Dr. Ali Ihsan Aygun, Duzce University, Turkey
Dr. Ali Ihsan Aygun is an Assistant Professor at Duzce University, Turkey, specializing in β‘power systems and smart grids. He earned his PhD in Electrical and Computer Engineering from the University of North Carolina at Charlotte πΊπΈ with a perfect GPA of 4.00. His research focuses on electric vehicle charging optimization, smart grid control, and energy efficiency ππ. He has published extensively in prestigious IEEE journals and conferences π. Dr. Aygun is proficient in tools like Matlab, Simulink, and Python π§ π». His international academic background and impactful innovations make him a leading voice in next-generation energy systems
Publication Profile
Google Scholar
π Education Background
Dr. Ali Ihsan Aygun holds a PhD in Electrical and Computer Engineering from the University of North Carolina at Charlotte πΊπΈ, completed in December 2022 with a perfect GPA of 4.00 π§ . He earned his MS in the same field from George Washington University, Washington DC, in 2018 with a GPA of 3.33 π. Prior to that, he began a second MS at YΔ±ldΔ±z Technical University πΉπ· but chose to pursue international opportunities. He also completed his BSc in Electrical and Electronic Engineering from YΔ±ldΔ±z Technical University in 2014, graduating
πΌ Professional Experience
Dr. Ali Ihsan Aygun is currently serving as an Assistant Professor at Duzce University πΉπ· since February 2022, teaching and researching in Power Systems and Smart Grids β‘. Previously, he was a Graduate Research Assistant at UNCC πΊπΈ, where he developed smart charging algorithms, hybrid EV routing systems ππ, and hardware testbeds for microgrid applications. As a Teaching Assistant, he supported courses like Logic and Network Lab and Network Theory π. Earlier, he worked as a Project Manager at Heper Moonlight Corp in Istanbul, managing lighting projects using Dialux and AutoCAD
π¬ Research Focus
Dr. Ali Ihsan Aygun’s research is centered on Electric Vehicles (EVs) ππ, Smart Grids β‘, and Power System Optimization π. His work emphasizes developing intelligent charging algorithms, real-time energy management, and decentralized EV fleet control to enhance grid reliability and operational efficiency π§ π. He is also involved in microgrid technologies, frequency regulation, and dynamic speed optimization within EV infrastructure πβοΈ. With contributions to IEEE journals and global conferences, Dr. Aygun focuses on making energy systems more sustainable, scalable, and smart through advanced computational and control methods
Publication Top Notes
π Centralized Charging Approach to Manage Electric Vehicle Fleets for Balanced Grid β Cited by: 10 π | Year: 2022 π
π Inverter-Angle-Induced Optimized Frequency Regulation Approach for ACβDC Microgrids β Cited by: 7 π | Year: 2022 π
π Optimal Hybrid Management of EV Fleet Charging & Load Scheduling β Cited by: 4 π | Year: 2024 π
π Two-Stage Optimal EV Charging Methodology with Aggregators β Cited by: 3 π | Year: 2024 π
π Optimal Approach to Manage EV Fleets Routing β Cited by: 3 π | Year: 2022 π
π ADMM-Based Optimal EV Fleets Charging in Active Distribution Network β Cited by: 2 π | Year: 2022 π
π Smart Charging Algorithms for EVs: Addressing Grid Stress β Year: 2024 π
π Distributed Generation Approach with Charging Stations β Year: 2024 π
π Dynamic Speed Optimization for Electric Vehicles βΒ Year: 2024 π
π Optimal Energy Management of Power Grid with EVs & Flexible Loads β Year: 2023 π