Abstract:
This paper presents a neural system intended to aid the control center operator in the task of fault section estimation. Its analysis is based on information about the op...Show MoreMetadata
Abstract:
This paper presents a neural system intended to aid the control center operator in the task of fault section estimation. Its analysis is based on information about the operation of protection devices and circuit breakers. In order to allow the diagnosis task, the protection system philosophy of busbars, transmission lines, and transformers are modeled with the use of two types of neural networks: the general regression neural network and the multilayer perceptron neural network. The tool described in this paper can be applied to real bulk power systems and is able to deal with topological changes without having to retrain the neural networks.
Published in: IEEE Transactions on Power Delivery ( Volume: 19, Issue: 3, July 2004)
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- IEEE Keywords
- Index Terms
- Neural Network ,
- Power System ,
- Electric Power System ,
- Center For Control ,
- Multilayer Perceptron ,
- Transmission Line ,
- Protection System ,
- Topological Changes ,
- Type Of Neural Network ,
- Protection Devices ,
- Multilayer Perceptron Neural Network ,
- Generalized Regression Neural Network ,
- Hidden Layer ,
- Neural Model ,
- Missing Information ,
- Gas Pressure ,
- Network Output ,
- Protection Scheme ,
- Cluster Centers ,
- Fuzzy Logic ,
- Hyperbolic Tangent Activation Function ,
- Dc Source ,
- Supervisory Control And Data Acquisition ,
- Expert System ,
- Relay Protection ,
- Neural Modulation ,
- Petri Nets ,
- Large-scale Systems ,
- Network Efficiency ,
- Line L2
Contents Keywords assist with retrieval of results and provide a means to discovering other relevant content. Learn more.
- IEEE Keywords
- Index Terms
- Neural Network ,
- Power System ,
- Electric Power System ,
- Center For Control ,
- Multilayer Perceptron ,
- Transmission Line ,
- Protection System ,
- Topological Changes ,
- Type Of Neural Network ,
- Protection Devices ,
- Multilayer Perceptron Neural Network ,
- Generalized Regression Neural Network ,
- Hidden Layer ,
- Neural Model ,
- Missing Information ,
- Gas Pressure ,
- Network Output ,
- Protection Scheme ,
- Cluster Centers ,
- Fuzzy Logic ,
- Hyperbolic Tangent Activation Function ,
- Dc Source ,
- Supervisory Control And Data Acquisition ,
- Expert System ,
- Relay Protection ,
- Neural Modulation ,
- Petri Nets ,
- Large-scale Systems ,
- Network Efficiency ,
- Line L2
