TR2013-065
Smart Meter Data Analysis for Power Theft Detection
-
- "Smart Meter Data Analysis for Power Theft Detection", International Conference on Machine Learning and Data Mining in Pattern Recognion (MLDM), July 2013.BibTeX TR2013-065 PDF
- @inproceedings{Nikovski2013jul,
- author = {Nikovski, D. and Wang, Z. and Esenther, A. and Sun, H. and Sugiura, K. and Muso, T. and Tsuru, K.},
- title = {Smart Meter Data Analysis for Power Theft Detection},
- booktitle = {International Conference on Machine Learning and Data Mining in Pattern Recognion (MLDM)},
- year = 2013,
- month = jul,
- url = {https://www.merl.com/publications/TR2013-065}
- }
,
- "Smart Meter Data Analysis for Power Theft Detection", International Conference on Machine Learning and Data Mining in Pattern Recognion (MLDM), July 2013.
-
MERL Contacts:
-
Research Area:
Abstract:
We propose a method for power theft detection based on predictive models for technical losses in electrical distribution networks estimated entirely from data collected by smart meters in smart grids. Although the data sampling rate of smart meters is not sufficiently high to detect power theft with complete certainty, detection is still possible in a statistical decision theory sense, based on statistical models estimated from collected data sets. Even without detailed knowledge of the exact topology of the distribution network, it is possible to estimate a statistical model of the technical losses that allows indirect estimation of the non-technical losses (power theft) with high accuracy.
Related News & Events
-
NEWS MLDM 2013: publication by Alan W. Esenther, Daniel N. Nikovski, Hongbo Sun and others Date: July 19, 2013
Where: International Conference on Machine Learning and Data Mining in Pattern Recognion (MLDM)
MERL Contacts: Hongbo Sun; Daniel N. Nikovski
Research Area: Data AnalyticsBrief- The paper "Smart Meter Data Analysis for Power Theft Detection" by Nikovski, D., Wang, Z., Esenther, A., Sun, H., Sugiura, K., Muso, T. and Tsuru, K. was presented at the International Conference on Machine Learning and Data Mining in Pattern Recognion (MLDM).