ZEMCH 2019 International Conference Proceedings April.2020 | Page 114
Figure 5. Energy performance gap by deficiencies
5. Conclusions
Buildings are responsible for a third of the global final energy consumption and similar levels of
CO 2 emissions as such the energy performance of buildings is an area that has assumed increasing
importance worldwide. Energy efficiency is one of the key objectives of the UAE policies to address the
challenges of energy security and climate change. Substantial steps have been taken towards increasing
energy efficiency in the building sector in the UAE and worldwide. However, there is an extensive
evidence to suggest that building usually do not perform as well as predicted and this discrepancy is
commonly referred to as the “energy performance gap”.
The focus area of this research is using the POE and energy audit data to reduce the energy
performance gap in one of the university buildings in the UAEU. To achieve the main objective of this
study, the POE, building energy audit, and detailed dynamic simulation methods were applied to the
several simulation models. Identifying the cause of discrepancies between as‐designed model and in‐
use model energy performance, and to increase the accuracy of simulation model, POE and energy
audit were carried on.
Through this research, it shows that the case study building in‐use condition is not operated as
designed and almost a quarter of the cooling related energy was wasted by mismanaged and poorly
understood building’s passive and active system strategies. These type of performance gaps are easily
spot in the UAE. This research method is very cost effective and s fast return of investment can be easily
achieved. It also shows that with energy audit and POE study, it is possible to reduce the energy
performance gaps in the building sector with improving the indoor environment quality, especially
after the buildings are occupied and in‐use. This method is able to use calibration of actual conditions
of the building with computer‐generated energy simulation model to improve accuracy of the
simulation model, which means it could therefore reduce the gap between numerical/computational
prediction and actual usage as well.
Author Contributions: Dr. Young and Dr. Lindita conceived the presented idea. Dr. Young developed the theory
and performed the computations. Dr. Young and Dr. Lindita verified the analytical methods. Prof. Anissa and Prof.
Hasim encouraged Dr. Young to investigate POE study and supervised the findings of this work. All authors
discussed the results and contributed to the manuscript.
Funding: This research was funded by the UAEU, grant name and number are 2018 Start ‐ UP (31N380).
Acknowledgments: The authors would like to thank the UAEU for supporting the study and allowing for the
measurements to take place.
Conflicts of Interest: The authors declare no conflict of interest and the funders had no role in the design of the
study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to
publish the results.
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ZEMCH 2019 International Conference l Seoul, Korea