Design and implementation of an adapative single pole autoreclosure technique for transmission lines using artificial neural networks

Adaptive single pole autoreclosure (SPAR) offers many advantages over conventional techniques. In the case of transient faults, the secondary arc extinction time can be accurately determined and in the case of a permanent fault, breaker reclosure can be avoided. This paper describes, in some detail, the design and implementation of a SPAR technique using artificial neural networks (ANNs). The design described includes special methods for extracting features from post-circuit breaker opening fault data, which is a prerequisite for setting up training data sets. The technique is then implemented in hardware based on a high performance T800 transputer system and some results obtained from laboratory tests of this equipment are presented.