Visible to the public CPS: Synergy: Collaborative Research: Real-time Data Analytics for Energy Cyber-Physical SystemsConflict Detection Enabled

Project Details
Lead PI:Maggie Cheng
Performance Period:08/24/16 - 08/31/18
Institution(s):New Jersey Institute of Technology
Sponsor(s):National Science Foundation
Award Number:1660025
265 Reads. Placed 450 out of 803 NSF CPS Projects based on total reads on all related artifacts.
Abstract: Inadequate system understanding and inadequate situational awareness have caused large-scale power outages in the past. With the increased reliance on variable energy supply sources, system understanding and situational awareness of a complex energy system become more challenging. This project leverages the power of big data analytics to directly improve system understanding and situational awareness. The research provides the methodology for detecting anomalous events in real-time, and therefore allow control centers to take appropriate control actions before minor events develop into major blackouts. The significance for the society and for the power industry is profound. Energy providers will be able to prevent large-scale power outages and reduce revenue losses, and customers will benefit from reliable energy delivery with service guarantees. Students, including women and underrepresented groups, will be trained for the future workforce in this area. The project includes four major thrusts: 1) real-time anomaly detection from measurement data; 2) real-time event diagnosis and interpretation of changes in the state of the network; 3) real-time optimal control of the power grid; 4) scientific foundations underpinning cyber-physical systems. The major outcome of this project is practical solutions to event or fault detection and diagnosis in the power grid, as well as prediction and prevention of large-scale power outages.