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Article: An Extensible Approach for Non-Intrusive Load Disaggregation With Smart Meter Data

TitleAn Extensible Approach for Non-Intrusive Load Disaggregation With Smart Meter Data
Authors
KeywordsHidden Markov models
Home appliances
Smart meters
Load modeling
Data models
Issue Date2018
PublisherInstitute of Electrical and Electronics Engineers. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5165411
Citation
IEEE Transactions on Smart Grid, 2018, v. 9 n. 4, p. 3362-3372 How to Cite?
AbstractAppliance-level load models are expected to be crucial to future smart grid applications. Unlike direct appliance monitoring approaches, it is more flexible and convenient to mine smart meter data to generate load models at device level nonintrusively and generalise to all households with smart meter ownership. This paper proposes a comprehensive and extensible framework to solve the load disaggregation problem for residential households. Our approach examines both the modelling of home appliances as hidden Markov models and the solving of non-intrusive load monitoring based on segmented integer quadratic constraint programming to disaggregate a household power profile into the appliance level. Structure of our approach to be implemented with current smart meter infrastructure is given and simulations are performed based on public datasets. All data are down-sampled to the rate that is consistent with the Australia smart meter infrastructure minimum functionality. The results demonstrate that our approach is able to work with existing smart meters to generate device level load model for other smart grid research and applications.
Persistent Identifierhttp://hdl.handle.net/10722/279141
ISSN
2017 Impact Factor: 7.365
2015 SCImago Journal Rankings: 4.784

 

DC FieldValueLanguage
dc.contributor.authorKong, W-
dc.contributor.authorDong, ZY-
dc.contributor.authorMa, J-
dc.contributor.authorHill, DJ-
dc.contributor.authorZhao, J-
dc.contributor.authorLuo, F-
dc.date.accessioned2019-10-21T02:20:19Z-
dc.date.available2019-10-21T02:20:19Z-
dc.date.issued2018-
dc.identifier.citationIEEE Transactions on Smart Grid, 2018, v. 9 n. 4, p. 3362-3372-
dc.identifier.issn1949-3053-
dc.identifier.urihttp://hdl.handle.net/10722/279141-
dc.description.abstractAppliance-level load models are expected to be crucial to future smart grid applications. Unlike direct appliance monitoring approaches, it is more flexible and convenient to mine smart meter data to generate load models at device level nonintrusively and generalise to all households with smart meter ownership. This paper proposes a comprehensive and extensible framework to solve the load disaggregation problem for residential households. Our approach examines both the modelling of home appliances as hidden Markov models and the solving of non-intrusive load monitoring based on segmented integer quadratic constraint programming to disaggregate a household power profile into the appliance level. Structure of our approach to be implemented with current smart meter infrastructure is given and simulations are performed based on public datasets. All data are down-sampled to the rate that is consistent with the Australia smart meter infrastructure minimum functionality. The results demonstrate that our approach is able to work with existing smart meters to generate device level load model for other smart grid research and applications.-
dc.languageeng-
dc.publisherInstitute of Electrical and Electronics Engineers. The Journal's web site is located at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5165411-
dc.relation.ispartofIEEE Transactions on Smart Grid-
dc.rightsIEEE Transactions on Smart Grid. Copyright © Institute of Electrical and Electronics Engineers.-
dc.rights©20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.-
dc.subjectHidden Markov models-
dc.subjectHome appliances-
dc.subjectSmart meters-
dc.subjectLoad modeling-
dc.subjectData models-
dc.titleAn Extensible Approach for Non-Intrusive Load Disaggregation With Smart Meter Data-
dc.typeArticle-
dc.identifier.emailHill, DJ: dhill@eee.hku.hk-
dc.identifier.authorityHill, DJ=rp01669-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/TSG.2016.2631238-
dc.identifier.scopuseid_2-s2.0-85049009967-
dc.identifier.hkuros307208-
dc.identifier.volume9-
dc.identifier.issue4-
dc.identifier.spage3362-
dc.identifier.epage3372-
dc.publisher.placeUnited States-

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