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System and method employing a self-organizing map load feature database to identify electric load types of different electric loads

Patent ·
OSTI ID:1134210
; ; ; ; ; ;
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.
Research Organization:
Eaton Corporation Cleveland, OH (United States)
Sponsoring Organization:
USDOE
DOE Contract Number:
EE0003911
Assignee:
Eaton Corporation (Cleveland, OH); Georgia Tech Research Corporation (Atlanta, GA)
Patent Number(s):
8,756,181
Application Number:
13/304,758
OSTI ID:
1134210
Country of Publication:
United States
Language:
English

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