Family houses energy consumption forecast tools for smart grid management

Lecture Notes in Electrical Engineering

Volumn 402, Issue , 2017, Pages 691-699

  Rodrigues, F ^a,b   Cardeira, C ^a   Calado, J M F ^a,c   Melicio R ^a,d  

^a INSTITUTO SUPERIOR TÉCNICO   (Portugal)

^b MASSACHUSETTS INSTITUTE OF TECHNOLOGY   (United States)

^c INSTITUTO SUPERIOR DE ENGENHARIA DE LISBOA   (Portugal)

^d UNIVERSITY OF ÉVORA   (Portugal)

Author keywords

Artificial neural networks; Energy forecasting; Energy management; Gradient methods; Smart grids

Indexed keywords

AUTOMATION; ELECTRIC POWER TRANSMISSION NETWORKS; ELECTRIC UTILITIES; EMBEDDED SYSTEMS; ENERGY MANAGEMENT; ENERGY UTILIZATION; FORECASTING; GRADIENT METHODS; HOUSES; NEURAL NETWORKS; PROCESS CONTROL;

CYBER-PHYSICAL SYSTEMS (CPS); DEMAND RESPONSE; ELECTRIC GENERATION; ELECTRICITY-CONSUMPTION; ENERGY FORECASTING; GENERALIZED REDUCED GRADIENT; RELIABLE MODELS; SMART GRID;

SMART POWER GRIDS;

EID: 84988493757     PISSN: 18761100     EISSN: 18761119     Source Type: Book Series    
DOI: 10.1007/978-3-319-43671-5_58     Document Type: Conference Paper

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