An empirical investigation of V-I trajectory based load signatures for non-intrusive load monitoring

IEEE Transactions on Smart Grid

Volumn 5, Issue 2, 2014, Pages 870-878

  Hassan, Taha ^a   Javed, Fahad ^a   Arshad, Naveed ^a  

^a LAHORE UNIVERSITY OF MANAGEMENT SCIENCES   (Pakistan)

Author keywords

Feedforward neural networks; load monitoring; load signature; optimization; smart grids; supervised learning; support vector machines

Indexed keywords

CLASSIFICATION ALGORITHM; DIFFERENTIAL EVOLUTION; EMPIRICAL INVESTIGATION; EXPERIMENTAL EVALUATION; INSTANTANEOUS VOLTAGE; LOAD MONITORING; NONINTRUSIVE LOAD MONITORING; SMART GRID;

ELECTRIC APPLIANCES; ENERGY UTILIZATION; EVOLUTIONARY ALGORITHMS; FEEDFORWARD NEURAL NETWORKS; FORECASTING; OPTIMIZATION; POWER QUALITY; SUPERVISED LEARNING; SUPPORT VECTOR MACHINES;

CRYPTOGRAPHY;

EID: 84897642995     PISSN: 19493053     EISSN: None     Source Type: Journal    
DOI: 10.1109/TSG.2013.2271282     Document Type: Article

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