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    •   BracU IR
    • School of Data and Sciences (SDS)
    • Department of Computer Science and Engineering (CSE)
    • Thesis & Report, BSc (Computer Science and Engineering)
    • View Item
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    Training free non-intrusive load monitoring of electronic appliances battery charging with low sampling rate

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    12101026.pdf (1.091Mb)
    Date
    2016-04
    Publisher
    BRAC University
    Author
    Nahar, Shamsun
    Anjum, SM. Navid
    Metadata
    Show full item record
    URI
    http://hdl.handle.net/10361/5305
    Abstract
    Non-intrusive load monitoring (NILM) is a convenient method to determine the amount of energy consumed by individual electrical appliances of our household and operate them by analyzing the composite load measured directly at the main circuit panel or electric meter of the building. A significant reduction in the energy wastage can be achieved through this approach. A lot of remarkable researches were developed to establish the theory of NILM and introduced its innovative applications. However, forthcoming deployment of electronic vehicle battery (EVB) will challenge NILM systems as the previous methods are not suitable for recognizing the variable characteristics of it. In this paper, we propose an improved algorithm to disaggregate EV charging signals from aggregated real power signals. The proposed method can effectively mitigate interference coming from air-conditioner (AC) and detect EVB signals effectively under the presence of AC power signals. The results demonstrate that the EVB charging load is recognized as well as other traditional appliances.
    Keywords
    EVB; Training free; NILM-non intrusive load monitoring
     
    Description
    This thesis report is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2016.
     
    Cataloged from PDF version of thesis report.
     
    Includes bibliographical references (page 40-42).
    Department
    Department of Computer Science and Engineering, BRAC University
    Collections
    • Thesis & Report, BSc (Computer Science and Engineering)

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