System and method employing a self-organizing map load feature database to identify electric load types of different electric loads
Abstract
A method identifies electric load types of a plurality of different electric loads. The method includes providing a self-organizing map load feature database of a plurality of different electric load types and a plurality of neurons, each of the load types corresponding to a number of the neurons; employing a weight vector for each of the neurons; sensing a voltage signal and a current signal for each of the loads; determining a load feature vector including at least four different load features from the sensed voltage signal and the sensed current signal for a corresponding one of the loads; and identifying by a processor one of the load types by relating the load feature vector to the neurons of the database by identifying the weight vector of one of the neurons corresponding to the one of the load types that is a minimal distance to the load feature vector.
- Inventors:
- Issue Date:
- Research Org.:
- Eaton Corporation Cleveland, OH (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 1134210
- Patent Number(s):
- 8756181
- Application Number:
- 13/304,758
- Assignee:
- Eaton Corporation (Cleveland, OH); Georgia Tech Research Corporation (Atlanta, GA)
- Patent Classifications (CPCs):
-
G - PHYSICS G06 - COMPUTING G06N - COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
Y - NEW / CROSS SECTIONAL TECHNOLOGIES Y04 - INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS Y04S - SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- DOE Contract Number:
- EE0003911
- Resource Type:
- Patent
- Resource Relation:
- Patent File Date: 2011 Nov 28
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION
Citation Formats
Lu, Bin, Harley, Ronald G., Du, Liang, Yang, Yi, Sharma, Santosh K., Zambare, Prachi, and Madane, Mayura A. System and method employing a self-organizing map load feature database to identify electric load types of different electric loads. United States: N. p., 2014.
Web.
Lu, Bin, Harley, Ronald G., Du, Liang, Yang, Yi, Sharma, Santosh K., Zambare, Prachi, & Madane, Mayura A. System and method employing a self-organizing map load feature database to identify electric load types of different electric loads. United States.
Lu, Bin, Harley, Ronald G., Du, Liang, Yang, Yi, Sharma, Santosh K., Zambare, Prachi, and Madane, Mayura A. Tue .
"System and method employing a self-organizing map load feature database to identify electric load types of different electric loads". United States. https://www.osti.gov/servlets/purl/1134210.
@article{osti_1134210,
title = {System and method employing a self-organizing map load feature database to identify electric load types of different electric loads},
author = {Lu, Bin and Harley, Ronald G. and Du, Liang and Yang, Yi and Sharma, Santosh K. and Zambare, Prachi and Madane, Mayura A.},
abstractNote = {A method identifies electric load types of a plurality of different electric loads. The method includes providing a self-organizing map load feature database of a plurality of different electric load types and a plurality of neurons, each of the load types corresponding to a number of the neurons; employing a weight vector for each of the neurons; sensing a voltage signal and a current signal for each of the loads; determining a load feature vector including at least four different load features from the sensed voltage signal and the sensed current signal for a corresponding one of the loads; and identifying by a processor one of the load types by relating the load feature vector to the neurons of the database by identifying the weight vector of one of the neurons corresponding to the one of the load types that is a minimal distance to the load feature vector.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Jun 17 00:00:00 EDT 2014},
month = {Tue Jun 17 00:00:00 EDT 2014}
}
Save to My Library
You must Sign In or Create an Account in order to save documents to your library.
Works referenced in this record:
Non-intrusive appliance monitor apparatus
patent, August 1989
- Hart, George W.; Kern, Jr., Edward C.; Schweppe, Fred C.
- US Patent Document 4,858,141
Transient event detector for use in nonintrusive load monitoring systems
patent, January 1996
- Leeb, Steven B.; Kirtley, Jr., James L.
- US Patent Document 5,483,153
Multiprocessing transient event detector for use in a nonintrusive electrical load monitoring system
patent, February 1998
- Leeb, Steven B.; Khan, Umair A.; Shaw, Steven R.
- US Patent Document 5,717,325
Perceptive system including a neural network
patent, November 1998
- Duvoisin, III, Herbert; Beck, Hal E.; Brown, Joe R.
- US Patent Document 5,835,901
Device for preventive detection of faults with recognition of the type of load
patent, June 1999
- Tian, Simon; Kasbarian, Jean-Marc
- US Patent Document 5,910,875
Device for preventive detection of faults with identification of the type of load
patent, June 2000
- Kasbarian, Jean-Marc; Tian, Simon; Hanchin, Pascal
- US Patent Document 6,081,123
Arc fault circuit interrupter for a compressor load
patent, September 2007
- Parker, Kevin L.; Elms, Robert T.
- US Patent Document 7,268,989
Arc fault circuit interrupter
patent, April 2008
- Elms, Robert T.; Parker, Kevin L.; Zuercher, Joseph C.
- US Patent Document 7,362,552
Detecting actuation of electrical devices using electrical noise over a power line
patent-application, March 2009
- Patel, Shwetak N.; Robertson, Thomas M.; Abowd, Gregory D.
- US Patent Document 12/283869; 20090072985
Unsupervised learning strategies for the detection and classification of transient phenomena on electric power distribution systems
conference, January 1991
- Lubkeman, D. L.; Fallon, C. D.; Girgis, A. A.
- Proceedings of the First International Forum on Applications of Neural Networks to Power Systems
A neuron nets based procedure for identifying domestic appliances pattern-of-use from energy recordings at meter panel
conference, January 2002
- Prudenzi, A.
- Winter Meeting of the Power Engineering Society, 2002 IEEE Power Engineering Society Winter Meeting. Conference Proceedings (Cat. No.02CH37309)
Artificial neural networks in measurements
journal, March 1998
- Daponte, P.; Grimaldi, D.
- Measurement, Vol. 23, Issue 2, p. 93-115
Classification, Filtering, and Identification of Electrical Customer Load Patterns Through the Use of Self-Organizing Maps
journal, November 2006
- Verdu, S. V.; Garcia, M. O.; Senabre, C.
- IEEE Transactions on Power Systems, Vol. 21, Issue 4
Neural-Network-Based Signature Recognition for Harmonic Source Identification
journal, January 2006
- Srinivasan, D.; Ng, W. S.; Liew, A. C.
- IEEE Transactions on Power Delivery, Vol. 21, Issue 1
A Novel Method to Construct Taxonomy Electrical Appliances Based on Load Signaturesof
journal, January 2007
- Lam, H.; Fung, G.; Lee, W.
- IEEE Transactions on Consumer Electronics, Vol. 53, Issue 2
Nonintrusive appliance load monitoring
journal, January 1992
- Hart, G. W.
- Proceedings of the IEEE, Vol. 80, Issue 12
Nonintrusive monitoring of electric loads
journal, January 1999
- Drenker, S.; Kader, A.
- IEEE Computer Applications in Power, Vol. 12, Issue 4
Nonintrusive load disaggregation computer program to estimate the energy consumption of major end uses in residential buildings
journal, September 2000
- Marceau, M. L.; Zmeureanu, R.
- Energy Conversion and Management, Vol. 41, Issue 13, p. 1389-1403
Nonintrusive identification of electrical loads in a three-phase environment based on harmonic content
conference, January 2000
- Cole, A.; Albicki, A.
- Proceedings of the 17th IEEE Instrumentation and Measurement Technology Conference [Cat. No. 00CH37066]
Harmonics load signature recognition by wavelets transforms
conference, January 2000
- Chan, W. L.; So, A. T. P.; Lai, L. L.
- International Conference on Electric Utility Deregulation and Restructuring, and Power Technologies 2000, DRPT2000. International Conference on Electric Utility Deregulation and Restructuring and Power Technologies. Proceedings (Cat. No.00EX382)
Nonintrusive Load Monitoring and Diagnostics in Power Systems
journal, July 2008
- Shaw, S. R.; Leeb, S. B.; Norford, L. K.
- IEEE Transactions on Instrumentation and Measurement, Vol. 57, Issue 7
A review of identification and monitoring methods for electric loads in commercial and residential buildings
conference, September 2010
- Du, Yi; Du, Liang; Lu, Bin
- 2010 IEEE Energy Conversion Congress and Exposition (ECCE)
Applications of hierarchical support vector machines for identifying load operation in nonintrusive load monitoring systems
conference, June 2011
- Yu-Hsiu Lin,
- 2011 9th World Congress on Intelligent Control and Automation (WCICA 2011)
Design a Neural Network for Features Selection in Non-intrusive Monitoring of Industrial Electrical Loads
conference, April 2007
- Yang, Hong-Tzer; Chang, Hsueh-Hsien; Lin, Ching-Lung
- 2007 11th International Conference on Computer Supported Cooperative Work in Design
Using neural networks for non-intrusive monitoring of industrial electrical loads
conference, January 1994
- Roos, J. G.; Lane, I. E.; Botha, E. C.
- IEEE Instrumentation and Measurement Technology Conference - IMTC '94, Conference Proceedings. 10th Anniversary. IMTC/94. Advanced Technologies in I & M. 1994 IEEE Instrumentation and Measurement Technolgy Conference (Cat. No.94CH3424-9)
Clustering method using self-organizing map
conference, January 2000
- Endo, M.; Ueno, M.; Tanabe, T.
- Neural Networks for Signal Processing X. Proceedings of the 2000 IEEE Signal Processing Society Workshop (Cat. No.00TH8501)
Automatic data classification by a hierarchy of self-organizing maps
conference, January 1999
- Costa, J. A. F.; de Andrade Netto, M. L.
- IEEE SMC'99 Conference Proceedings. 1999 IEEE International Conference on Systems, Man, and Cybernetics (Cat. No.99CH37028)