A simple and robust approach to energy disaggregation in the presence of outliers

Sustainable Computing: Informatics and Systems

Volumn 9, Issue , 2016, Pages 8-19

  Tang, Guoming ^a   Wu, Kui ^a   Lei, Jingsheng ^b   Tang, Jiuyang ^c  

^a UNIVERSITY OF VICTORIA   (Canada)

^b SHANGHAI UNIVERSITY OF ELECTRIC POWER   (China)

^c NATIONAL UNIVERSITY OF DEFENSE TECHNOLOGY   (China)

Author keywords

Energy disaggregation; Measurement; Non intrusive appliance load monitoring; Optimization

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; ENERGY UTILIZATION; EQUIPMENT; HIDDEN MARKOV MODELS; ITERATIVE METHODS; LEARNING SYSTEMS; LEAST SQUARES APPROXIMATIONS; MARKOV PROCESSES; MEASUREMENTS; OPTIMIZATION; PROBLEM SOLVING; STATISTICS; VOLTAGE DIVIDERS;

DETECTION ACCURACY; DISAGGREGATION; K-MEDIAN CLUSTERING; LEAST SQUARE ESTIMATION; LOCAL OPTIMIZATION ALGORITHM; MACHINE LEARNING METHODS; NON-INTRUSIVE APPLIANCE LOAD MONITORING; POWER CONFIGURATION;

ELECTRIC LOAD MANAGEMENT;

EID: 84960931025     PISSN: 22105379     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.suscom.2016.01.004     Document Type: Article

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