PECASE: Dynamic-Data-Driven Monitoring and Control in Real Time for Resilient Smart Grid Networks
Abstract
Real-time inferencing in a large-scale system under limited computational resources is very challengingdue to the excessive number of parameters and massive data loads involved. Computational intensitywould go even worse when evaluation of integrals for continuous variables is considered. New andeffective methodologies that are capable of dealing with massive, highly complex, and rapid moving dataare needed to make useful discoveries and achieve punctual control over these networks. This increasedneed of multi-scale simulations and autonomous systems are highlighted in the AF Technology Horizons,Energy Horizons and Global Horizons Reports alongside of the deployment of smart grid and energyefficient technologies as an essential focus area for science and technology investment. Addressing thisneed, the PI’s future research efforts will concentrate on data driven knowledge discovery by real-timeinferencing.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Apr 09, 2018
- Source ID
- FA95501810075
Entities
People
- Nurcin Celik
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of Miami