Power consumption profiling using energy time-frequency distributions in smart grids

Marnerides, Angelos and Schaeffer-Filho, Alberto and Smith, Paul and Mauthe, Andreas (2015) Power consumption profiling using energy time-frequency distributions in smart grids. IEEE Communications Letters, 19 (1). pp. 46-49. ISSN 1089-7798

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Abstract

Smart grids are power distribution networks that include a significant communication infrastructure, which is used to collect usage data and monitor the operational status of the grid. As a consequence of this additional infrastructure, power networks are at an increased risk of cyber-attacks. In this letter, we address the problem of detecting and attributing anomalies that occur in the sub-meter power consumption measurements of a smart grid, which could be indicative of malicious behavior. We achieve this by clustering a set of statistical features of power measurements that are determined using the Smoothed Pseudo Wigner Ville (SPWV) energy Time-Frequency (TF) distribution. We show how this approach is able to more accurately distinguish clusters of energy consumption than simply using raw power measurements. Our ultimate goal is to apply the principles of profiling power consumption measurements as part of an enhanced anomaly detection system for smart grids.

Item Type:
Journal Article
Journal or Publication Title:
IEEE Communications Letters
Additional Information:
©2015 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Uncontrolled Keywords:
/dk/atira/pure/subjectarea/asjc/2600/2611
Subjects:
?? modelling and simulationcomputer science applicationselectrical and electronic engineering ??
ID Code:
72746
Deposited By:
Deposited On:
30 Jan 2015 11:31
Refereed?:
Yes
Published?:
Published
Last Modified:
10 Jan 2024 00:18