Civil Engineering Reference
In-Depth Information
uncertainty resides in the building envelope material in modeling simulation and to
predict its effects on the accuracy of the outcome of building energy consumption.
In my PhD thesis “Effects of sub-optimal equipment of overall energy consumption
and effi ciency of the cooling systems” (Khazaii
2012
) I quantifi ed the effects of the
allowable test tolerance of the HVAC equipment on the energy consumption of a
few typical buildings when it uses a number of different HVAC systems. It was done
on an excel based modeling platform, that I wrote to make the probabilistic simula-
tion possible. In the same research I also presented that “G” section of the ASHRAE
standard (ASHRAE
2013
) champions the comparison between a design building
(a real building subjected to the uncertainties) and a base building (an imaginary
building and therefore not subjected to the uncertainties) energy consumption
(cost). It can be argued that it would be a more accurate modeling exercise, if the
energy modeling software be revised in such manner that it can perform a probabi-
listic simulation (including the uncertainty factors) for the design building, and a
deterministic simulation (as it is currently done) for the base building, before com-
paring the two simulation results, and making decision regarding compliance of the
design building with the standard requirements. Without these changes to the soft-
ware and the standard there is always risk of scoring energy saving credits for a
building (in comparison with the imaginary building) which it is in fact not going to
be realized in the real world.
13.10
Risk Management and Decision Making
What I have discussed in this fi nal chapter and up to this point could become the
source of information and therefore basis for multiple new ideas and solutions. Risk
management and decision making which are the immediate benefi ts of uncertainty
and sensitivity analyses can be the sources of estimation of the future performance,
or future energy cost of any building. Of course one may say people all over the
industry are making decisions every day and as everybody knows every decision
making naturally involves some level of risk taking. That is correct, but what I mean
in this chapter is not a simple blind risk involved decision making. It is actually an
educated risk taking act based on quantifi ed allocated risks to each action. As an
example, assume the commercial software is fully developed in a manner that
designer can include the uncertainty of all the aspects of the building accounted into
the energy model. By doing this the designer can take the results of probabilistic
energy modeling of his building and use that to predict the probability distribution
of the energy consumption and cost for that building in any future period of time.
Such information could be very valuable since it can be communicated with a sim-
ple language containing percentages and numbers. Generally people tend to make
better decisions when they are given the opportunity of knowing how much risk
they are asked to take.
