Graphical Contingency Analysis for the Nation's Electric Grid
Principal Investigator: Z Huang
Co-Principal Investigators: P Wong, Y Chen
Technical Advisors: FL Greitzer, JE Dagle, MD Hadley, JJ Thomas
Purpose of research
- Handle a large volume of predictions using analytical methods to accomplish a three-step prediction process: prediction of deteriorating conditions, prediction of the impact of the problems, and prediction of the effect of remedial actions.
Innovative methods to predict possible future impacts of alternative courses of action (candidate corrective measures) by visualization and modeling of system/infrastructure data.
More sophisticated models/methods and visualizations to enable more effective, real-time forecasting and decision making.
Managing complexity of high-volume predictive and adaptive network operations is a four-step process that consists of 1) ensuring data integrity with detection of compromised data points, 2) improving situational awareness by visualizing and analyzing the change in the risk level, 3) predicting consequences of problems by analyzing the pattern of the impact, and 4) assessing the effect of alternative remedial actions via interactive risk analysis. This predictive situational awareness and decision making support is designed to significantly improve electric power grid operations.