Skip to main content
archive
Search Submit Donate Log in
Press Enter to search · Advanced search

Electrical Engineering and Systems Science > Systems and Control

arXiv:1708.00118 (eess)
[Submitted on 1 Aug 2017]

Title:Anomaly Detection Using Optimally-Placed Micro-PMU Sensors in Distribution Grids

Authors:Mahdi Jamei, Anna Scaglione, Ciaran Roberts, Emma Stewart, Sean Peisert, Chuck McParland, Alex McEachern
View a PDF of the paper titled Anomaly Detection Using Optimally-Placed Micro-PMU Sensors in Distribution Grids, by Mahdi Jamei and 6 other authors
View PDF HTML (experimental)
Abstract:As the distribution grid moves toward a tightly-monitored network, it is important to automate the analysis of the enormous amount of data produced by the sensors to increase the operators situational awareness about the system. In this paper, focusing on Micro-Phasor Measurement Unit ($\mu$PMU) data, we propose a hierarchical architecture for monitoring the grid and establish a set of analytics and sensor fusion primitives for the detection of abnormal behavior in the control perimeter. Due to the key role of the $\mu$PMU devices in our architecture, a source-constrained optimal $\mu$PMU placement is also described that finds the best location of the devices with respect to our rules. The effectiveness of the proposed methods are tested through the synthetic and real $\mu$PMU data.
Comments: This article is submitted to IEEE Transaction on Power System and is currently under the review process
Subjects: Systems and Control (eess.SY); Data Analysis, Statistics and Probability (physics.data-an)
Cite as: arXiv:1708.00118 [eess.SY]
  (or arXiv:1708.00118v1 [eess.SY] for this version)
  https://doi.org/10.48550/arXiv.1708.00118
arXiv-issued DOI via DataCite

Submission history

From: Mahdi Jamei [view email]
[v1] Tue, 1 Aug 2017 01:08:35 UTC (836 KB)
Full-text links:

Access Paper:

    View a PDF of the paper titled Anomaly Detection Using Optimally-Placed Micro-PMU Sensors in Distribution Grids, by Mahdi Jamei and 6 other authors
  • View PDF
  • HTML (experimental)
  • TeX Source
view license

Current browse context:

eess.SY
< prev   |   next >
new | recent | 2017-08
Change to browse by:
cs
cs.SY
eess
physics
physics.data-an

References & Citations

  • INSPIRE HEP
  • NASA ADS
  • Google Scholar
  • Semantic Scholar
Loading...

BibTeX formatted citation

Data provided by:

Bookmark

BibSonomy Reddit

Bibliographic and Citation Tools

Bibliographic Explorer (What is the Explorer?)
Connected Papers (What is Connected Papers?)
Litmaps (What is Litmaps?)
scite Smart Citations (What are Smart Citations?)

Code, Data and Media Associated with this Article

alphaXiv (What is alphaXiv?)
CatalyzeX Code Finder for Papers (What is CatalyzeX?)
DagsHub (What is DagsHub?)
Gotit.pub (What is GotitPub?)
Hugging Face (What is Huggingface?)
ScienceCast (What is ScienceCast?)

Demos

Replicate (What is Replicate?)
Hugging Face Spaces (What is Spaces?)
TXYZ.AI (What is TXYZ.AI?)

Recommenders and Search Tools

Influence Flower (What are Influence Flowers?)
CORE Recommender (What is CORE?)
  • Author
  • Venue
  • Institution
  • Topic

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.

Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)
We gratefully acknowledge support from our major funders, member institutions, , and all contributors.
About · Help · Contact · Subscribe · Copyright · Privacy · Accessibility · Operational Status (opens in new tab)
Major funding support from
Simons Foundation Simons Foundation International Schmidt Sciences