A Hybrid Expert System based on Neural Networks and Fuzzy Logic for Fault Identification in Electric Power Substations
This paper presents a novel approach for on-line fault identification in an Electric Power Substation (EPS). The proposed methodology is based on signal processing techniques allied with a Fuzzy Logic and Artificial Neural Network. The test electric system was rigorously built in an electromagnetic transient numerical simulator, named Alternative Transient Program (ATP), conformably to the needs presented by a Thermoelectric Generation Plant of 711 MW 230 kV, located in southern Brazil. Simulated test cases demonstrate the generalization capability of the developed hybrid Expert System based on Neural Networks and Fuzzy Logic, now utilized in a Southern Brazilian Utility.
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A Hybrid Expert System based on Neural Networks and Fuzzy Logic for Fault Identification in Electric Power Substations
Semantic Scholar · Computer Science · 2010
Abstract
This paper presents a novel approach for on-line fault identification in an Electric Power Substation (EPS). The proposed methodology is based on signal processing techniques allied with a Fuzzy Logic and Artificial Neural Network. The test electric system was rigorously built in an electromagnetic transient numerical simulator, named Alternative Transient Program (ATP), conformably to the needs presented by a Thermoelectric Generation Plant of 711 MW 230 kV, located in southern Brazil. Simulated test cases demonstrate the generalization capability of the developed hybrid Expert System based on Neural Networks and Fuzzy Logic, now utilized in a Southern Brazilian Utility.