Quantifying the Underlying Causes of a Discrepancy Between Predicted and Measured Energy Use

Simulation is commonly utilized as a best practice approach to assess building performance in the building industry. However, the built environment is complex and influenced by a large number of independent and interdependent variables, making it difficult to achieve an accurate representation of real-world building energy in-use. This gives rise to significant discrepancies between simulation results and actual measured energy consumption, termed “the performance gap.” The research presented in this paper quantified the impact of underlying causes of this gap, by developing building simulation models of four existing non-domestic buildings, and then calibrating them toward their measured energy use at a high level of data granularity. It was found that discrepancies were primarily related to night-time use and seasonality in universities is not being captured correctly, in addition to equipment and server power density being underestimated (indirectly impacting heating and cooling loads). Less impactful parameters were among others; material properties, system efficiencies, and air infiltration assumptions.