Conference proceeding
Hybrid expert system neural network hierarchical architecture for classifying power system contingencies
Proceedings of the First International Forum on Applications of Neural Networks to Power Systems
1991
Abstract
The authors present a hierarchical architecture which couples an expert system (ES) with multiple neural networks (NNs) for classifying power system contingencies. The ES performs the 'coarse' screening to decide if a contingency is potentially harmful and then determines its type of security limit violations. It uses a set of heuristic rules and a set of performance indicators to filter out the secure contingencies and direct the potentially harmful ones for further analysis in the appropriate NN. The NN's take the coarse classification outcome from the ES and perform a 'finer' screening by classifying the contingencies according to the severity of limit violations.< >
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Details
- Title
- Hybrid expert system neural network hierarchical architecture for classifying power system contingencies
- Creators
- H.H Yan - Drexel UniversityJ.-C Chow - Drexel UniversityM Kam - Drexel UniversityR Fischl - Drexel UniversityC.R Sepich - Drexel University
- Publication Details
- Proceedings of the First International Forum on Applications of Neural Networks to Power Systems
- Publisher
- IEEE
- Resource Type
- Conference proceeding
- Language
- English
- Other Identifier
- 991019346798104721