Title
Reheat optimization of the variable-air-volume box
Document Type
Article
Peer Reviewed
1
Publication Date
1-1-2010
Journal/Book/Conference Title
Energy
Volume
35
Abstract
A data-driven approach for optimizing the reheat process in a variable-air-volume box is presented. Data-mining algorithms derive temporal predictive models from the reheat process data. The bi-objective model formed is solved with a modified particle swarm optimization algorithm. To increase computational efficiency, two levels of non-dominated solutions are introduced while solving the optimization model. A model predictive control strategy is used to generate controls minimizing the reheat output while maintaining the thermal comfort at an acceptable level. 2010 Elsevier Ltd. All rights reserved.
Keywords
Sustainability, A data-driven approach for optimizing the reheat process in a variable-air-volume box is presented. Data-mining algorithms derive temporal predictive models from the reheat process data. The bi-objective model formed is solved with a modified particle swarm optimization algorithm. To increase computational efficiency, two levels of non-dominated solutions are introduced while solving the optimization model. A model predictive control strategy is used to generate controls minimizing the reheat output while maintaining the thermal comfort at an acceptable level. 2010 Elsevier Ltd. All rights reserved.
Published Article/Book Citation
Energy, 35:5 (2010) pp.1997-2005.
URL
http://ir.uiowa.edu/cee_pubs/436