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.
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| Γλώσσα: | English |
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BRAC University
2016
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| Διαθέσιμο Online: | http://hdl.handle.net/10361/5305 |
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10361-5305 |
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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 |
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1814307968555941888 |