Research Papers

Advances in Near-Optimal Control of Passive Building Thermal Storage

[+] Author and Article Information
Gregor P. Henze1

Department of CEAE, University of Colorado at Boulder, Boulder, CO 80309-0428gregor.henze@colorado.edu

Anthony R. Florita, Michael J. Brandemuehl

Department of CEAE, University of Colorado at Boulder, Boulder, CO 80309-0428

Clemens Felsmann

Institut für Energietechnik, Technische Universität Dresden, Dresden D-01187, Germany

Hwakong Cheng

 Taylor Engineering, LLC, 1080 Marina Village Parkway, Suite 501, Alameda, CA 94501-1142


Corresponding author.

J. Sol. Energy Eng 132(2), 021009 (May 10, 2010) (9 pages) doi:10.1115/1.4001466 History: Received August 06, 2009; Revised February 15, 2010; Published May 10, 2010; Online May 10, 2010

Using a simulation and optimization environment, this paper presents advances toward near-optimal building thermal mass control derived from full factorial analyses of the important parameters influencing the passive thermal storage process for a range of buildings and climate/utility rate structure combinations. Guidelines for the application of, and expected savings from, building thermal mass control strategies that can be easily implemented and result in a significant reduction in building operating costs and peak electrical demand are sought. In response to the actual utility rates imposed in the investigated cities, fundamental insights and control simplifications are derived from those buildings deemed suitable candidates. The near-optimal strategies are derived from the optimal control trajectory, consisting of four variables, and then tested for effectiveness and validated with respect to uncertainty regarding building parameters and climate variations. Due to the overriding impact of the utility rate structure on both savings and control strategy, combined with the overwhelming diversity of utility rates offered to commercial building customers, this study cannot offer universally valid control guidelines. Nevertheless, a significant number of cases, i.e., combinations of buildings, weather, and utility rate structure, have been investigated, which offer both insights and recommendations for simplified control strategies. These guidelines represent a good starting point for experimentation with building thermal mass control for a substantial range of building types, equipments, climates, and utility rates.

Copyright © 2010 by American Society of Mechanical Engineers
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Grahic Jump Location
Figure 1

Setpoint trajectory and typical operational modes

Grahic Jump Location
Figure 2

Contribution of factorial combinations to the total savings



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