1
Tutorial
Time-Synchronized Estimation Problems in Modern Power Systems
Session format with hands-on emphasis and step-by-step examples for synchronized measurement applications.
Program
Tutorials
Technical tutorials for the 5th International Conference on Smart Grid Synchronized Measurements and Analytics (SGSMA 2026).
Abstract
In the last decade, the number and types of sensors capable of producing time-synchronized measurements has grown significantly. Consequently, a variety of power system problems can now be addressed using measurements coming from these types of devices. This tutorial focuses on recent algorithms that have been developed to solve practical problems related to state estimation, oscillations, modal estimation, and inertia calculations using time-synchronized measurements alone as well as in combination with supervisory control and data acquisition (SCADA) measurements.
The tutorial will present hands-on exercises with step-by-step examples for each type of estimation problem. Simulated data along with real measurements will be used as input data to the algorithms used for estimation and the applications will span IEEE benchmark models as well as actual systems. Example programming codes, wherever possible, will be provided to facilitate reproducibility of the results. Moreover, additional references to support the material covered by each of the speakers will be provided.
Outline
5 min
Introduction
50 min
Mani V. Venkatasubramanian: Offline analysis of oscillations using synchrophasors and SCADA
The talk introduces ringdown and ambient algorithms for analyzing oscillatory modes and oscillations with synchrophasors, plus a methodology for locating oscillation sources using SCADA measurements.
10 min
Break
50 min
Yilu Liu: Oscillations and inertia measurements
The talk focuses on captured oscillations, damping approaches, and field-probing-based inertia measurements with examples.
10 min
Break
50 min
Saikat Chakrabarti: Use of synchrophasor measurements in static state estimation
Topics include PMU-only SSE, hybrid PMU+SCADA SSE, observability with PMUs, bad data detection, and real-world usage examples. Links to MATLAB code for basic algorithms are provided.
10 min
Break
50 min
Backer Abu-Jaradeh: Need for Linear State Estimation (LSE) for real-time control room assessment
Topics include PMU deployment and observability, bad data handling, virtual PMUs with LSE, real-time assessments, and industry deployment considerations.
5 min
Closure
Instructors
Mani V. Venkatasubramanian
Boeing Distinguished Professor in Electrical Engineering at Washington State University (WSU), and Director of the Energy Systems Innovation Center (ESIC). He received M.S. and D.Sc. degrees in Systems Science and Mathematics from Washington University, St. Louis, and a B.E. (Hons.) in Electrical and Electronics Engineering from BITS Pilani, India. He served in working groups studying the 1996 Western Interconnection and 2003 Northeastern blackouts. He is Chair of the IEEE PES Working Group on Power System Dynamic Measurements, an IEEE Fellow, recipient of the IEEE PES Prabha S. Kundur Power System Dynamics and Control Award, and elected member of the Washington State Academy of Sciences.
Yilu Liu
Received M.S. and Ph.D. degrees from The Ohio State University (1986, 1989), and B.S. degrees from Xi'an Jiaotong University, China. She is currently the UT-ORNL Governor's Chair at the University of Tennessee and Oak Ridge National Laboratory, and deputy director of the DOE/NSF ERC CURENT (curent.utk.edu). She led the North American grid Frequency Monitoring Network FNET/GridEye. Her research focuses on large-grid dynamic modeling, simulation, and monitoring. She is a member of the National Academy of Engineering, a member of the National Academy of Inventors, and an IEEE Fellow.
Saikat Chakrabarti
Completed his Ph.D. in Electrical Engineering at Memorial University of Newfoundland, Canada (2006). Since 2009 he has been with the Department of Electrical Engineering, IIT Kanpur, where he has served as professor since 2018. He also worked as Chair Professor and Director of the Emera and NB Power Research Centre for Smart Grid Technologies, University of New Brunswick, Fredericton, Canada. His research interests include monitoring, control, and protection of smart transmission/distribution systems and microgrids. He is an IEEE Fellow and Fellow of the Indian National Academy of Engineering (INAE).
Backer Abu-Jaradeh
Received his M.S. in Power Systems Electrical Engineering from California State University, Los Angeles (2012), and his Ph.D. from the University of Southern California (2022), focused on power system real-time applications. He is an IEEE Senior Member, NERC-certified Reliability Coordinator, and Professional Engineer with extensive operations experience. He has supported control room operations directly with grid operators and currently serves as Vice President of Customer Engineering Services at EPG, supporting synchrophasor technology applications for utilities and ISOs.
2
Tutorial
Synthetic PMU Datasets — Uncertainty, Interoperability, and Trustworthy AI
Session Length: 240 minutes | Expected Attendees: 10–15
Abstract
As smart grids transition into cyber-physical systems of unprecedented complexity, the demand for trustworthy, replicable, and explainable data-driven methodologies has become paramount. This tutorial addresses the scarcity of open, high-fidelity PMU datasets by proposing a framework for their generation, evaluation, and integration.
The session combines theoretical foundations and practical demonstrations to support resilient and human-oriented smart-grid analytics. Main topics include:
1. Digital representations: digital models, shadows, and digital twins.
2. Uncertainty quantification: statistical characterization and propagation impacts (including UFLS).
3. Data fusion and AI: combining real and synthetic data for learning tasks such as state estimation.
4. Human-oriented design: human-in-the-loop and human-on-the-loop perspectives.
Outline
5 min
Introduction to Synthetic PMU Data Generation
Motivations, data scarcity context, and overview of generation methods with operational constraints.
25 min
Digital Representations: From Model to Digital Twin
Definitions, simulation role, and hybrid synchronized systems / hardware-in-the-loop integration.
30 min
Quantifying and Propagating Uncertainty
Statistical characterization of synthetic data and downstream impacts on UFLS and state estimation.
30 min
Demo 1: Data Generation and Validation
UFLS-focused use case, robustness and adaptability, reproducible workflows, and traceability.
30 min
Break / Q&A
30 min
Merging Real and Synthetic Data for ML Tasks
Fusion strategies, trust levels, validation approach, and performance implications.
30 min
Demo 2: Simple Anomaly Detection and Data Fusion
General-purpose event detection and gossiping approach using PMU signals.
30 min
Trustworthy AI Benchmarks for the Smart Grid
Benchmark design for robustness, explainability, generalizability, and human-in-the-loop operation.
Instructors
Federico Grasso Toro
University of Bern, Switzerland. Electronic Engineering degree (automation and robotics) from the National University of San Juan, Argentina, and Ph.D. in Mechanical Engineering from Technische Universitat Braunschweig, Germany. His work focuses on digitalization of metrology, human+machine systems, and transdisciplinary digital infrastructures. Contact: federico.grasso@unibe.ch.
Guglielmo Frigo
Federal Institute of Metrology METAS, Switzerland. Senior Member IEEE, with a Ph.D. from the University of Padova and research experience at EPFL and NIST. His current research includes enhanced measurement infrastructures for electrical systems and strategy for energy and mobility. Contact: guglielmo.frigo@metas.ch.