Using recurrent artificial neural networks to forecast household electricity consumption

Energy Procedia

Volumn 14, Issue , 2012, Pages 45-55

  Marvuglia, Antonino ^a   Messineo, Antonio ^b  

^a LUXEMBOURG INSTITUTE OF SCIENCE AND TECHNOLOGY   (Luxembourg)

^b KORE UNIVERSITY OF ENNA   (Italy)

Author keywords

Air conditioning systems; Artificial neural networks; Carbon dioxide; Sensitivity analysis; Short term load forecasting

Indexed keywords

AIR CONDITIONING; CARBON DIOXIDE; ELECTRIC POWER UTILIZATION; FORECASTING; NEURAL NETWORKS; SENSITIVITY ANALYSIS;

CONDITIONING EQUIPMENT; DEVELOPED COUNTRIES; ELECTRIC CONSUMPTION; ELECTRICITY DEMANDS; ELECTRICITY-CONSUMPTION; HOUSEHOLD ELECTRICITY CONSUMPTION; RECURRENT ARTIFICIAL NEURAL NETWORKS; SHORT TERM LOAD FORECASTING;

RECURRENT NEURAL NETWORKS;

EID: 84858373926     PISSN: 18766102     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1016/j.egypro.2011.12.1180     Document Type: Conference Paper

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