In large-scale power transmission systems, predicting faults and preemptively taking corrective action to avoid them is essential to preventing rolling blackouts. The computational study of the constantly-shifting state of the power grid and its weaknesses is called contingency analysis. Multiple-contingency planning in the electrical grid is one example of a complex monitoring system where a full computational solution is operationally infeasible. We present a general framework for building and evaluating resource-aware models of filtering techniques for this type of monitoring.
Revised: April 19, 2013 |
Published: December 31, 2011
Citation
Adolf R.D., D.J. Haglin, M. Halappanavar, Y. Chen, and Z. Huang. 2011.Techniques for Improving Filters in Power Grid Contingency Analysis. In Proceedings of the 7th International Conference on Machine Learning and Data Mining in Pattern Recognition (MLDM), August 30-September 3, 2011, New York. Lecture Notes in Computer Science, edited by P Perner, 6871, 599-611. Berlin:Springer-Verlag.PNNL-SA-77563.doi:10.1007/978-3-642-23199-5_44