Abstract
A thermal monitoring and reliability analysis system for underground substation is introduced in this paper. Back propagation (BP) neural network is applied in the proposed system for temperature prediction; life estimation model is utilized for estimating residual life span of transformer. This system is capable of real time on-line monitoring, early warning, control and alarm for substation operation. In addition, with novel algorithms the proposed system is also capable of forecasting failure of power facilities as well as ambient environment of transformer room. It could be employed in substation with various hazardous conditions for intelligent and safe operation of power equipment.
Published Version
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