Hamed Mohsenian-Rad, Ph.D., IEEE Fellow Professor and Bourns Family Faculty Fellow Department of Electrical and Computer Engineering University of California, Riverside Email: hamed (at) ee DOT ucr DOT edu Office: Room 436—Winston Chung Hall Research Lab: Room 225—Winston Chung Hall Phone: 951-827-2387    Fax: 951-827-2425

New Book on Smart Grid Sensors and Data-Driven Applications

Short Bio

I am a Professor of Electrical and Computer Engineering. My research is on developing optimization-based and data-driven techniques for power systems and smart grid applications with focus on sensing, controls, and operations. I received the NSF CAREER Award from the National Science Foundation for my research on smart grid; the Best Paper Award from the IEEE Power and Energy Society General Meeting; the Best Paper Award from the IEEE International Conference on Smart Grid Communication; and the Technical Achievement Award from the IEEE Communications Socity. I have been the Lead PI for over $10 million research projects. Before becoming a faculty member I was a post-doctoral fellow at the University of Toronto. I received my Ph.D. in Electrical and Computer Engineering from the University of British Columbia in 2008, M.Sc. in Electrical Engineering from Sharif University of Technology in 2004, and B.Sc. in Electrical Engineering from Amir-Kabir University of Technology in 2002. In 2007, I was a visiting student at Princeton University. I serve as Editor for the IEEE Transactions on Power Systems, the IEEE Power Engineering Letters, and the IEEE Transactions on Network Science and Engineering. Previously, I served as Editor for the IEEE Transactions on Smart Grids for six years. I am the Associate Director of the Winston Chung Global Energy Center. Previously, I served as the Director of the UC-National Lab Center on Power System Cyber Security. I received the Distinguished Teaching Award from the Bourns College of Engineering in 2017. I am an IEEE Fellow, Class of 2020.

News

• 09/2022: I will be a Keynote Speaker at the IEEE Smart Grid Comm 2022 I will talk about the Frontiers in Smart Grid Data Availability.

• 07/2022: I am a co-PI on a new $3,000,000 NSF grant entitled NRT: Science to Policy Education: Activating Knowledge for Sustainable Transportation to enhance multi-disciplinary graduate student training on power grid infrastruture for sustainable transportation.

• 06/2022: I received the Technical Achievement Award from the IEEE Communications Society for "Pioneering Contributions to Optimization and Data Analytics in Smart Grids".

Research on Distribution Synchro-phasors

• Our publications on distribution-level phasor measurement units (D-PMUs):

  • Distribution Synchrophasors: Pairing Big Data with Analytics to Create Actionable Information
  • GraphPMU: Event Clustering via Graph Representation Learning
  • Automated Event Region Identification and its Data-Driven Applications in Behind-the-Meter Solar Farms Based on Micro-PMU Measurements
  • Impact Analysis and Mitigation of Losing Time Synchronization at Micro-PMUs in Event Location Identification
  • Unsupervised Event Detection, Clustering, and Use Case Exposition in Micro-PMU Measurements
  • Individual Load Model Parameter Estimation in Distribution Systems using Load Switching Events
  • Locating the Source of Events in Power Distribution Systems Using Micro-PMU Data
  • Situational Awareness in Distribution Grid Using Micro-PMU Data: A Machine Learning Approach
  • Event-Based Analysis of Solar Power Distribution Feeder Using Micro-PMU Measurements
  • Poisoning Attack against Event Classification in Distribution Synchrophasor Measurements
  • Cyberattacks Against Event-Based Analysis in Micro-PMUs: Attack Models and Counter Measures
  • Analysis of Cyber Attacks Against Micro-PMUs: The Case of Event Source Location Identification
  • Sparse Tracking State Estimation for Low-Observable Power Distribution Systems Using D-PMUs
  • Sparse Distribution System State Estimation: An Approximate Solution Against Low Observability
  • A Machine Learning Approach to Event Analysis in Distribution Feeders Using Distribution Synchrophasors
  • Linear Distribution System State Estimation Using Synchrophasor Data and Pseudo-Measurement
  • Tracking State Estimation in Distribution Networks Using Distribution-level Synchrophasor Data
  • Distribution Grid Reliability vs Regulation Market Efficiency: Analysis based on Micro-PMU Data
  • Autopsy on Active Distribution Networks: A Data-Driven Fault Analysis Using Micro-PMU Data.
  • Location Identification of Distribution Network Events Using Synchrophasor Data.
  • A Data-Driven Analysis of Lightning-Initiated Contingencies at a Distribution Grid with a PV Farm.
  • Data-Driven Analysis of Capacitor Bank Operation at a Distribution Feeder Using Micro-PMU Data.
  • Distribution Grid Reliability Analysis with Regulation Down Load Resources by Micro-PMU Data.

• I served as the Guest Editor-in-Chief for the IEEE Transactions on Smart Grid a Special Issue on Theory and Application of PMUs in Power Distribution Systems.

Research on Synchro-waveforms and Harmonic Synchro-phasors

• Our publications on waveform measurement units (WMUs) and harmonic phasor measurement units (H-PMUs):

  • Tutorial: Synchro-Waveforms: A New Frontier in Advanced Smart Grid Sensing and Data Analytics
  • A Synchronized Lissajous-based Method to Detect and Classify Events in Synchro-waveform Measurements in Power Distribution Networks
  • Synchronous Waveform Measurements to Locate Transient Events and Incipient Faults in Power Distribution Networks
  • Characterizing Synchronized Lissajous Curves to Scrutinize Power Distribution Synchro-waveform Measurements
  • A Physics-Aware MIQP Approach to Harmonic State Estimation in Low-Observable Power Distribution Systems Using Harmonic Phasor Measurement Units
  • Switch Status Identification in Distribution Networks using Harmonic Synchrophasor Measurements
  • Event Location Identification in Distribution Networks Using Waveform Measurement Units
  • Physics-Aware Sparse Harmonic State Estimation in Power Distribution Systems
  • Data-Driven Event Location Identification Without Knowing Network Parameters Using Synchronized Electric-Field and Current Waveform Data
  • Location Identification of High Impedance Faults Using Synchronized Harmonic Phasors
  • GraphPMU: Event Clustering via Graph Representation Learning Using Fundamental and Harmonic PMU Measurements
  • Synchro-Waveforms for Situational Awareness with Application to Wildfire Monitoring
  • Presentations at SGSMA 2022 Panel on Synchronized Waveform Measurements: Hamed Mohsenian-Rad, Wilsun Xu, Steven Blair, Alvaro Furlani Bastos