The Effect of Climatic Data on Building Performance Optimization

Marco Manzan (University of Trieste, Department of Engineering and Architecture)

CHALLENGE - This work investigates  the effect of climatic data on the results in an optimization loop applied to a refurbished social housing building. 

SOLUTION - An existing building in Trieste was chosen to run the optimization: it is a historical building and it is composed of four sections with apartments adjacent to each other.  The building was firstly modelled with DesignBuilder, a software interface that uses EnergyPlus as calculation engine. For the present case a python script has been created in order to allow modeFRONTIER to drive the optimization. Primary energy and net present value are used as optimization objectives by modeFRONTIER in order to define new designs. The multi-objective optimization aims to minimize the primary energy and the net present value of the refurbishment investment.

BENEFITS - The results highlight the differences in the optimal choices a designer can obtain by changing the climatic database.