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:
- Issue 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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