Abstract
This paper assesses the energy performance of applying optimal control of air handling unit (AHU) discharge air temperature (DAT). An artificial neural network (ANN) model was used through the link between Matlab and EnergyPlus via BCVTB to realize automatic and optimal control of the AHUDAT. As a result of this study, the predictive control algorithm was able to significantly reduce cooling energy by approximately 10%, compared to a conventional control strategy of fixing AHUDAT to 14°C. These findings suggest that the ANN model and the control algorithm showed energy saving potential for various types of forced air systems by taking dynamic operating conditions into account.
Original language | English |
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Title of host publication | 16th International Conference of the International Building Performance Simulation Association, Building Simulation 2019 |
Editors | Vincenzo Corrado, Enrico Fabrizio, Andrea Gasparella, Francesco Patuzzi |
Publisher | International Building Performance Simulation Association |
Pages | 1802-1808 |
Number of pages | 7 |
ISBN (Electronic) | 9781713809418 |
Publication status | Published - 2019 |
Event | 16th International Conference of the International Building Performance Simulation Association, Building Simulation 2019 - Rome, Italy Duration: 2019 Sept 2 → 2019 Sept 4 |
Publication series
Name | Building Simulation Conference Proceedings |
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Volume | 3 |
ISSN (Print) | 2522-2708 |
Conference
Conference | 16th International Conference of the International Building Performance Simulation Association, Building Simulation 2019 |
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Country/Territory | Italy |
City | Rome |
Period | 19/9/2 → 19/9/4 |
Bibliographical note
Publisher Copyright:© 2019 Building Simulation Conference Proceedings. All rights reserved.
ASJC Scopus subject areas
- Building and Construction
- Architecture
- Modelling and Simulation
- Computer Science Applications