Experimental analysis of the input variables' relevance to forecast next day's aggregated electric demand using neural networks

Energies

Volumn 6, Issue 6, 2013, Pages 2927-2948

  Hernández, Luis ^a   Baladrón, Carlos ^b   Aguiar, Javier M ^b   Calavia, Lorena ^b   Carro, Belén ^b   Sánchez Esguevillas, Antonio ^b   García, Pablo ^c   Lloret, Jaime ^d  

^a CIEMAT   (Spain)

^b UNIVERSITY OF VALLADOLID   (Spain)

^c UNIVERSITY OF OVIEDO   (Spain)

^d UNIVERSITAT POLITÈCNICA DE VALÈNCIA   (Spain)

Author keywords

Aggregated load; Artificial neural network; Microgrid; Multilayer perceptron; Smart grid

Indexed keywords

CLIMATE MODELS; DEEP NEURAL NETWORKS; ELECTRIC POWER PLANT LOADS; ELECTRIC POWER TRANSMISSION NETWORKS; FORECASTING; MULTILAYER NEURAL NETWORKS; MULTILAYERS; NEURAL NETWORKS;

EFFICIENT PREDICTIONS; EXPERIMENTAL ANALYSIS; INTELLIGENT DEVICES; LOAD FORECASTING; MICRO GRID; RESOURCE SAVINGS; SMART GRID; USER SATISFACTION;

SMART POWER GRIDS;

EID: 84880434977     PISSN: None     EISSN: 19961073     Source Type: Journal    
DOI: 10.3390/en6062927     Document Type: Article

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