance decision-making and operational security in dynamic systems,
potentially benefiting AI-based fault management in power networks. Gultom et al. [7] examined the Unified Power Quality
Conditioner (UPQC) as a control strategy for mitigating harmonics and voltage fluctuations in distribution networks. Simulation-
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
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ISSN 2278-2540 | DOI: 10.51583/IJLTEMAS | Volume XIV, Issue X, October 2025
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based results verified that UPQC enhances voltage stability and ensures reliable power delivery under varying load conditions,
marking it as a key technology for integrated PQ improvement. A 2025 study on mobile ad hoc network security mechanisms [8]
emphasized the need for robust communication and control layers in distributed energy systems. While primarily focusing on
networking, its insights into secure communication protocols can be applied to IoT-enabled power distribution monitoring for data
integrity assurance. Chen et al. [9] investigated key technologies for improving power supply reliability in next-generation
distribution networks, emphasizing system redundancy, self-healing capabilities, and predictive maintenance. Their findings
underline the importance of integrating intelligent electronic devices (IEDs) with distributed control to enhance system robustness.
Sharma and Kumar [10] discussed the role of artificial intelligence (AI) in improving security and privacy in smart cities. Their
study linked data-driven intelligence with secure decision frameworks, relevant to safeguarding power quality control data and
maintaining integrity within interconnected grids. Xia et al. [11] conducted an economic evaluation of power electronic reactive
compensation systems integrated with electric vehicle loads. The results indicated that advanced compensation devices not only
stabilize reactive power but also provide cost-effective benefits for EV-integrated networks, making them vital for sustainable
distribution system design. Finally, Liang et al. [12] proposed a voltage regulation strategy for medium and low-voltage networks
using power electronic converters. Their work emphasized dynamic control algorithms that adjust reactive power flow in real time,
ensuring stable voltage profiles and improved power quality across diverse operating conditions.
III. Proposed Methodology
The proposed methodology aims to design and implement an Advanced Power Electronic Transformer (PET) system for
improving power quality in distribution networks. The approach integrates PET topology selection, control system design,
MATLAB/Simulink modeling, and performance evaluation. The methodology is divided into several key phases as described
below.
1. System Modeling of Distribution Network: The study begins with modeling a typical three-phase AC distribution
network containing both linear and nonlinear loads. The nonlinear loads, such as diode rectifiers and variable frequency drives
(VFDs), introduce significant harmonic distortions and voltage fluctuations into the system. These disturbances serve as the
baseline for evaluating the impact of the proposed PET system. The distribution feeder model simulates real-world grid
conditions, including voltage sags, swells, unbalanced loading, and harmonic pollution. The modelled system operates at a
nominal voltage of 11 kV and supplies load ratings ranging between 5 kW and 20 kW. Various operating scenarios are simulated
to examine voltage regulation and harmonic compensation performance before and after the integration of the proposed PET.
2. Selection of Advanced PET Topology: The proposed PET structure is based on a Modular Multilevel Converter
(MMC) topology, chosen for its modularity, scalability, and superior harmonic performance. The PET is divided into three major
functional stages:
Input Rectifier Stage: Converts the incoming low-frequency AC voltage from the grid into a regulated DC link voltage.
High-Frequency Isolation Stage: Employs a Dual Active Bridge (DAB) converter that operates at high frequency,
providing galvanic isolation and step-up/step-down voltage transformation.
Output Inverter Stage: Converts the DC link voltage back into AC for the load with required magnitude and frequency
control.
This configuration reduces transformer core size, enhances transient response, and enables bidirectional power flow, allowing the
PET to perform both voltage regulation and harmonic filtering simultaneously.
3. Control Strategy and Algorithm Design: An adaptive control mechanism is employed to ensure that the PET maintains the
desired power quality under variable load conditions. The control system comprises two main control loops:
Outer Voltage Control Loop: Maintains constant output voltage by comparing the reference voltage with the measured
load voltage. A Proportional-Integral (PI) controller adjusts the modulation index to stabilize voltage fluctuations.
Inner Current Control Loop: Ensures sinusoidal current flow and suppresses harmonic distortion. A Space Vector
Modulation (SVM) technique is implemented to improve switching efficiency and dynamic response.
Additionally, a synchronous reference frame (dq)–based harmonic compensation algorithm is applied to identify and mitigate
current harmonics generated by nonlinear loads. This adaptive control strategy enables real-time compensation for voltage
sag/swell, reactive power imbalance, and harmonic distortion.
4. MATLAB/Simulink Model Implementation: The proposed PET system and distribution network are simulated in
the MATLAB/Simulink environment using the Sim Power System toolbox. Key system components include IGBT-based
converter modules, high-frequency transformers, and digital controllers for real-time signal processing. Simulation parameters
include:
Input Voltage: 11 kV (AC)
Load Range: 5–20 kW
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
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Switching Frequency: 10 kHz
Sampling Time: 50 µs
Different operational scenarios—such as load unbalance, harmonic distortion, and transient voltage conditions—are tested to
analyze system stability and compensation effectiveness.
IV. Result & Analysis
The performance of the proposed Modular Multilevel Converter (MMC)–based Power Electronic Transformer (PET) system was
analyzed through detailed MATLAB/Simulink simulations under various operating conditions. The study focused on four major
performance indicators: Voltage Regulation, Total Harmonic Distortion (THD), Power Factor (PF), and System Efficiency. The
results were compared against those of a conventional transformer-based distribution system to evaluate the effectiveness of the
proposed PET configuration.
1. Voltage Regulation Analysis: The PET-based system demonstrated superior voltage regulation performance compared to the
conventional transformer. By employing adaptive control and high-frequency isolation, the PET maintained voltage variations
within ±2% of the nominal value, whereas the conventional system exhibited up to ±6% deviation under varying load conditions.
Voltage Regulation Performance Comparison
System Type Voltage Regulation (%)
Conventional
Transformer
5.6
Proposed PET System 1.8
Table I. compares voltage regulation performance between a conventional transformer and the proposed PET system, showing
that the PET provides much tighter voltage control (1.8%) compared to 5.6% in the conventional setup.
Fig. 2. Fake Review and News Workflow
Fig. 2. comparing voltage regulation percentages of both systems, illustrating that the proposed PET system achieves significantly
lower voltage regulation deviation than the conventional transformer.
2. Harmonic Distortion Analysis: Harmonic reduction is a key objective in power quality improvement. The PET system
achieved significant THD reduction due to its advanced modulation technique and dq-based harmonic compensation. The THD
was reduced from 11.2% (conventional) to 3.4% (PET), remaining within IEEE-519 standard limits.
Voltage Regulation Performance Comparison
System Type THD (%)
Conventional
Transformer
11.2
Proposed PET System 3.4
Table II. shows that the proposed PET system reduced total harmonic distortion from 11.2% to 3.4%, meeting IEEE standards for
power quality.
INTERNATIONAL JOURNAL OF LATEST TECHNOLOGY IN ENGINEERING,
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Fig. 3. Fake Review and News Workflow
Fig. 3. illustrating THD levels for both systems, clearly showing the proposed PET system’s superior harmonic mitigation
capabilities compared to the conventional transformer.
3. Power Factor Improvement: The adaptive control mechanism of the PET effectively compensates for reactive power, leading
to an improved power factor close to unity. The simulation results indicate an increase in PF from 0.89 in the conventional setup
to 0.98 with the PET.
Voltage Regulation Performance Comparison
System Type Power Factor
Conventional Transformer 0.89
Proposed PET System 0.98
Table III. compares power factor values, indicating that the proposed PET system enhances reactive power compensation and
achieves near-unity power factor operation.
Fig. 4. Fake Review and News Workflow
Fig. 4. capabilities compared to the conventional transformer. comparing the power factor of both systems, showing the PET’s
superior reactive power control resulting in improved system efficiency and stability.
4. System Efficiency Evaluation: The overall system efficiency improved significantly with the PET due to reduced harmonic
losses and optimized switching control. The proposed PET achieved an efficiency of 96.8%, outperforming the conventional
transformer’s 91.5%.
Voltage Regulation Performance Comparison
System Type Efficiency (%)
Conventional Transformer 91.5
Proposed PET System 96.8
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Table IV. presents the efficiency comparison, where the proposed PET exhibits approximately 5.3% higher efficiency than the
conventional transformer.
Fig. 5. Fake Review and News Workflow
Fig. 5. displaying the efficiency comparison of both systems, highlighting that the proposed PET achieves higher energy
conversion efficiency due to reduced harmonic losses and optimized control.
V. Conclusion
In this study, an advanced Modular Multilevel Converter (MMC)-based Power Electronic Transformer (PET) topology was
proposed and analyzed for power quality enhancement in modern distribution networks. The simulation results clearly
demonstrated that the PET system significantly improves voltage regulation, reduces total harmonic distortion (THD), enhances
power factor, and increases overall system efficiency compared to conventional transformer-based configurations. The integration
of high-frequency isolation, adaptive control strategies, and dq-based harmonic compensation enables dynamic and intelligent
control over power flow and voltage stability, making PETs highly suitable for smart grid and renewable energy
integration applications. Future work will focus on hardware implementation of the proposed PET design to validate its real-time
performance under variable load conditions, as well as exploring AI-driven predictive control and IoT-based
monitoring frameworks to further enhance operational reliability, fault diagnosis, and autonomous optimization of power
distribution systems.
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