research-article

Fundamental limits of nonintrusive load monitoring

Authors:

Lillian Ratliff,

Henrik Ohlsson,

S. Shankar SastryAuthors Info & Claims

HiCoNS '14: Proceedings of the 3rd international conference on High confidence networked systems

Pages 11 - 18

https://doi.org/10.1145/2566468.2566471

Published: 15 April 2014 Publication History

Abstract

Provided an arbitrary nonintrusive load monitoring (NILM) algorithm, we seek bounds on the probability of distinguishing between scenarios, given an aggregate power consumption signal. We introduce a framework for studying a general NILM algorithm, and analyze the theory in the general case. Then, we specialize to the case where the error is Gaussian. In both cases, we are able to derive upper bounds on the probability of distinguishing scenarios. Finally, we apply the results to real data to derive bounds on the probability of distinguishing between scenarios as a function of the measurement noise, the sampling rate, and the device usage.

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Cited By

Góis JPereira L(2023)ANR: A New Metric to Quantify the Appliance to Noise Ratio in Load Disaggregation DatasetsIEEE Transactions on Instrumentation and Measurement10.1109/TIM.2023.331106672(1-8)Online publication date: 2023
https://doi.org/10.1109/TIM.2023.3311066
Huchtkoetter JReinhardt A(2020)On the Impact of Temporal Data Resolution on the Accuracy of Non-Intrusive Load MonitoringProceedings of the 7th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation10.1145/3408308.3427974(270-273)Online publication date: 18-Nov-2020
https://dl.acm.org/doi/10.1145/3408308.3427974
Kaippilly Radhakrishnan KChinh HGupta MPanda SSpanos C(2020)Context-Aware Plug-Load Identification Toward Enhanced Energy Efficiency in the Built EnvironmentIEEE Transactions on Industry Applications10.1109/TIA.2020.301662156:6(6781-6791)Online publication date: Nov-2020
https://doi.org/10.1109/TIA.2020.3016621
Show More Cited By

Index Terms

Fundamental limits of nonintrusive load monitoring
1. Computing methodologies
  1. Modeling and simulation
    1. Simulation theory
      1. Systems theory
2. Mathematics of computing
  1. Information theory

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cover image ACM Conferences

HiCoNS '14: Proceedings of the 3rd international conference on High confidence networked systems

April 2014

162 pages

ISBN:9781450326520

DOI:10.1145/2566468

General Chairs:
Linda Bushnell
University of Washington, USA
,
Larry Rohrbough
University of California, Berkeley, USA
,
Program Chairs:
Saurabh Amin
Massachusetts Institute of Technology, USA
,
Xenofon Koutsoukos
Vanderbilt University, USA

Copyright © 2014 ACM.

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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Publication History

Published: 15 April 2014

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HiCoNS '14

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HiCoNS '14: 3rd International Conference on High Confidence Networked Systems

April 15 - 17, 2014

Berlin, Germany

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HiCoNS '14 Paper Acceptance Rate 12 of 18 submissions, 67%;

Overall Acceptance Rate 30 of 55 submissions, 55%

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Cited By

Góis JPereira L(2023)ANR: A New Metric to Quantify the Appliance to Noise Ratio in Load Disaggregation DatasetsIEEE Transactions on Instrumentation and Measurement10.1109/TIM.2023.331106672(1-8)Online publication date: 2023
https://doi.org/10.1109/TIM.2023.3311066
Huchtkoetter JReinhardt A(2020)On the Impact of Temporal Data Resolution on the Accuracy of Non-Intrusive Load MonitoringProceedings of the 7th ACM International Conference on Systems for Energy-Efficient Buildings, Cities, and Transportation10.1145/3408308.3427974(270-273)Online publication date: 18-Nov-2020
https://dl.acm.org/doi/10.1145/3408308.3427974
Kaippilly Radhakrishnan KChinh HGupta MPanda SSpanos C(2020)Context-Aware Plug-Load Identification Toward Enhanced Energy Efficiency in the Built EnvironmentIEEE Transactions on Industry Applications10.1109/TIA.2020.301662156:6(6781-6791)Online publication date: Nov-2020
https://doi.org/10.1109/TIA.2020.3016621
Held PMauch SSaleh AOuld Abdeslam DBenyoucef D(2019)Frequency Invariant Transformation of Periodic Signals (FIT-PS) for Classification in NILMIEEE Transactions on Smart Grid10.1109/TSG.2018.288684910:5(5556-5563)Online publication date: Sep-2019
https://doi.org/10.1109/TSG.2018.2886849
Nalmpantis CVrakas D(2019)Machine learning approaches for non-intrusive load monitoringArtificial Intelligence Review10.1007/s10462-018-9613-752:1(217-243)Online publication date: 1-Jun-2019
https://dl.acm.org/doi/10.1007/s10462-018-9613-7
Dong RRatliff LCárdenas AOhlsson HSastry S(2018)Quantifying the Utility--Privacy Tradeoff in the Internet of ThingsACM Transactions on Cyber-Physical Systems10.1145/31855112:2(1-28)Online publication date: 23-May-2018
https://dl.acm.org/doi/10.1145/3185511
Held PWeiBhaar DMauch SAbdeslam DBenyoucef D(2018)Parameter Optimized Event Detection for NILM Using Frequency Invariant Transformation of Periodic Signals (FIT-PS)2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA)10.1109/ETFA.2018.8502522(832-837)Online publication date: Sep-2018
https://doi.org/10.1109/ETFA.2018.8502522
Ledva GDu ZBalzano LMathieu J(2018)Disaggregating Load by Type from Distribution System Measurements in Real TimeEnergy Markets and Responsive Grids10.1007/978-1-4939-7822-9_17(413-437)Online publication date: 1-Jun-2018
https://doi.org/10.1007/978-1-4939-7822-9_17
Hong YLiu WWang L(2017)Privacy Preserving Smart Meter Streaming Against Information Leakage of Appliance StatusIEEE Transactions on Information Forensics and Security10.1109/TIFS.2017.270490412:9(2227-2241)Online publication date: Sep-2017
https://doi.org/10.1109/TIFS.2017.2704904
Held PLaasch FAbdeslam DBenyoucef D(2016)Frequency invariant transformation of periodic signals (FIT-PS) for signal representation in NILMIECON 2016 - 42nd Annual Conference of the IEEE Industrial Electronics Society10.1109/IECON.2016.7793617(5149-5154)Online publication date: Oct-2016
https://doi.org/10.1109/IECON.2016.7793617
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