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Home Energy Simulation for Non-Intrusive Load Monitoring Applications

Authors:

Krishnan Srinivasarengan,

Y. G. Goutam,

M. Girish ChandraAuthors Info & Claims

ES4CPS '14: Proceedings of International Workshop on Engineering Simulations for Cyber-Physical Systems

Pages 9 - 12

https://doi.org/10.1145/2589650.2559630

Published: 11 November 2013 Publication History

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Abstract

Home Energy Management (HEM) is a vital component of smart grid, which can be considered as a distributed cyber physical system. HEM involves appropriate management of home appliance usage through deliberate efforts from the end-user. This can enable a stable operation of the grid as well as reduce energy usage and bills for the end-user. The installation of smart meter has led to a number of analytics and applications developed on top of its data. However, the algorithms are evaluated over a very small subset of experimental or open dataset. To mitigate this problem, a bottom-up data generation approach is proposed in this paper. The appliances are considered as combination of fundamental electrical components. The appliance characteristics and operations are modeled through stochastic parameters, which are available as prior information or through learning from existing meter data. Preliminary results of generating data for the application of Non-Intrusive Load Monitoring is presented.

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Cited By

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Kumar KChandra M(2021)Transform Learning Assisted Graph Signal Processing for Low Rate Electrical Load Disaggregation2020 28th European Signal Processing Conference (EUSIPCO)10.23919/Eusipco47968.2020.9287576(1673-1677)Online publication date: 24-Jan-2021
https://doi.org/10.23919/Eusipco47968.2020.9287576
Kumar KChandra M(2017)An intuitive explanation of graph signal processing-based electrical load disaggregation2017 IEEE 13th International Colloquium on Signal Processing & its Applications (CSPA)10.1109/CSPA.2017.8064932(100-105)Online publication date: Mar-2017
https://doi.org/10.1109/CSPA.2017.8064932

Index Terms

Home Energy Simulation for Non-Intrusive Load Monitoring Applications
1. Information systems
  1. Information systems applications

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Published In

ES4CPS '14: Proceedings of International Workshop on Engineering Simulations for Cyber-Physical Systems

March 2014

44 pages

ISBN:9781450326148

DOI:10.1145/2589650

Conference Chairs:
C. Berger,
I. Schaefer

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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Technische Universität Ilmenau: Technische Universität Ilmenau

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 11 November 2013

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ES4CPS '14: International Workshop on Engineering Simulations for Cyber-Physical Systems

March 28, 2014

Dresden, Germany

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Kumar KChandra M(2021)Transform Learning Assisted Graph Signal Processing for Low Rate Electrical Load Disaggregation2020 28th European Signal Processing Conference (EUSIPCO)10.23919/Eusipco47968.2020.9287576(1673-1677)Online publication date: 24-Jan-2021
https://doi.org/10.23919/Eusipco47968.2020.9287576
Kumar KChandra M(2017)An intuitive explanation of graph signal processing-based electrical load disaggregation2017 IEEE 13th International Colloquium on Signal Processing & its Applications (CSPA)10.1109/CSPA.2017.8064932(100-105)Online publication date: Mar-2017
https://doi.org/10.1109/CSPA.2017.8064932

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Recommendations

An Intercommunication Home Energy Management System with Appliance Recognition in Home Network

Detecting Anomalies in Activities of Daily Living of Elderly Residents via Energy Disaggregation and Cox Processes

A Survey of Home Energy Management Systems in Future Smart Grid Communications