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A practical application and implementation of adaptive techniques using neural networks into autoreclose protection and system control

A practical application and implementation of adaptive techniques using neural networks into autoreclose protection and system control

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Reyrolle Protection have carried out research in conjunction with Bath University into applying adaptive techniques to autoreclose schemes and have produced an algorithm based on an artificial neural network which can recognise when it is 'safe to reclose' and when it is 'unsafe to reclose'. This algorithm is based on examination of the induced voltage on the faulted phase and by applying pattern recognition techniques determines when the secondary arc extinguishes. Significant operational advantages can now be realised using this technology resulting in changes to existing operational philosophy. Conventional autoreclose relays applied to the system have followed the philosophy of 'reclose to restore the system', but a progression from this philosophy to 'reclose only if safe to do so' can now be made using this adaptive approach. With this adaptive technique the main requirement remains to protect the investment i.e. the system, by reducing damaging shocks and voltage dips and maintaining continuity of supply.

Inspec keywords: neural nets; pattern recognition; artificial intelligence; relay protection; power distribution protection; circuit-breaking arcs

Other keywords: adaptive techniques; autoreclose schemes; secondary arc; Reyrolle protection; relays; pattern recognition; artificial neural network

Subjects: Power system protection

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