All modern Energy Management Systems (EMS) use some type of Automatic Contingency Selection (ACS) package to rank contingencies in the order of severity of their impact on the system security. We have developed a coherent theory for Automatic Contingency Selection (ACS), which puts the ACS problem in the decision framework which the system operator makes and allows him to assess the risk of making the wrong decision when using a specific performance index (PI) for ranking. Moreover, this work showed that a PI can be automatically tuned as the system status and load condition changes, so as to maximize the effectiveness of the decision performed by the ACS algorithm, a necessary feature when operating close to the security limits. This approach has been implemented in EPRI's RP2148 project on fast voltage estimation.
We have developed an ACS software package for finding the insecure contingencies and ranking them without solving a load flow for each contingency. Our program obtains the most effective performance index and threshold for selecting and ranking the contingencies without having to resort to masking. The contingencies are ranked in terms of their severity and those which give insecure operation are identified. The current program can handle up to 40 buses, but can be expanded.
1. The Application of Decision Theory to Contingency Selection," R. Fischl, T.F. Halpin, and A. Guvenis, IEEE Transactions on Circuits and Systems, vol. CAS-30, no. 11, pp. 712-23, November 1982.
2. "Analysis of Automatic Contingency Selection Algorithms," R. Fischl, T. F. Halpin and R. Fink, IEEE Trans. on Power Apparatus and Systems, vol. PAS-l03, no. 5, pp 938-945, May l984.
3. "An Algorithm for Automatically Tuning the Weights of Performance Indices for Monitoring Power System Loading or Security," R.Fischl, T.F. Halpin, J.J. Helferty, V. Gershman, F. Mercede, IEEE Trans. on Power Systems, vol. PRWS-1, no. 3, pp. 207-213, 1986.
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