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

Rationale 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 ONLINE IMPLEMENTATION To turn a large volume of real-time “mixture” data into actionable information and help prevent outages from happening

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 Thus far there are about 150 FDRs installed and another 40 installed worldwide. Currently, the system is operated by the University of Tennessee and Oak Ridge National Laboratory as a joint effort. The price difference between PMU and FDR plus installation is $80,000 vs. $1,000

Data Analysis through Event Unmixing 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 Generator Trip Accuracy: 98%, FA: 0%; Line Trip Accuracy: 82%, FA: 0%

Actuation with Load Participation 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 Residential power demand decreased by 600 kW (~30 %) for 9.5 minutes. Residential power demand increased by 350 kW (~18 %) for 18 minutes. Most load shedding is for large industrial plants.  Load participation by residential or small commercial is relatively new.   To understand the impact residential loads have on the power system, we developed the Residential Power Demand Simulation Tool (the tool’s GUI is shown on the right). This tool was developed in MATLAB and combines Markov chain-based occupant behavior models, dynamic models of all of the major residential loads, and models for residential demand response. It can be used to understand the potential resources that can be provided by residential loads. This tool simulates real and reactive power demand on a 1-second time scale. Simulation of 1000 homes on Sunday June 3rd, 2012 (At 4 pm, shed 50 % of HVACs).

Online Programming by Approximation 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 6% 0.12% 4.5M p=0.1%, 0.01%, 0.001%, 0.0001% FP FN Memory

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

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 From the utility perspective: 1. If the utility can get enough load participation so that peak demand can be considerably reduced, then a. The utility can avoid having to purchase power from a neighboring utility which is usually at very high prices. b. The utility may avoid having to build as many "peaking units" generally natural gas turbines.  Again, cost savings in terms of deferred construction, maintenance, and operation costs. From the customer perspective: 1. If they agree to have interruptible load, generally can purchase power at cheaper prices. 2. If utilities start using real-time pricing, customers can avoid using large amounts of power during high price times and save money. So methods and devices that allow greater load participation has both customers and utilities as markets.