Abstract
Maximizing occupant comfort and minimizing energy costs are two challenging tasks in the efficient operation of any office building. Often these objectives cannot be achieved simultaneously which asks for methods that resolve this trade-off in the best way. Several approaches deal with this problem by focusing on optimizing one of the above criteria while keeping the other one within an acceptable range. However, defining the latter can be very difficult in practice. In particular, setting the acceptable comfort range for offices shared by multiple occupants with conflicting thermal comfort preferences is a challenging problem. This paper presents an intelligent decision support system that assists a building operator in resolving the trade-off between energy efficiency and occupant comfort. Its key component is a case-based reasoning algorithm for predicting the distribution of the occupants’ thermal preferences.
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Schumann, A., Wilson, N. (2011). Predicting the Distribution of Thermal Comfort Votes. In: Mehrotra, K.G., Mohan, C.K., Oh, J.C., Varshney, P.K., Ali, M. (eds) Modern Approaches in Applied Intelligence. IEA/AIE 2011. Lecture Notes in Computer Science(), vol 6704. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21827-9_49
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DOI: https://doi.org/10.1007/978-3-642-21827-9_49
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