The DEAP software was found to lack the necessary capabilities to model the shape and form of a building, hampering its analysis of deep or shallow floor plans which have an impact on solar gains and daylighting analysis. The BIM software tools were both capable of utilizing any obtainable weather station data to simulate localized conditions, utilizing the annual vari-ances recorded in regional weather stations. The DEAP software was found to be extremely limited with standardized weather data used and actual building location not accounted for, with an annual mean external temperature used for space and water heating simulations. The study found that weather station data plays a key factor in overall energy performance. Other influential parameters found within the study relate to overall building size, and coverage of primary heating zones. These are pa-rameters that are not currently assessed in the DEAP methodology and are therefore not ed-itable within the DEAP software but can be modelled and assessed within both BIM software suites. The study found that the most influential parameters for building energy performance are related to building location, occupancy patterns, and space heating schedules. This process was implemented to create 26 distinct models through the DEAP and Autodesk Revit software, and 46 model houses within IES VE. The modelling approach was to select distinctive parameters within the three initial houses and to alter them in such a way as to create model iterations that would have different energy performance characteristics. The Dwelling Energy Assessment Procedure (DEAP) software, approved by the Sustainable Energy Authority of Ireland (SEAI) for BER certification in Ireland, was the third software package analysed in the research.
This document is intended as a brief introduction to the plug-in to let you get started.
The simu-lations involved the creation of three distinct model houses, repeated in three different software packages. The aim of the analysis was to assess the capa-bility of BIM based software for BER certification of new housing units in Ireland. Grasshopper) into Revit’s memory, just like any other Revit add-ons. Technically speaking, it is an add-on for Revit that loads Rhino and its plugins (e.g. In this paper, a simulation-based approach was taken to perform sensitivity anal-ysis on building energy consumption datasets. is based on this technology and provides a platform for an unprecedented level of integration between Rhino and Revit.