3849 -- Hourly Thermal Load Prediction for the Next 24 Hours by ARIMA, EWMA, LR and an Artificial Neural Network PDF

3849 -- Hourly Thermal Load Prediction for the Next 24 Hours by ARIMA, EWMA, LR and an Artificial Neural Network PDF

Name:
3849 -- Hourly Thermal Load Prediction for the Next 24 Hours by ARIMA, EWMA, LR and an Artificial Neural Network PDF

Published Date:
1995

Status:
Active

Description:

Publisher:
ASHRAE

Document status:
Active

Format:
Electronic (PDF)

Delivery time:
10 minutes

Delivery time (for Russian version):
200 business days

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$4.8
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States that predicting the thermal load for the next 24 hours is essential for optimal control of HVAC systems using thermal cool storage. Notes a joint U.S. Japanese research project to investigate four generally-used prediction methods to examine the basic models with variations and to compare the accuracy of each model. States the results indicate that an artificial neural network (ANN) produces the most accurate thermal load predictions. The ANN model was then applied to two measured building loads from another research project and the results confirmed its accuracy.

KEYWORDS: year 1995, Calculating, expert systems, controls, energy storage, cooling, research, comparing, testing, accuracy, cooling load


File Size : 1 file , 1.5 MB
Note : This product is unavailable in Russia, Belarus
Product Code(s) : D-16701
Published : 1995

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