Advanced Building Simulation

26 de Wit
model parameters, which are included in almost all simulation tools, specify default
or “best” values, but lack information on the spread in these values. Second, with the
exception of one or two, none of these tools offer methods to carry out a systematic
sensitivity analysis or to propagate uncertainty. Finally, the possibilities to selectively
refine or simplify model aspects are limited in most simulation environments.
In the building simulation research field, several studies have been dedicated to
uncertainty in the output of building simulations and the building performance
derived from these outputs. Report of the most relevant research can be found in
Lomas and Bowman (1988), Clarke et al. (1990), Pinney et al. (1991), Lomas and
Eppel (1992), Lomas (1993), Martin (1993), Fürbringer (1994), Jensen (1994),
Wijsman (1994), Rahni et al. (1997), de Wit (1997b, 2001), MacDonald et al. (1999),
MacDonald (2002, 2003), de Wit and Augenbroe (2002). These studies indicate that
adequate data on the various uncertainties that may contribute to the uncertainty in
building performance is limited. Among these, uncertainties related to natural variability,
which can sensibly be quantified on the basis of statistical analysis such as
spread in, for example, material properties and building dimensions are relatively
well covered. Modeling uncertainties, though, and other uncertainties that cannot be
comprehensively derived from observed relative frequencies, have received only limited
attention, and usually only on an ad hoc basis. Although several of the studies
have focused on a comparison of techniques for sensitivity analysis and propagation
of uncertainty, these techniques have hardly pervaded the mainstream tools for
building simulation. Virtually no concern is given to the question how quantitative
uncertainty can be used to better-inform a design decision.
This chapter illustrates how uncertainties in building simulations can be addressed
in a rational way, from a first exploration up to the incorporation of explicit uncertainty
information in decision-making. Most attention is given to those issues, which
have been sparsely covered in the building simulation literature, that is modeling
uncertainties and decision-making under uncertainty. To keep the discussion of these
issues as tangible as possible, this chapter is constructed around a specific case.
Section 2.2 presents an outline of the case. Subsequently, in Section 2.3 the main
issues of uncertainty analysis are discussed and applied to the case. Section 2.4 shows
how the uncertainty analysis can be refined, guided by the findings of the analysis in
Section 2.3. A demonstration of how the compiled information on uncertainties can
be constructively used in a decision analysis is elaborated in Section 2.5. Finally,
Section 2.6 concludes with summary and outlook.
2.2 Outline of the case
Uncertainties in building simulations are especially relevant when decisions are made
on the basis of the results. Hence, a decision-making problem is selected as a suitable
case. The context is a (advanced) design stage of an office building in The
Netherlands. In the moderate climate it is possible to make naturally ventilated
buildings, which are comfortable in summer. Hence, the choice to either or not install
a cooling plant is a common design issue. This decision-problem will be addressed
here. In the next section, the main characteristics of the office building and its immediate
environment are outlined. Subsequently, the decision-problem is described in
Section 2.2.2.