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New artificial neural network prediction method for electrical consumption forecasting based on building end-uses

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New artificial neural network prediction method for electrical consumption forecasting based on building end-uses

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Escrivá-Escrivá, G.; Álvarez Bel, CM.; Roldán Blay, C.; Alcázar-Ortega, M. (2011). New artificial neural network prediction method for electrical consumption forecasting based on building end-uses. Energy and Buildings. 43(11):3112-3119. doi:10.1016/j.enbuild.2011.08.008.

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Título: New artificial neural network prediction method for electrical consumption forecasting based on building end-uses
Autor:
Entidad UPV: Universitat Politècnica de València. Departamento de Ingeniería Eléctrica - Departament d'Enginyeria Elèctrica
Universitat Politècnica de València. Instituto de Ingeniería Energética - Institut d'Enginyeria Energètica
Fecha difusión:
Resumen:
Due to the current high energy prices it is essential to find ways to take advantage of new energy resources and enable consumers to better understand their load curve. This understanding will help to improve customer ...[+]
Palabras clave: Artificial neural networks , Building end-uses , Building energy consumption , Forecast method , Active energy , Artificial Neural Network , Commercial customers , Customer flexibility , Demand response programs , Electrical consumption , Electricity market , End-uses , Fundamental features , High energy prices , In-buildings , Load curves , Short term prediction , Total power consumption , Training data sets , Customer satisfaction , Electric load forecasting , Energy resources , Energy utilization , Forecasting , Sales , Neural networks
Derechos de uso: Reserva de todos los derechos
Fuente:
Energy and Buildings. (issn: 0378-7788 )
DOI: 10.1016/j.enbuild.2011.08.008
Editorial:
Elsevier
Versión del editor: http://dx.doi.org/10.1016/j.enbuild.2011.08.008
Patrocinador:
Universitat Politecnica de Valencia (Spain) [CE 19990032]
Tipo: Artículo

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