International Building Performance Simulation Association - England
Abstract
Building Energy Performance Simulations (BEPS) become more and more common in the design
process of energy efficient buildings. Despite the many attempts to improve the user friendliness
of these applications there is still an important effort required to create a well-adapted model.
One of the main issues is the necessity to re-introduce manually data originating from different
sources: project specific geometry as well as component and material properties from
manufacturers. This tedious and error prone process can lead to poor judgment or input errors
that can have significant impact on the correctness of the model predictions.
In order to tackle these issues, studies have recently set their focus on the use of Building
Information Modelling (BIM) and its standard format Industry Foundation Classes (IFC) to
(partially) automate the BEPS model creation. Nonetheless, most of the existing tools relying on
this concept are either commercial software, complex to use for a non BIM expert or still under
development.
To facilitate the use of an IFC model as a base for BEPS model creation, the focus of this research
is to implement and test an open and easy to use PYTHON package which maps IFC objects and
their relations to objects of a Modelica library to assist the BEPS modeller.
The PYTHON package is intended to reduce the workload and human involvement within the
modelling process by generating automatically a “pre-model”. This “pre-model” is a semi-
configured BEPS obtained from the IFC to Modelica mapping and contains the relevant
information retrieved from the BIM including building geometry, spaces together with a
description of their function and occupation, material properties, HVAC components with their
properties and how they are connected,…
Nevertheless, not all required information for the BEPS-model implementation is present in the
BIM and the modeller might want to reduce model complexity, especially in early design stages,
or introduce additional aspects. The necessity to manually introduce missing data and to adapt
and correct the “pre-model” to obtain the final BEPS-model motivated the use of Modelica which
facilitates model modification from top to component level. A two-phase approach was
implemented: first the IFC model is parsed, relevant information is extracted and a “space
topology” based on the space boundaries characteristics defined in the BIM is generated. In the
second step the “pre-model” for building and systems is created using a template corresponding
to the Modelica library structure.
To investigate the effectiveness and robustness of the implementation, a step-by-step validation
was performed. Starting from a simple four walls building a rigorous checking of the mapping
consistency was undertaken. Gradually the complexity level of the test cases was increased. A
successful mapping to the IDEAS Modelica library was achieved for the BuildingSMART duplex
apartment building case.
Finally the method was applied to a university building with detailed monitoring data available.
The obtained BEPS-model was calibrated and used for fault detection and diagnosis. Despite some
limitations of the current implementation, the PYTHON package significantly improves the
process of BEPS-model creation for the studied building and its HVAC system.status: publishe