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Synchro-Waveforms Data Analytics and Data-Driven Applications

Mladen Kezunovic, Yilu Liu, Jhi-Young Joo, Mario Paolone, Hamed Mohsenian-Rad, Abder Elandaloussi, Lakshan Piyasinghe

  • PES
    Members: Free
    IEEE Members: $25.00
    Non-members: $40.00
    Pages/Slides: 30
Panel 12 Sep 2024

Waveforms are the most granular and authentic representation of voltage and current in power systems. With the latest advancements in power system sensor technologies, it is now possible to obtain time-synchronized waveform measurements, i.e., synchro-waveforms, from different locations of a power system. At a much higher reporting rate than synchro-phasors, synchro-waveforms create a new frontier in Big Data Analytics in power systems, moving beyond the conventional synchro-phasors. However, data availability is not sufficient to build a new level of operational intelligence in power systems. Data must be furnished with helpful analytics to translate said data into actionable information and practical use cases. This calls for developing new methodologies, tools, and techniques to analyze waveform and synchro-waveform data in power systems. In this panel, which is led by the new IEEE Task Force on Big Data Analytics for Waveform Measurements will cover the advancements in this new field, including new data-driven and machine learning methods and innovative data-driven applications. The panelists have diverse expertise; coming from academia, national laboratories, and industry. In addition to discussing methodologies and applications, the panelists will also present insightful examples of real-world synchro-waveform measurements and data-driven applications Adopting the synchro-waveform data analytics technologies in the industry will also be discussed. The list below shows the potential panelists, which will be confirmed once the panel is approved. The titles of the talks are tentative as they are selected based on the general expertise of each potential panelist.

Chairs:
Hamed Mohsenian-Rad, Jhi-Young Joo
Primary Committee:
(AMPS) Big Data Analytics