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Prediction of hourly energy consumption in buildings based on a feedback artificial neural network

González, Pedro A. / Zamarreño, Jesús M.

AbstractIn this paper a new approach for short-term load prediction in buildings is shown. The method is based on a special kind of artificial neural network (ANN), which feeds back a part of its outputs. This ANN is trained by means of a hybrid algorithm. The new system uses current and forecasted values of temperature, the current load and the hour and the day as inputs. The performance of this predictor was evaluated using real data and results from international contests. The achieved results demonstrate the high precision reached with this system.

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Prediction of hourly energy consumption in buildings based on a feedback artificial neural network

González, Pedro A. / Zamarreño, Jesús M.

AbstractIn this paper a new approach for short-term load prediction in buildings is shown. The method is based on a special kind of artificial neural network (ANN), which feeds back a part of its outputs. This ANN is trained by means of a hybrid algorithm. The new system uses current and forecasted values of temperature, the current load and the hour and the day as inputs. The performance of this predictor was evaluated using real data and results from international contests. The achieved results demonstrate the high precision reached with this system.

Prediction of hourly energy consumption in buildings based on a feedback artificial neural network

González, Pedro A. / Zamarreño, Jesús M.

AbstractIn this paper a new approach for short-term load prediction in buildings is shown. The method is based on a special kind of artificial neural network (ANN), which feeds back a part of its outputs. This ANN is trained by means of a hybrid algorithm. The new system uses current and forecasted values of temperature, the current load and the hour and the day as inputs. The performance of this predictor was evaluated using real data and results from international contests. The achieved results demonstrate the high precision reached with this system.

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Title:

Prediction of hourly energy consumption in buildings based on a feedback artificial neural network

Contributors:

González, Pedro A. (author) / Zamarreño, Jesús M. (author)

Published in:

Energy and Buildings ; 37 ; 595-601

Publication date:

2004-09-15

Size:

7 pages

ISSN:

DOI:

https://doi.org/10.1016/j.enbuild.2004.09.006

Type of media:

Article (Journal)

Type of material:

Electronic Resource

Language:

English

Keywords:

Intelligent buildings , Energy demands and consumption , Neural networks , Load forecasting , Optimization methods

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