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Title: System and method for electric load identification and classification employing support vector machine

Abstract

A method identifies electric load types of a plurality of different electric loads. The method includes providing a support vector machine load feature database of a plurality of different electric load types; sensing a voltage signal and a current signal for each of the different electric loads; determining a load feature vector including at least six steady-state features with a processor from the sensed voltage signal and the sensed current signal; and identifying one of the different electric load types by relating the load feature vector including the at least six steady-state features to the support vector machine load feature database.

Inventors:
; ; ; ; ; ;
Publication Date:
Research Org.:
Eaton Intelligent Power Ltd., Dublin (Ireland)
Sponsoring Org.:
USDOE
OSTI Identifier:
1568489
Patent Number(s):
10,325,150
Application Number:
13/597,324
Assignee:
Eaton Intelligent Power Limited (Dublin IE)
DOE Contract Number:  
EE0003911
Resource Type:
Patent
Resource Relation:
Patent File Date: 08/29/2012
Country of Publication:
United States
Language:
English

Citation Formats

Lu, Bin, Harley, Ronald G., Du, Liang, Yang, Yi, Sharma, Santosh K., Zambare, Prachi S., and Madane, Mayura A. System and method for electric load identification and classification employing support vector machine. United States: N. p., 2019. Web.
Lu, Bin, Harley, Ronald G., Du, Liang, Yang, Yi, Sharma, Santosh K., Zambare, Prachi S., & Madane, Mayura A. System and method for electric load identification and classification employing support vector machine. United States.
Lu, Bin, Harley, Ronald G., Du, Liang, Yang, Yi, Sharma, Santosh K., Zambare, Prachi S., and Madane, Mayura A. Tue . "System and method for electric load identification and classification employing support vector machine". United States. https://www.osti.gov/servlets/purl/1568489.
@article{osti_1568489,
title = {System and method for electric load identification and classification employing support vector machine},
author = {Lu, Bin and Harley, Ronald G. and Du, Liang and Yang, Yi and Sharma, Santosh K. and Zambare, Prachi S. and Madane, Mayura A.},
abstractNote = {A method identifies electric load types of a plurality of different electric loads. The method includes providing a support vector machine load feature database of a plurality of different electric load types; sensing a voltage signal and a current signal for each of the different electric loads; determining a load feature vector including at least six steady-state features with a processor from the sensed voltage signal and the sensed current signal; and identifying one of the different electric load types by relating the load feature vector including the at least six steady-state features to the support vector machine load feature database.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {6}
}

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Works referenced in this record:

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Transient event detector for use in nonintrusive load monitoring systems
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Multiprocessing transient event detector for use in a nonintrusive electrical load monitoring system
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