ENERGY MANAGEMENT SYSTEM WITH INTELLIGENT ANOMALY DETECTION AND PREDICTION

摘要

A computer-implemented method for detecting and predicting anomalies in an energy management system is presented. The method includes detecting, in real-time, a first set of outliers for a plurality of energy devices under operation, predicting a second set of outliers for running the plurality of energy devices, analyzing historical energy data of the plurality of energy devices to extract a third set of outliers, receiving feedback, in real-time, from a user regarding each of the first, second, and third sets of outliers, and training the energy management system with the real-time feedback received from the user to automatically optimize a threshold of error detection.