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This paper presents an on-going research project to develop an intelligent system (IS) that can be used together with existing power system dynamic security assessment tools in order to enhance the capabilities of on-line secunty assessment for power system operations. The use of intelligent systems in this application is exEcted to improve the speed, accuracy, and robustness of security assessment. A prototype system named POSSIT, Power System Security using Intelligent Technologies, is resently being developed. An overview ofthe functional design of %s prototype is given here and shows how this approach is applied to the HydroQuCbec andBC Hydro power systems.

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This paper presents a method, using data mining techniques, to find dynamic power transfer limits and sensitivity of the limits due to element variations for the Hydro-Quebec power system based on topology information. The paper illustrates a systematic way to automatically generate a tremendous amount of cases to represent a wide range of parameter variations and compute their corresponding transfer limits based on time-domain dynamic simulations. These transfer limits are used to determine the transfer limit sensitivity for each parameter. Data mining techniques are used to build regression trees on this huge database, generated by the supercomputer at IREQ (the Hydro-Quebec Research institute), to find the relationship between either the transfer limits or the Δlimits and parameter variations. The benefit of this method is its ability to determine limits and/or Δlimits without requiring time-domain simulations in future studies. Rapid access to these limits and the sensitivities of the status of specific elements can potentially be foreseen to aid planning engineers in the planning and execution steps of limit calculations.

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