Abstract

Deregulation of the energy sector has created new markets for producers as well as opportunities for consumers to meet their needs in a more customized way. Yet, traditional building energy management systems operate statically by adjusting air or water flow in heating and cooling systems in response to predetermined triggers, in relation to large deviations in the zone temperature from the equipment’s set-point temperature. The writers provide decision support to managers of buildings through dynamic control of the installed equipment that seeks to minimize energy costs. Assuming that the building’s occupants have comfort preferences expressed by upper and lower limits for the temperature, the writers model the effect of active equipment control (through changes to either the set point or valve flow) on the zone temperature, taking into account the external temperature, solar gains, building’s shell, and internal loads. The energy required to change the zone temperature in each time period is then used to calculate the energy cost in the objective function of an optimization problem. By implementing the model for actual public buildings, the writers demonstrate the advantages of more active equipment-management in terms of lower costs and energy consumption.

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Acknowledgments

The research leading to the results reported in this paper has received funding from the European Union Seventh Framework Programme (FP7/2007–2013) under grant agreement number 260041 for the collaborative project “Energy Efficiency and Risk Management in Public Buildings” (EnRiMa). The Center for Energy and Innovative Technologies (CET) is supported by the Austrian Federal Ministry for Transport, Innovation, and Technology through the “Building of Tomorrow” program and by the Theodor Kery Foundation of the province of Burgenland. The cooperation of Centro de Adultos La Arboleya of Fundación Asturiana de Atención y Protección a Personas con Discapacidades y/o Dependencias (Siero, Asturias, Spain), Fachhochschule Burgenland’s Pinkafeld campus (Burgenland, Austria), and Fachhochschule Technikum Wien’s ENERGYbase facility (Vienna, Austria) has greatly enhanced the writers’ understanding of energy management at the building level. The writers are grateful for comments received from attendees of the Computational Management Science Conference in London, U.K. (April 18–20, 2012) and the XXV EURO Conference in Vilnius, Lithuania (July 8–11, 2012). The writers have benefited from the suggestions provided by the associate editor and two anonymous referees. Feedback from Angel Luis Alvarez Iglesias (HC Energía), Emilio L. Cano (Universidad Rey Juan Carlos), and Paula Rocha (University College London) has also helped to improve this paper. All remaining errors are the writers’ own.

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Go to Journal of Energy Engineering
Journal of Energy Engineering
Volume 140Issue 1March 2014

History

Received: Mar 15, 2013
Accepted: Jun 24, 2013
Published online: Jun 26, 2013
Published in print: Mar 1, 2014
Discussion open until: May 11, 2014

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Markus Groissböck [email protected]
Center for Energy and Innovative Technologies, HofamtPriel A-3681 Austria. E-mail: [email protected]
Somayeh Heydari [email protected]
Dept. of Statistical Science, Univ. College London, London WC1E 6BT, U.K. E-mail: [email protected]
Energy and Environment Division, Tecnalia Research and Innovation, Bizkaia 48160, Spain. E-mail: [email protected]
Eugenio Perea [email protected]
Energy and Environment Division, Tecnalia Research and Innovation, Bizkaia 48160, Spain. E-mail: [email protected]
Afzal S. Siddiqui [email protected]
Dept. of Statistical Science, Univ. College London, London WC1E 6BT, U.K.; and Dept. of Computer and Systems Sciences, Stockholm Univ., Stockholm, SE-164 40 Kista, Sweden (corresponding author). E-mail: [email protected]
Michael Stadler [email protected]
Center for Energy and Innovative Technologies, HofamtPriel A-3681, Austria. E-mail: [email protected]

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