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Real-time detection of smart meter events with odysseus

Authors:

Michael Brand,

Tobias Brandt,

Marco GrawunderAuthors Info & Claims

DEBS '20: Proceedings of the 14th ACM International Conference on Distributed and Event-based Systems

Pages 193 - 198

https://doi.org/10.1145/3401025.3401757

Published: 15 July 2020 Publication History

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Abstract

The energy grid is changing rapidly to include volatile, renewable energy sources to help achieve climate goals. The transition to a smart grid, including smart meters for the metering and communication of the energy consumption, helps with that transition. The smart meters provide a stream of measurements, which can be used for additional services, such as visualization of power consumption. Detecting switching events, when devices in a household are switched on or off, is one possible application on smart meter data.

The goal of the ACM DEBS Grand Challenge 2020 is to implement a live switch detection on a data stream from a smart meter for Non-Intrusive Load Monitoring. This paper presents a solution for the challenge with a general purpose and open source data stream management system that focuses on reusable, generic operators instead of a custom black-box implementation.

References

[1]

H.-Jürgen Appelrath, Dennis Geesen, Marco Grawunder, Timo Michelsen, and Daniela Nicklas. 2012. Odysseus - A Highly Customizable Framework for Creating Efficient Event Stream Management Systems. In Proceedings of the 6th ACM International Conference on Distributed Event-based Systems. Association for Computing Machinery, Berlin, Germany, 367--368.

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[2]

Karim Said Barsim and Bin Yang. 2016. Sequential clustering-based event detection for non-intrusive load monitoring. Computer Science & Information Technology 6 (2016), 77--85.

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[3]

Vincenzo Gulisano, Daniel Jorde, Ruben Mayer, Hannaneh Najdataei, and Dimitris Palyvos-Giannas. 2020. The DEBS 2020 Grand Challenge. In Proceedings of the 14th ACM International Conference on Distributed and Event-Based Systems (DEBS '20). Association for Computing Machinery, New York, NY, USA.

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Index Terms

Real-time detection of smart meter events with odysseus
1. Hardware
  1. Power and energy
    1. Energy distribution
      1. Smart grid
2. Information systems
  1. Data management systems
    1. Database design and models
      1. Data model extensions
        Data streams
    2. Database management system engines
      1. Stream management
  2. Information systems applications
    1. Data mining
      1. Data stream mining

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Published In

DEBS '20: Proceedings of the 14th ACM International Conference on Distributed and Event-based Systems

July 2020

244 pages

ISBN:9781450380287

DOI:10.1145/3401025

Conference Chair:
Julien Gascon-Samson
ÉTS
,
General Chairs:
Kaiwen Zhang
ÉTS Montréal
,
Khuzaima Daudjee
University of Waterloo
,
Bettina Kemme
McGill University

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

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Published: 15 July 2020

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DEBS '20: The 14th ACM International Conference on Distributed and Event-based Systems

July 13 - 17, 2020

Quebec, Montreal, Canada

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Real-time energy data compression strategy for reducing data traffic based on smart grid AMI networks

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