1. A method for predicting anomaly associated with at least one energy asset, the method comprising: receiving, by a processor, time stamped historical energy data associated with the at least one energy asset; creating, by the processor, one or more frequency components by performing frequency domain analysis on the time stamped historical energy data, each of the one or more frequency components indicative of time stamped energy values associated with the at least one energy asset; clustering, by the processor, the one or more frequency components to generate one or more clusters based on similarity of time stamped energy values, each of the one or more clusters associated with at least one energy signature, the at least one energy signature being average of time stamped energy values for a cluster; receiving time stamped energy data in real time from the at least one energy asset; comparing, by the processor, between the time stamped energy data and the at least one energy signature associated with a cluster; identifying, by the processor, the cluster comprising outlier data based on the comparison to predict anomaly associated with the at least one energy asset.