Hello, I am Jiahui (Clay) Yang, a PhD researcher in Electrical Engineering at the University of Tennessee, Knoxville. My research focuses on wide-area power system monitoring, with an emphasis on PMU/FDR system design, precision timing and synchronization, and edge computing. I work on PMU hardware and embedded systems, GPS- and FPGA-based timing sources, real-time frequency and phasor estimation, and data compression for large-scale distribution networks. I am actively involved in the FNET/GridEye project and collaborative research with utility partners.

News

2025 🐍

• The Universal GridEdge Analyzer (UGA), a project I contributed to at the University of Tennessee, Knoxville in collaboration with Oak Ridge National Laboratory, received an R&D 100 Award. 🎉

• Published “Enhancing Time Synchronization in Smart Grid with White Rabbit: Theory, Architecture and Challenges”, presenting a systematic analysis of White Rabbit–based sub-nanosecond time synchronization for smart grid applications. 🎉

• Presented “A Hybrid System for High-Accuracy Timekeeping Using Millisecond Pulsars” at the 2025 Joint Conference of the European Frequency and Time Forum and IEEE IFCS, demonstrating a hybrid pulsar- and GPS-based PPS timing system with nanosecond-level accuracy. 🎉

• Published “Time Synchronization Techniques in the Modern Smart Grid: A Comprehensive Survey” in Energies, providing an extensive review of synchronization methods, standards, and challenges in modern power systems. 🎉

• Published “Lightweight Data-Driven Planning Method of Hybrid Energy Storage Systems in the New Power System” in IEEE Transactions on Industry Applications. 🎉

• Published “Pulsar’s Application in Energy Systems: Review of Current Status, Challenges, and Opportunities” in Energies. 🎉

2024 🐉

• Published “Research Progress and Prospects on Compression Methods of Smart Power Distribution and Consumption Data” in Distribution & Utilization, reviewing recent advances and future directions in data compression techniques for smart distribution and consumption systems. 🎉

2023 🐇

• Published “Real-Time D-PMU Data Compression for Edge Computing Devices in Digital Distribution Networks” in IEEE Transactions on Power Systems, proposing a real-time PMU data compression framework validated using both field and simulated data under normal and fault conditions. 🎉

2022 🐅

• Published “Two-Stage Data Compression Method for Edge Computing Devices in Distribution Networks” in Power System Technology, introducing an efficient two-stage compression approach for distribution-level measurement data. 🎉