collaborators

6 papers

eess.SY2026

Contingency Detection Integrated Model Predictive Control for Resilient Load Frequency Control

Erfan Mehdipour Abadi, Hamid Varmazyari, Sharaf K. Magableh +3

Contingencies can alter power-system dynamics and introduce prediction mismatch in model predictive control (MPC)-based load frequency control (LFC). Although such events may be de…

eess.SY2026

A Review of Community-Centric Power System Resilience: Strategies, Data-Driven Methods, and Techno-Legal Perspectives

Masoud H. Nazari, Hamid Varmazyari, Antar Kumar Biswas +3

This paper presents a comprehensive review of community-centric power system resilience, emphasizing the integration of community-level resilience considerations and techno-legal g…

eess.SY2025

A Learning-Driven Stochastic Hybrid System Framework for Detecting Unobservable Contingencies in Power Systems

Hamid Varmazyari, Masoud H. Nazari

This paper presents a new learning based Stochastic Hybrid System (LSHS) framework designed for the detection and classification of contingencies in modern power systems. Unlike co…

eess.SY2025

A Learning-based Hybrid System Approach for Detecting Contingencies in Distribution Grids with Inverter-Based Resources

Hamid Varmazyari, Masoud H. Nazari

This paper presents a machine-learning based Stochastic Hybrid System (SHS) modeling framework to detect contingencies in active distribution networks populated with inverter-based…

eess.SY2025

Detecting Unobservable Contingencies in Active Distribution Systems Using a Stochastic Hybrid Systems Approach

Erfan Mehdipour Abadi, Hamid Varmazyari, Masoud H. Nazari

This paper introduces a distributed contingency detection algorithm for detecting unobservable contingencies in power distribution systems using stochastic hybrid system (SHS) mode…

eess.SY2025

Early Detection and Classification of Hidden Contingencies in Modern Power Systems: A Learning-based Stochastic Hybrid System Approach

Erfan Mehdipour Abadi, Hamid Varmazyari, Masoud H. Nazari

This paper introduces a novel learning-based Stochastic Hybrid System (LSHS) approach for detecting and classifying various contingencies in modern power systems. Specifically, the…