Reheat optimization of the variable-air-volume box
Andrew Kusiak and
Energy, 2010, vol. 35, issue 5, 1997-2005
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.
Keywords: Multi-objective optimization; Particle swarm optimization; Variable-air-volume; Reheat process; Model predictive control; Energy savings (search for similar items in EconPapers)
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