1. A method for predicting anomaly associated with at least one energy asset via a system that includes a processor comprising a data receiver, a depacketizer and a band pass filter, the method comprising: receiving, by the data receiver of the 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, by the data receiver of the processor, time stamped energy data in real time from the at least one energy asset over a network, wherein the time stamped energy data is received in a data packet format comprising encrypted data; translating, by the depacketizer of the processor, the encrypted data from the packet format to a user readable format to generate depacketized data comprising the time stamped energy in the user reasonable format; filtering, by the band filter of the processor, the depacketized data to filter the time stamped energy data within a predetermined range, wherein band pass filter is configured to reject the time stamped energy data that is outside the predetermined range; comparing, by the processor, between the filtered time stamped energy data and the at least one energy signature associated with a cluster; and identifying, by the processor, the cluster comprising outlier data based on the comparison to predict anomaly associated with the at least one energy asset.