data-driven planning and operation

Imran Pervez

Ph.D. Student, Electrical and Computer Engineering

power systems optimization Advanced control systems engineering renewable energy integration data-driven planning and operation

Imran Pervez's research focuses on integrating machine learning, optimization, and advanced control methodologies for power systems, with applications in renewable energy integration, stochastic and robust model predictive control, and data-driven decision-making to improve the efficiency, reliability, and economic performance of modern energy systems.

KAUST-CEMSE-ECE-PhD-Dissertation-Defense-Otavio-Jose-Dezem-Bertozzi-Junior

Modeling, Analysis, and Control for Planning and Operation of Modern Mixed-Generation Power Systems

Otavio Bertozzi, Ph.D. Student, Electrical and Computer Engineering

Nov 19, 09:30 - 10:30

B5, L5, R5209

mixed-generation power systems stability-aware modeling data-driven planning and operation renewable energy integration

This dissertation presents an interpretable framework for modeling, planning, and control of mixed-generation power systems, integrating ternary stability-aware planning, reinforcement learning-based control tuning, and data-driven stability forecasting to bridge analytical models with real-time operation in converter-dominated grids.