New artificial neural network prediction method for electrical consumption forecasting based on building end-uses-Reference-Cited by-同舟云学术

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

Published:2011-11 Issue:11 Volume:43 Page:3112-3119
ISSN:0378-7788
Container-title:Energy and Buildings
language:en
Short-container-title:Energy and Buildings

Author:

Escrivá-Escrivá Guillermo,Álvarez-Bel Carlos,Roldán-Blay Carlos,Alcázar-Ortega Manuel

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Mechanical Engineering,Building and Construction,Civil and Structural Engineering

Reference23 articles.

1. Demand response and electricity market efficiency;Spees;The Electricity Journal,2007

2. The power to choose;International Energy Agency,2003

3. Technical and economical tools to assess customer demand response in the commercial sector;Álvarez-Bel;Energy Conversion and Management,2009

4. G. Escrivá-Escrivá. New tools to encourage active demand response in competitive electricity markets: implementation and settlement. Dissertation to obtain the degree of doctor, June 2009.

5. Short term load forecasting using adaptive pattern recognition and self-organizing techniques;Dillon,1975

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