Data-Driven power system operations

Authors:
E. H. Abed;N. S. Namachchivaya;T. J. Overbye;M. A. Pai;P. W. Sauer;A. Sussman
Affiliations:
University of Maryland, College Park, MD;University of Illinois, Urbana, IL;University of Illinois, Urbana, IL;University of Illinois, Urbana, IL;University of Illinois, Urbana, IL;University of Maryland, College Park, MD
Venue:
ICCS'06 Proceedings of the 6th international conference on Computational Science - Volume Part III
Year:
2006

Citing 5
Cited 0

Processing large-scale multi-dimensional data in parallel and distributed environments

Parallel Computing - Parallel data-intensive algorithms and applications
The SDSC storage resource broker

CASCON '98 Proceedings of the 1998 conference of the Centre for Advanced Studies on Collaborative research
Flexible Control of Data Transfers between Parallel Programs

GRID '04 Proceedings of the 5th IEEE/ACM International Workshop on Grid Computing
Spatial indexing of distributed multidimensional datasets

CCGRID '05 Proceedings of the Fifth IEEE International Symposium on Cluster Computing and the Grid (CCGrid'05) - Volume 2 - Volume 02
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking

IEEE Transactions on Signal Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In operations, simulation and control of power systems, the presence of real-time data relating to system states can yield precise forecasts and can enable robust active control. In this research we are developing efficient and robust methods to produce “data enhanced” reduced order models and filters for large-scale power systems. The application that this paper focuses on is the creation of new data-driven tools for electric power system operation and control. The applications systems include traditional SCADA systems as well as emerging PMU data concentrators. A central challenge is to provide near real-time condition assessment for ”extreme events,” as well as long-term assessment of the deterioration of the electrical power grid. In order to provide effective guidance for power system control, we are also developing visualization methods for integrating multiple data sets. These visualization methods provide an up-to-date view of the system state, and guide operator-initiated power system control.