KETEP 세계에너지시장정보

1. A method for using forecasting power transformer faults, the method comprising:
receiving, by at least one processor of a device, dissolved gas data of power transformers;
receiving, by the at least one processor, features of the power transformers;
generating, by the at least one processor, based on the features and the dissolved gas data, clusters of transformers, wherein each respective cluster of the clusters comprises transformers exhibiting similarities to each other;
selecting, by the at least one processor, for each respective cluster and for each respective gas of the dissolved gas data, from among multiple machine learning models trained to minimize a difference between a forecast gas concentration and an actual gas concentration, a machine learning model associated with forecasting concentration of the respective gas of the respective cluster;
generating, by the at least one processor, using a selected machine learning model, a forecasted gas concentration of the respective gas of the respective cluster;
estimating, by the at least one processor, using the forecasted gas concentration, a rate of change (ROC) of the respective gas of the respective cluster;
predicting, by the at least one processor, based on comparisons of the forecasted gas concentration and the ROC to respective alarm thresholds, a future fault of a transformer; and
generating, by the at least one processor, an alert indicating that transformer maintenance is required prior to the predicted future fault.