PhD Candidate | Power System Engineer | AI in Power Systems
Rouzbeh Haghighi
Short Bio
Rouzbeh Haghighi is a Ph.D. candidate in Electrical Engineering at the University of Michigan–Dearborn, where his research focuses on power systems, renewable energy integration, smart grid technologies, and the application of machine learning in power system analysis and optimization. He holds an M.Sc. in Electrical Engineering–Power Systems from Amirkabir University of Technology (Tehran Polytechnic), where he specialized in energy planning, hybrid renewable systems, and power system reliability. He also completed his B.Sc. in Electrical Engineering (Power Systems) at K. N. Toosi University of Technology, conducting research on distribution network reconfiguration and smart grids. Across his academic journey, Rouzbeh has developed strong expertise in advanced power system modeling, intelligent control, renewable energy resources, and data-driven engineering solutions.
Research Interests
Power System Modeling and Optimization
Smart Grid Technologies and Applications
Energy Management and Demand Response
Integration of Renewable Energy Technologies
Reliability and Resilience in Power Systems
AI and Large Language Models (LLMs) in Power Systems
Advanced Machine Learning and Deep Learning Techniques
Publications
Selected Journals
- “Survey of Reliability Challenges and Assessment in Power Grids with High Penetration of Inverter-Based Resources” Journal of Energies – MDPI – 2024
- “A Systemic Stochastic Infrastructure Damage Evaluation Framework, Incorporating Fragility Curves, Reinforced by Network Reduction in Distribution Systems” IEEE Transactions on Power Delivery – 2024
- “Cloud Energy Storage Investment by Collaboration of Microgrids for Profit and Reliability Enhancement Considering a TSO-DSO Yearly Reward” IEEE Access – 2023
- “A Game Theory Approach using TLBO algorithm for Generation Expansion Planning by applying carbon curtailment policy” Journal of Energies – MDPI – 2022
- “Generation Expansion Planning Using Game Theory Approach to Reduce Carbon Emission” Journal of Computers & Industrial Engineering – 2021
Conferences
- “Large Language Models for Solving Economic Dispatch Problem” – 2025 IEEE Energy Conversion Conference and Expo (ECCE) – 2025
- “Reinforcement Learning-Based Optimization of Second-Life Battery Utilization in Electric Vehicles Charging Stations” – 2025 IEEE Power & Energy Society General Meeting (PESGM) – 2025
- “Fast Accurate Phasor Estimation in Less than One Cycle using Neural Networks” – 2024 IEEE 18th International Conference on Control & Automation (ICCA), 359-363 – 2024
- “Impact of Congestion on Optimal Sizing of DG Resources in an Active Distribution Network Optimized by TLBO Algorithm” – The 26th Electrical Power Distribution Conference, May 11-12, Tehran, Iran. – 2022
Book Chapters
- “Genetic Algorithm and Its Applications in Power Systems” -Frontiers in Genetics Algorithm Theory and Applications – Springer – 2024
- “Optimal Power Flow by Genetic Algorithm” – Frontiers in Genetics Algorithm Theory and Applications – Springer – 2024