ART artificial neural networks based adaptive phase selector

This paper introduces a new phase selector based on adaptive resonance theory (ART). Because conventional phase selector cannot adapt dynamically to the power system operating conditions, it will present different characters under different power system conditions. To overcome the disadvantage, an adaptive phase selector, which utilizes artificial neural network based on ART, is designed. The phase selector may adapt dynamically to the varying power system operation conditions and needs fewer training patterns to train neural networks. Furthermore, the phase selector could be trained and learned online so that it could best adapts itself to the varying power system conditions. A lot of EMTP simulations and experimental field data tests have illustrated the phase selector´s correctness and effectiveness.