Model calibration for building energy efficiency simulation

  • Giorgio Mustafaraj
  • , Dashamir Marini
  • , Andrea Costa
  • , Marcus Keane

Research output: Contribution to a Journal (Peer & Non Peer)Articlepeer-review

174 Citations (Scopus)

Abstract

This research work deals with an Environmental Research Institute (ERI) building where an underfloor heating system and natural ventilation are the main systems used to maintain comfort condition throughout 80% of the building areas. Firstly, this work involved developing a 3D model relating to building architecture, occupancy & HVAC operation. Secondly, the calibration methodology, which consists of two levels, was then applied in order to insure accuracy and reduce the likelihood of errors. To further improve the accuracy of calibration a historical weather data file related to year 2011, was created from the on-site local weather station of ERI building. After applying the second level of calibration process, the values of Mean bias Error (MBE) and Cumulative Variation of Root Mean Squared Error (CV(RMSE)) on hourly based analysis for heat pump electricity consumption varied within the following ranges: (MBE)hourly from -5.6% to 7.5% and CV(RMSE)hourly from 7.3% to 25.1%. Finally, the building was simulated with EnergyPlus to identify further possibilities of energy savings supplied by a water to water heat pump to underfloor heating system. It found that electricity consumption savings from the heat pump can vary between 20% and 27% on monthly bases.

Original languageEnglish
Pages (from-to)72-85
Number of pages14
JournalApplied Energy
Volume130
DOIs
Publication statusPublished - 1 Oct 2014

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Building energy simulation
  • Energy efficiency
  • Heat pump water to water
  • Model calibration
  • Natural ventilation
  • Underfloor heating

Fingerprint

Dive into the research topics of 'Model calibration for building energy efficiency simulation'. Together they form a unique fingerprint.

Cite this