Compel (Vol. 23, 2004): Special Issue by Carpinelli G., Testa A.

By Carpinelli G., Testa A.

Certain factor: chosen papers from PMAPS 2002 -Conference on Probabilistic tools utilized to strength platforms, Naples 2002

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The data cases represent actual operating states collected over a 5 year period. By using the data mining technique, the most relevant parameters for this automat were identified and effective settings were determined. A correlation analysis and the construction of RTs were carried out on the results of these simulations using data mining software developed at the University of Liege. This analysis made it possible to minimize, in particular, the number of generators tripped by the RPTC system for a large number of network conditions, while maintaining the same performance in terms of security coverage.

COMPEL 23,1 46 Figure 10. Probability of stability result Different power systems may have different stability performance due to their different network topologies, installation capacities, and protection character/scenarios. Protection failures are rare events in power system. This can be noticed by the long time taken by simulation to converge. Some variance reduction techniques could be applied to reduce simulation time. The methodology presented in this paper will be validated in the future on a larger test system that closely represents real power system.

Event 6, as the result of event-3, simply shows the certainty of backup protection scheme for “failure to operate”. However, the origin of “failure to operate” (event 3) already embodies the probabilistic feature. Therefore, entire cascading procedure is incorporated with a series of stochastic processes, reflecting the true picture of events in the power system. Monte Carlo simulation method is utilized in this paper because it can handle complicated stochastic problems in a more realistic manner.

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