Martin Gough Award: Runner-up Paper

Adelaide, Australia

Martin Gough Award: Runner-up Paper

Key Facts

Calibration process of apartment

  • investigated possibilities of energy independent residential buildings in fast-growing megacity

Studied the important role of building performance simulation

  • in accurately reproducing real-world results in a virtual model

Measured hourly indoor air temperature

  • 1.37% CV (RMSE)

Monthly electricity consumption

  • 7.42% CV (RMSE)

In the first year of the Martin Gough student award, the prize for second place goes to Rehnuma Parveen, PhD student from the University of Adelaide, with her paper ‘IES-VE for Achieving Energy Independence’.

Read on to find out more about Rehnuma’s research paper and what it means to her to be selected as this year’s runner-up.

The 2nd Prize Paper
Rehnuma’s paper presented a case study of the calibration process of an apartment, which investigated the possibilities of energy independent residential buildings in a fast-growing megacity in the developing world. The project used the IES Virtual Environment (IESVE) for obtaining its outcomes. In the current context of global warming, it is imperative that buildings improve their energy efficiency. The paper studied the important role of building performance simulation tools in this regard and the importance of accurately reproducing real-world results in a virtual model. Rehnuma concluded that calibrating the model with real-time measured data is one of the procedures that must be followed to ensure the model’s reliability.

A calibrated model’s reliability can be measured. The most commonly used method to evaluate how well the model has replicated the real-world situation is to calculate the coefficient of variance of the root-mean-square error (CV (RMSE)) between the simulated data and the measured data. A model that achieves at least 20% CV (RMSE) is generally considered acceptable. In this study, the calibration of the model with the measured hourly indoor air temperature achieved 1.37% CV (RMSE) and with the monthly electricity consumption achieved 7.42% CV (RMSE).

This paper concludes that the IESVE can produce a highly calibrated model that can be utilised to establish energy independence.

Could you be a prize winner next year?
Congratulations again to Rehnuma. Entries for next year’s award will open in early 2019. If you are interested in taking part, please register for updates via our newsletter or watch this space for further details being posted in due course.