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Achieving High-Resolution Situational Awareness in Ultra-Wide-Area Cyber-Physical Systems

Achieving High-Resolution Situational Awareness in Ultra-Wide-Area Cyber-Physical Systems. PIs: Hairong Qi, Qing Cao, Yilu Liu, and Leon Tolbert Students: Brandon Johnson, Liu Liu, Wei Wang, Sisi Xiong, Yanjun Yao, and Lingwei Zhan Electrical Engineering and Computer Science

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Achieving High-Resolution Situational Awareness in Ultra-Wide-Area Cyber-Physical Systems

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  1. Achieving High-Resolution Situational Awareness in Ultra-Wide-Area Cyber-Physical Systems PIs: Hairong Qi, Qing Cao, Yilu Liu, and Leon Tolbert Students: Brandon Johnson, Liu Liu, Wei Wang, Sisi Xiong, Yanjun Yao, and Lingwei Zhan Electrical Engineering and Computer Science University of Tennessee, Knoxville NSF CPS PI Meeting, October 2013

  2. Rationale ONLINE IMPLEMENTATION To turn a large volume of real-time “mixture” data into actionable information and help prevent outages from happening • Develop a high-resolution, ultra-wide-area situational awareness system • Employ the power grid as a target application • Synergistically integrate • Sensing: High-resolution sensing with innovative design of frequency disturbance recorder at the distribution level • Processing: High-resolution online data analysis through event unmixing • Actuation: Coordinated local actuation with load as resource • Online implementation: Novel programming abstractions such as DataSQL DATA PROCESSING ACTUATION SENSING Physical World /System

  3. Sensing Towards the Edge • Innovation: • Accurate frequency measurement from low voltage distribution systems • Wide deployment of Frequency Disturbance Recorders (FDRs): measure essential transmission level information at the distribution level using low-cost sensors. • New wireless non-contact versions are being developed • Challenge: Noisy voltage signal at the distribution level • Comparison to state-of-the-art: PMU • Transmission level • Expensive

  4. Data Analysis through Event Unmixing Generator Trip Accuracy: 98%, FA: 0%; Line Trip Accuracy: 82%, FA: 0% • Innovation • A new conceptual framework, event unmixing: • Go beyond what are immediately detectable in a system, providing high-resolution data understanding at a finer scale. • Challenge • The universal existence of “mixture” or “mixed measurements” • How to construct a dictionary to reflect event dynamics • Comparison to state-of-the-art: single event detection • Nonnegative Sparse Event Unmixing (NSEU): Multiple event detection, recognition and temporal localization in ONE unmixing process at each FDR location

  5. Actuation with Load Participation Residential power demand decreased by 600 kW (~30 %) for 9.5 minutes. Residential power demand increased by 350 kW (~18 %) for 18 minutes. Simulation of 1000 homes on Sunday June 3rd, 2012 (At 4 pm, shed 50 % of HVACs). • Innovation • Load participation by residential or small commercial • Challenge • How much we know about loads? • How to participate? • A residential power demand simulation tool • Markov chain-based occupant behavior models • Dynamic models of all major residential loads • Models for residential demand response

  6. Online Programming by Approximation 6% 0.12% 4.5M p=0.1%, 0.01%, 0.001%, 0.0001% FP FN Memory • Innovation • Novel and compact data structures that are probabilistic by nature for data programming abstractions in DataSQL on resource constrained platforms • Challenge • Accurate data measurement and storage vs. approximate identification and measurement • Key-value bloom filter – supports the approximate key-value storage service

  7. Our Team Hairong Qi ONLINE IMPLEMENTATION Leon Tolbert Yilu Liu Charles Q. Cao DATA PROCESSING ACTUATION SENSING Physical World /System

  8. Target Market • Monitor devices and Load control devices with online processing algorithms • Huge economic impact • FNET/GridEye (joint effort by Univ. of Tennessee and Oak Ridge National Laboratory) • 150 FDRs installed in US and Canada • Another 40 installed worldwide

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