Senior Member at Amirkabir University of Technology – PEDAR Group, Iran📖
Dr. Mehdi Zareian Jahromi is a distinguished Power Electrical Engineer specializing in power microgrid control, energy storage systems, and renewable energy integration. With extensive experience in research, technical consulting, and academia, he has contributed significantly to power system stability, distributed generation, and software development for power grid optimization. As a visiting researcher at Amirkabir University of Technology, he has led numerous projects in real-time transient stability assessment and microgrid energy management. Dr. Jahromi has received multiple awards, including Distinguished Lecturer, Exceptional Talent Student, and National Innovation Prizes, reflecting his leadership in power engineering research and education.
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Education Background🎓
- Ph.D. in Power Electrical Engineering, Amirkabir University of Technology, Tehran, Iran (2012-2017)
- Distinguished Student Award
- Thesis: Real-time Transient Stability Assessment of Large-Scale Power Systems including Renewable Energies
- M.Sc. in Power Electrical Engineering, Graduate University of Advanced Technology, Kerman, Iran (2010-2012)
- Top Researcher Award
- Thesis: Simulation of a Stirling Engine Solar Power Generation System Using Simulink
- B.Sc. in Power Electrical Engineering, Shahid Bahonar University, Kerman, Iran (2006-2010)
- First-Ranked Student
- Project: Unit Commitment Using Neural Networks
Professional Experience🌱
Dr. Jahromi has held multiple leadership and technical roles across research institutes, academia, and the energy industry, contributing to microgrid stability, smart grid optimization, and power system software development:
- Head of Power Electrical Advanced Research Group (PEDAR Group – PowerMatlab) (2016–Present)
- Leads modeling and simulation of large-scale power systems with renewable energy integration.
- Visiting Researcher, Amirkabir University of Technology (2019-2023)
- Developed security and stability indices for real-time power grid software (POUYA).
- Senior Software Developer, Amirkabir University of Technology (2012-2022)
- Worked on real-time transient stability assessment software for power microgrids.
- Visiting Researcher, Shiraz University (2017-2018)
- Designed real-time transient stability systems for power microgrids.
- Senior Technical Consultant, Dana Noavaran Energy & Industry Company (2014-2016)
- Led solar energy optimization projects and photovoltaic system software development.
- Head of Electrical Department, Naghshejahan University (2013-2016)
- Taught courses in power system analysis, power electronics, and distributed generation.
- Technical Support Expert, Niroo Research Institute (2012-2014)
- Managed power transformer life cycle planning and optimization.
- Technical Consultant, Tavanir (2010-2012)
- Provided training on power market and risk management.
- Technical Consultant, Kerman Electricity Distribution Company (2009-2010)
- Developed strategic plans for loss management in distribution networks.
Research interests include:
- Power Microgrid Control & Smart Grids
- Energy Storage Systems & Renewable Integration
- Stability and Security Assessment of Power Systems
- Optimal Power Management & Distributed Generation
- Power Electrical Software Development & AI-Based Grid Optimization
Author Metrics
Publications Top Notes 📄
1. An Approach to Power Transformer Asset Management Using Health Index
- Authors: M.Z. Jahromi, R. Piercy, S. Cress, J. Service, W. Fan
- Journal: IEEE Electrical Insulation Magazine
- Volume: 25 (2), Pages: 20-34
- Year: 2009
- Citations: 547
- DOI: [Available via IEEE Xplore]
- Summary:
This paper presents a health index-based method for power transformer asset management, helping utilities make informed maintenance and replacement decisions. The approach integrates multiple diagnostic indicators, ensuring enhanced reliability and cost-effective power grid operation.
2. An Analytical Approach for Removal of Decaying DC Component Considering Frequency Deviation
- Authors: M. Tajdinian, M.Z. Jahromi, K. Mohseni, S.M. Kouhsari
- Journal: Electric Power Systems Research
- Volume: 130, Pages: 208-219
- Year: 2016
- Citations: 44
- DOI: [Available via ScienceDirect]
- Summary:
This study proposes an analytical technique to eliminate the decaying DC component in power signals, considering frequency deviation. The method enhances protection relay accuracy and improves fault detection and system stability.
3. Optimum Design, Simulation, and Test of a New Flow Control Valve with an Electronic Actuator for Turbine Engine Fuel Control System
- Authors: S.M. Agh, J. Pirkandi, M. Mahmoodi, M. Jahromi
- Journal: Flow Measurement and Instrumentation
- Volume: 65, Pages: 65-77
- Year: 2019
- Citations: 34
- DOI: [Available via Elsevier]
- Summary:
This paper introduces a novel flow control valve with an electronic actuator for turbine engines, improving fuel efficiency, response time, and reliability. The simulation and experimental validation demonstrate the system’s enhanced performance for aerospace applications.
4. Classification of Power Quality Disturbances Using S-Transform and TT-Transform Based on the Artificial Neural Network
- Authors: S. Jashfar, S. Esmaeili, M.Z. Jahromi, M. Rahmanian
- Journal: Turkish Journal of Electrical Engineering and Computer Sciences
- Volume: 21 (6), Pages: 1528-1544
- Year: 2013
- Citations: 34
- DOI: [Available via TÃœBÄ°TAK]
- Summary:
This research applies artificial neural networks (ANNs) to detect and classify power quality disturbances. The hybrid S-transform and TT-transform techniques enhance classification accuracy, making it valuable for smart grids and fault diagnosis systems.
5. Mitigating Voltage Sag by Optimal Allocation of Distributed Generation Using Genetic Algorithm
- Authors: M. Zareian Jahromi, E. Farjah, M. Zolghadri
- Conference: 9th International Conference on Electrical Power Quality and Utilisation (EPQU)
- Year: 2007
- Citations: 33
- DOI: [Available via IEEE Xplore]
- Summary:
This study utilizes Genetic Algorithm (GA) optimization to determine the optimal placement of distributed generation (DG) for voltage sag mitigation. The proposed strategy improves power quality, voltage stability, and system reliability.
Conclusion
Dr. Mehdi Zareian Jahromi is a highly deserving candidate for the Best Researcher Award due to his exceptional contributions to power system resilience, microgrid optimization, and energy storage technologies.
His high-impact research, technical leadership, and innovative solutions have significantly influenced network resilience, grid security, and power quality enhancement. With continued industry collaboration, AI integration, and global partnerships, his work can further transform modern energy infrastructure and smart grid reliability.
This nomination is strongly recommended based on his groundbreaking research, technical expertise, and leadership in electrical engineering and power systems.