Nauman Memon

Nauman Ali Memon

M.E. POWER SYSTEMS

Smart Grids FACTS & STATCOM Renewables

Bridging Dynamic Grid Stability with Advanced Power Electronics

Research Assistant, Smart Grids and High Voltages Sukkur IBA University

Electrical Engineer with an M.E. in Electrical Power Systems (CGPA 3.61/4.0) and hands-on experience across smart grids, STATCOM-based power quality enhancement, SCADA operations, and renewable energy systems. Currently serving as a Research Assistant at the Department of Electrical Engineering, Sukkur IBA University (Jan 2026 – Present), conducting research on reinforcement learning-based STATCOM control for power quality improvement in renewable-rich community microgrids.

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Core Research & Methods

  • Reinforcement Learning STATCOM Control
  • SSSC Cross-Border Power Flow Optimization
  • SCADA & High-Voltage Grid Station Ops
  • Coordinated DG & Shunt Reactor Placement

Engineering Toolchain

  • MATLAB / Simulink & Simscape Electrical
  • PSS/E (Power System Simulator)
  • Python & C++ Modeling
  • NI LabVIEW, MultiSim & Design-Expert

Research Publications

Peer-reviewed publications and conference submissions addressing modern power grid stability, STATCOM control, and series compensation.

Peer-Reviewed & Published

Mitigating Fault Currents and Overloads via Coordinated DG and Reactor Placement

Published

Nauman Ali Memon, Hafiz Mudassir Munir, Mohammad R. Altimania, Fares Suliaman Alromithy, Sajad Ali, and Abdul Wajid

2025  •  9th International Conference on Power and Energy Engineering (ICPEE)  •  pp. 258–263

Formulated and validated an optimization-based strategy for coordinated placement of distributed generation and reactors to mitigate fault currents and overloads on a 132 kV meshed network using PSS/E.

Network132 kV · 9 bus
Generation2 DG units
Control2 reactors
Case GBest balance
5.0 → 2.4 MW active losses11.5 → 4.2 MVAR reactive losses210% → 108% peak loading±5% voltage band
View on IEEE DOI
Distributed Generation Shunt Reactors Fault Mitigation PSS/E 132 kV Meshed Network

Submitted & Under Review

Thesis Defense Document Scheme

Reinforcement learning-assisted control strategies for STATCOM in renewable-rich microgrid environments.

Reinforcement Learning-Assisted STATCOM for Power Quality Enhancement in Renewable-Rich Community Microgrids
Researcher: Nauman Memon Supervisor: Dr. Hafiz Mudassir Munir Sukkur IBA University 2024 to Present

Core Microgrid Challenges

1. Dynamic Power & Renewable Volatility: Community microgrids suffer from severe voltage and frequency deviations due to high integration of intermittent solar PV, wind generators, and volatile localized loading profiles.

2. Harmonic Distortion & Fixed-Gain Limitations: Non-linear power electronic loads degrade overall power quality. Conventional fixed-gain PI controllers in standard FACTS devices struggle to adapt rapidly to topological shifts and load dynamics.

Research Objectives

1. Adaptive RL-Based Outer Loop: Designing and training a reinforcement learning agent to dynamically modulate reactive power injection without requiring exact mathematical model parameterization.

2. Real-Time Power Quality Regulation: Mitigating voltage sags, swells, and harmonics in real time under abrupt generation and load variations typical of decentralized networks.

3. Comparative Assessment: Benchmarking against classical PI-controlled STATCOM configurations to demonstrate superior settling time, overshoot suppression, and THD compliance.

Simulation & Modeling Specifications

Simscape
MATLAB Engine
RL Agent
Adaptive Control
d-q Frame
Vector Control
Microgrid
Renewable Integration

The model implements dynamic decoupled vector control loops in the synchronized d-q reference frame. The reinforcement learning agent dynamically coordinates reactive current injection and DC-link capacitor voltage regulation to maintain grid-compliant voltage profiles under steep renewable ramps.

Academic References

Research advisors and faculty members at Sukkur IBA University, Department of Electrical Engineering.

Dr. Hafiz Mudassir Munir

Assistant Professor & Supervisor

Department of Electrical Engineering

Sukkur IBA University

Email Advisor

Dr. Qasim Ali

Assistant Professor

Department of Electrical Engineering

Sukkur IBA University

Email Professor

Dr. Ghulam Akbar

Assistant Professor

Department of Electrical Engineering

Sukkur IBA University

Email Professor

Education

Jan 2024 to Present

Master of Engineering (M.E.), Electrical Power Systems

Sukkur IBA University, Sukkur, Pakistan | Grade: 90% (3.61/4.0 CGPA)

Thesis: Reinforcement Learning-Assisted STATCOM for Power Quality Enhancement in Renewable-Rich Community Microgrids.

Aug 2018 to Dec 2022

Bachelor of Engineering (B.E.), Electrical Engineering

Sukkur IBA University, Sukkur, Pakistan | Grade: 81.75%

Focused on power systems, electrical machines, protection, control, and renewable energy systems.

Honors & Awards

  • First Prize, IEEE SCONEST-22 Conference – Sukkur IBA University (Nov 2022) for best abstract presentation on biogas production optimization from campus waste.
  • Accepted as Leadership Candidate – Aspire Institute, founded at Harvard University, USA (Jan 2023).

Leadership & Volunteering

Jul 2021 to Jun 2022

General Secretary

Sukkur IBA Students' Council (SISC), Sukkur, Pakistan

Elected by over 2,500 students; contributed to policy-making, event management, and student governance at university level.

Technical Skills

Simulation & Software
MATLAB Simulink PSS/E NI LabVIEW NI Multisim EAGLE PCB AutoCAD 2D/3D SolidWorks Design-Expert OriginPro
Power Systems & Domain
SCADA Systems STATCOM SSSC FACTS Devices Smart Grid Design Renewable Integration Power Quality Analysis Protection & Control Transmission Line Analysis Distributed Generation Wind Turbines Load Flow Analysis
Programming & Research
Python C++ Reinforcement Learning Optimization Dynamic Simulation IEEE Technical Writing

Work Experience

Jan 2026 to Present

Research Assistant, Smart Grids and High Voltages

Sukkur IBA University, Department of Electrical Engineering, Sukkur, Pakistan

• Conducting research on reinforcement learning-based STATCOM control for power quality improvement in renewable-integrated microgrids.
• Developing and validating simulation models in MATLAB/Simulink for dynamic grid analysis.
• Supporting high-voltage laboratory experiments and graduate-level research activities.

Sep 2024 to Jul 2025

Subject Specialist, Physics

School of Excellence, Sukkur, Pakistan

• Delivered physics instruction with emphasis on applied concepts and analytical problem-solving.
• Designed curriculum aligned with national board standards and integrated practical demonstrations.

Jun 2024 to Aug 2024

Management Trainee Engineer, Wind Generators

Zorlu Electric Pvt. Ltd., Jhimpir, Sindh, Pakistan

• Operated and monitored SCADA systems for a 56.4 MW wind power plant, ensuring real-time control and performance tracking.
• Gained hands-on experience with VESTAS V90 and VENSYS 62 wind turbine generators (gearboxes, transformers, control panels, yaw motors, slip rings).
• Worked in high-voltage grid station environments (20 kV to 132 kV) and MV rooms, handling feeders and power distribution.

Aug 2023 to May 2024

Subject Specialist, Electrical and Electronics

Directorate of IBA Community Colleges and Schools, Naushahro Feroze, Pakistan

• Taught Power Systems, Electronics, and Python programming to over 150 DAE and Associate Degree students.
• Developed and executed curriculum plans covering transmission, distribution, protection, and Python.
• Integrated hands-on laboratory projects to strengthen real-world problem-solving skills.

Dec 2022 to Jan 2023

Protection and Inspection Intern

Sukkur Electric Power Company (SEPCO), Sukkur, Pakistan

• Assisted in annual maintenance of a 132/11 kV grid station including transformer oil changes, Megger testing, CNDF testing, and bus bar maintenance.
• Conducted circuit breaker timing tests and relay tripping/closing tests to verify system reliability.

Key Projects

RL-Assisted STATCOM Control

Developing an adaptive RL control strategy for STATCOM to enhance power quality in renewable microgrids.

M.E. Thesis (2024 – Present)
SSSC Power Transfer Enhancement

Modeled and simulated a Static Synchronous Series Compensator for power flow control across a 275 kV interconnection.

2025 – 2026
STATCOM Voltage Profile Enhancement

Simulated and validated STATCOM placement strategies to improve voltage stability along a 275 kV transmission corridor.

2025 – 2026
Coordinated DG & Reactor Placement

Optimization strategy for DG and reactor placement to mitigate fault currents. Published at IEEE ICPEE 2025.

Published 2025
Series Compensation for Voltage Regulation

Implemented frequency/voltage control, series compensation, and overcurrent protection; analyzed behavior via SCADA.

2022
Optimization of Biogas Production

Optimized anaerobic digestion of campus organic waste using Design-Expert and OriginPro. Awarded Best Presentation.

B.E. Final Year Project

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