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A user demand and preference profiling method for residential energy management

Published: 13 September 2014 Publication History

Abstract

The home appliance scheduling is a promising energy saving technique that has significant commercial potential. In this paper, a novel method is proposed to profile user demand and preference for residential energy management. Non-Intrusion Load Monitoring (NILM) is applied to identify user operations on each appliance. The operations are integrated with dynamic electric price and environment data to mine users' personal demand and preference on various devices. Finally, the personalized scheduling strategy is generated to meet the different users' demands at the minimal cost. The major contributions of this paper are: 1) NILM is an low-cost and easy-accept solution to profile users' demand, since power meters have been widely deployed and power consumption data are less privacy-related. 2) Five preference indexes are firstly introduced, which can dramatically improve the user's satisfaction on scheduling strategies.

References

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Prasad, R. S., Semwal, S. A simplified new procedure for identification of appliances in smart meter applications. In Proc. SysCon 2013, IEEE (2014).
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    cover image ACM Conferences
    UbiComp '14 Adjunct: Proceedings of the 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct Publication
    September 2014
    1409 pages
    ISBN:9781450330473
    DOI:10.1145/2638728
    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: 13 September 2014

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    Author Tags

    1. energy saving
    2. non-intrusion load monitoring
    3. personalized scheduling
    4. ubiquitous computing
    5. user preference

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    UbiComp '14
    UbiComp '14: The 2014 ACM Conference on Ubiquitous Computing
    September 13 - 17, 2014
    Washington, Seattle

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    Overall Acceptance Rate 764 of 2,912 submissions, 26%

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