Significance
Building energy modeling is a robust technique that can enable testing, analyzing, and optimizing different innovate building solutions and technologies. As a result, detailed whole building energy models are seen as useful tools for decision making and energy code compliance. However, these models work at a disaggregated level and thus need extensive databases composed of quantitative data on physically measurable variables (e.g. thermal characteristics of building envelope elements, internal temperatures, heating patterns, etc.). In this regard, one of the most discussed issues in the academic and industrial community is the energy performance gap, which often occurs due to the uncertainty and absence of reliable and accurate modeling input data.
Research has shown that different limitations apply to almost every building performance simulation (BPS) software available today. Therefore, in order to have confidence in the predictions of the whole-building energy models, it is necessary to have a thorough understanding of various features, specific capabilities, and disadvantages of BPS tools.
While existing studies have provided valuable information regarding the capabilities of different BPS tools to perform whole-building energy analysis, many of them have also demonstrated considerable discrepancies between the aggregated energy predictions, and especially for complex buildings, which can undermine the confidence in the use of BPS software for building design optimization and certification. Worse off, there is limited published information that compares different BPS tools on the HVAC system level and especially for complex institutional buildings.
In a recent publication, Dr. Miroslava Kavgic at University of Manitoba and her research team comprising Ali Al-janabi and Ali Mohammadzadeh in collaboration with Ms. Afaf Azzouz at Stantec’s Energy and Mechanical Engineering group proposed to extend the existing knowledge and understanding required for successful integration of BPS tools in different stages of the building design process and code compliance. In addition, they also attempted to address the energy performance gap due to the differences in simulation predictions that may be caused by algorithmic differences, modeling limitations, or input dissimilarities. To this quest, they adopted EnergyPlus (E+) and Integrated Environmental Solutions Virtual Environment (IES VE) software packages. Their work is currently published in the Journal of Building Engineering.
EnergyPlus (E+) and Integrated Environmental Solutions Virtual Environment (IES VE) are both whole-building simulation tool that can simulate multiple building systems while still providing design professionals with a suitable environment for detailed assessment and optimization of building and system designs. The researchers employed the aforementioned software packages in their study where two models were prepared. In general, three model scenarios were described and compared.
The authors reported that by carefully mapping the input parameters, very good agreement between the aggregated energy predictions of the two BPS tools was achieved. Additionally, with regard to temperature prediction of the EnergyPlus and IES models, it was established that the EnergyPlus model was more sensitive to the changes in the outdoor air temperatures compared to the IES model.
In summary, Canadian researchers presented pioneering works in the comparison of EnergyPlus and IES software packages. The approach used entailed comparison of EnergyPlus and IES models of a multi-purpose university building using three scenarios: free-floating, ideal air load system, and detailed. Overall, the approach allowed for an in-depth comparison of the different model complexities that are often used in the building design process. Altogether, valuable information that would come in handy in both academia and industrial set ups was presented.

Reference
Ali Al-janabi, Miroslava Kavgic, Ali Mohammadzadeh, Afaf Azzouz. Comparison of EnergyPlus and IES to model a complex university building using three scenarios: Free-floating, Ideal air load system, and Detailed. Journal of Building Engineering, volume 22, Pages 262-280.
Go To Journal of Building Engineering
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