Introduction
The purpose of this section is to introduce
the S.D.E.M. software used, explain why the use of an energy
targeting tool is an essential part of our methodology,
as well indicate the assumptions taken during
the progress of S.D.E.M. modeling.
Why S.D.E.M. ?
One of the first obstacles the team faced
in defining the path that leads to a carbon neutral community
was how do describe the housing stock of the case study, with
respect to a greater methodology
that can be applied to any community that aspires to become
carbon neutral.
Initially the team thought that the best way
to describe and analyze the building stock was simply to model
each house. Later on, this thought was rejected due to time
limitations. The team has decided to use S.D.E.M (Strathclyde
Domestic Energy Modeling) tool developed by the University of
Strathclyde for the Scottish Executive. In brief, S.D.E.M. is
a housing stock energy targeting tool that can provide information
regarding the annual energy delivered to a specific housing
stock and the associated carbon emissions. Its function is based
on the classical S.A.P.
(government’s Standard Assessment Procedure) analysis
but the results database originates from a series of ESP-r
(dynamic) simulations.
After the team has finished with the site
survey in Riverside (case
study), the building stock database
has been defined. Due to the outstanding degree of freedom of
the building stock in terms of modeling (build period, house
types, size of houses, type of glazing, heating system details,
fabric improvements, type of appliances, etc) the team has decided
to model the building stock of the community varying 6 essential
parameters and assuming the remaining as common among community's
building stock. Thus, the S.D.E.M. modeling was set for:
• Each Build Period
• Each House type
• Type of Glazing of each house
• Number of rooms in the house
• Size of rooms in the house
• Type of Ceiling (Victorians have a higher Ceiling than
new Builds)
Regarding the parameters indicated below, we assumed
that that these were the same among the community:
• Main heating fuel
• Type of lighting (low energy or filament)
• Attics
• Main heating system and water heating system type and
installation date
• Ventilation
• Fabric upgrades and installation date
• Etc...
After having the building stock database modeled
and ready, the team was able to proceed to the next step of
the methodology (Reduction).
Modeling this step was easier due to the flexibility and the
friendly user interface of S.D.E.M. Two scenarios were created
and modeled: the base case scenario, which describes the current
state of the building stock in the community, and the best case
scenario which represents the summary of the recommendations
we made, covering fabric improvements and the use of efficient
boilers use among others. for more information regarding these
improvements can be found in case
study.
Results:
The results
section in this web report, is a quantification of the recommendations
made for the community and are presented with respect to the
annual energy consumption, the associated carbon dioxide emissions
as well as the cost and payback period of these recommendations.
