Training free non-intrusive load monitoring of electronic appliances battery charging with low sampling rate

This thesis report is submitted in partial fulfillment of the requirements for the degree of Master of Science in Computer Science and Engineering, 2016.

Bibliografische gegevens
Hoofdauteurs: Nahar, Shamsun, Anjum, SM. Navid
Andere auteurs: Khan, Md. Muhidul Islam
Formaat: Thesis
Taal:English
Gepubliceerd in: BRAC University 2016
Onderwerpen:
Online toegang:http://hdl.handle.net/10361/5305
id 10361-5305
record_format dspace
spelling 10361-53052022-01-26T10:13:12Z Training free non-intrusive load monitoring of electronic appliances battery charging with low sampling rate Nahar, Shamsun Anjum, SM. Navid Khan, Md. Muhidul Islam Department of Computer Science and Engineering, BRAC University EVB Training free NILM-non intrusive load monitoring 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). 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. Shamsun Nahar SM. Navid Anjum B. Computer Science and Engineering 2016-05-22T11:17:39Z 2016-05-22T11:17:39Z 2016 2016-04 Thesis ID 12101026 ID 12101075 http://hdl.handle.net/10361/5305 en BRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. 42 pages application/pdf BRAC University
institution Brac University
collection Institutional Repository
language English
topic EVB
Training free
NILM-non intrusive load monitoring
spellingShingle EVB
Training free
NILM-non intrusive load monitoring
Nahar, Shamsun
Anjum, SM. Navid
Training free non-intrusive load monitoring of electronic appliances battery charging with low sampling rate
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.
author2 Khan, Md. Muhidul Islam
author_facet Khan, Md. Muhidul Islam
Nahar, Shamsun
Anjum, SM. Navid
format Thesis
author Nahar, Shamsun
Anjum, SM. Navid
author_sort Nahar, Shamsun
title Training free non-intrusive load monitoring of electronic appliances battery charging with low sampling rate
title_short Training free non-intrusive load monitoring of electronic appliances battery charging with low sampling rate
title_full Training free non-intrusive load monitoring of electronic appliances battery charging with low sampling rate
title_fullStr Training free non-intrusive load monitoring of electronic appliances battery charging with low sampling rate
title_full_unstemmed Training free non-intrusive load monitoring of electronic appliances battery charging with low sampling rate
title_sort training free non-intrusive load monitoring of electronic appliances battery charging with low sampling rate
publisher BRAC University
publishDate 2016
url http://hdl.handle.net/10361/5305
work_keys_str_mv AT naharshamsun trainingfreenonintrusiveloadmonitoringofelectronicappliancesbatterychargingwithlowsamplingrate
AT anjumsmnavid trainingfreenonintrusiveloadmonitoringofelectronicappliancesbatterychargingwithlowsamplingrate
_version_ 1814307968555941888