Abstract
The incessant need for energy has raised its cost to unexpected heights. In response to this situation, many projects have been started in order to save energy. In this context, the RIDER project tries to identify pathways for providing recommendations to decrease those costs. The main goal of this project is to develop a weak system dependency of energy management framework which could be applied to different systems and various scales. Particularly, our work focuses on proposing generic optimization techniques for energy management systems. Therefore, our supervision system has to follow RIDER requirements and consider the weak system dependency as well as genericity (i.e., a multi-scale applicable solution). In order to improve the thermal comfort level and/or reduce energy costs, RIDER supervision rules allow the computation of the most relevant setpoints to be provided to the energy control system. Since thermal comfort is a subjective multidimensional concept, an interpretable model is introduced. For this, Multi Attribute Utility Theory is introduced in order to make the multidimensional comfort control problem tractable. In fact, the aggregate objective thermal comfort function proposed by literatures; makes control not intuitive. Thus, interpretable and easily tractable control rules must be designed. The control of thermal comfort is directly based on comfort performance and not on the behavioral model of the supervised building. It guarantees as well its weak system dependency as its multi-scale applicability. This model is embedded in a decision support system that supervises the building energy system control.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Kolokotsa, D., Tsiavos, D., Stavrakakis, G.S., Kalaitzakis, K., Antonidakis, E.: Advanced fuzzy logic controllers design and evaluation for buildings’ occupants thermal: visual comfort and indoor air quality satisfaction. Energy and Buildings 33, 531–543 (2000)
Yang, I.H., Yeo, M.S., Kim, K.W.: Application of artificial neural network to predict the optimal start time for heating system in building. Energy Conversion and Management 44, 2791–2809 (2003)
Pérez-Lombard, L., Ortiz, J., Pout, C.: A review on buildings energy consumption information. Energy and Buildings 40, 394–398 (2008)
Morosan, P.D., Bourdais, R., Dumur, D., Buisson, J.: Building temperature regulation using a distributed model predictive control. Energy and Buildings (2010)
Chwieduk, D.: Towards sustainable-energy buildings. Applied Energy 76, 211–217 (2003)
Jiangjiang, W., Zhiqiang, J.Z., Youyin, J., Chunfa, Z.: Particle swarm optimization for redundant building cooling heating and power system. Applied Energy 87(12), 3668–3679 (2010)
Pohekar, S.D., Ramachandran, M.: Application of multi-criteria decision making to sustainable energy planning-A review. Renewable and Sustainable Energy Reviews 8(4), 365–381 (2004)
Fanger, P.O.: Thermal comfort: analysis and applications in environmental engineering. McGraw-Hill, New York (1972)
Norme, NF EN ISO 7730. Ergonomie des ambiances thermiques : Détermination analytique et interprétation du confort thermique à l’aide de calculs des indices PMV et PPD et du confort thermique local. AFNOR (2006).
Fishburn, P.C.: Utility Theory for Decision-Making. John Wiley & Sons, New York (1970)
Fishburn, P.C.: The foundations of expected utility. Reidel, Dordrecht (1982); Keeney, R.L., und Raiffa, H.: Decisions with Multiple Objectives – Preferences and Value Tradeoffs. Cambridge University Press (1976)
Modave, F., Grabisch, M.: Preference representation by a Choquet integral: Commensurability hypothesis. In: IPMU 1998, Paris, France, pp. 164–171 (1998)
Krantz, D.H., Luce, R.D., Suppes, P., Tversky, A.: Foundations of measurement. In: Additive and Polynomial Representations, vol. 1. Academic Press (1971)
Roy, B.: À propos de la signification des dépendances entre critères: quelle place et quels modes de prise en compte pour l’aide à la décision? RAIRO-Oper. Res. 43, 255–275 (2009)
Grabisch, M., Roubens, M.: The application of fuzzy integrals in multicriteria decision-making. European Journal of Operational Research 89, 445–456 (1996)
Grabisch, M.: k-Ordered Discrete Fuzzy Measures and Their Representation. Fuzzy Sets and Systems 92, 167–189 (1997)
Montmain, J., Trousset, F.: The translation of will into act: achieving a consensus between managerial decisions and operational abilities. In: Information Control Problems in Manufacturing (INCOM), Moscow, Russia (2009)
Labreuche, C.: Construction of a Choquet integral and the value functions without any commensurateness assumption in multi-criteria decision making. In: European Society of Fuzzy Logic and Technology (EUSFLAT-LFA), Aix-les-Bains, France (2011)
Labreuche, C., Grabisch, M.: The Choquet integral for the aggregation of interval scales in multicriteria decision making. Fuzzy Sets & Systems 37, 11–26 (2003)
Sahraoui, S., Montmain, J., Berrah, L., Mauris, G.: User-friendly optimal improvement of an overall industrial performance based on a fuzzy Choquet integral aggregation. In: IEEE International Conference on Fuzzy Systems, London, UK (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Denguir, A., Trousset, F., Montmain, J. (2012). Research for IT Driven Energy Efficiency Based on a Multidimensional Comfort Control* . In: Auweter, A., Kranzlmüller, D., Tahamtan, A., Tjoa, A.M. (eds) ICT as Key Technology against Global Warming. ICT-GLOW 2012. Lecture Notes in Computer Science, vol 7453. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32606-6_2
Download citation
DOI: https://doi.org/10.1007/978-3-642-32606-6_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-32605-9
Online ISBN: 978-3-642-32606-6
eBook Packages: Computer ScienceComputer Science (R0)