A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Developing building benchmarking for Brunei Darussalam
Highlights SVM, EM, and OLS were used as benchmarking methods for residential buildings. Results show a variation in EUI for the three methods. The EUI values for residential buildings in Brunei are 2035kWh/person/year and 56kWh/m2/year.
Abstract This paper demonstrates the use of benchmarking methods for residential buildings in an energy rich economy. Three bottom-up methods were used, ordinary least square (OLS), support vector machines (SVM), and engineering modelling (EM). EM highlighted the energy inefficiency in these buildings, where the EM simulations showed the potential of halving the average measured consumption of 20.5MWh/year. SVM could demarcate buildings and households with consumption of >16.0MWh/year which are considered to be inefficiency. OLS is simple to use and the non-linear least square, showing R 2 >0.8, performs better than linear least square fit. This work allows two EUI benchmark measures to be determined and they have average values of 2035kWh/person/year and 56kWh/m2/year.
Developing building benchmarking for Brunei Darussalam
Highlights SVM, EM, and OLS were used as benchmarking methods for residential buildings. Results show a variation in EUI for the three methods. The EUI values for residential buildings in Brunei are 2035kWh/person/year and 56kWh/m2/year.
Abstract This paper demonstrates the use of benchmarking methods for residential buildings in an energy rich economy. Three bottom-up methods were used, ordinary least square (OLS), support vector machines (SVM), and engineering modelling (EM). EM highlighted the energy inefficiency in these buildings, where the EM simulations showed the potential of halving the average measured consumption of 20.5MWh/year. SVM could demarcate buildings and households with consumption of >16.0MWh/year which are considered to be inefficiency. OLS is simple to use and the non-linear least square, showing R 2 >0.8, performs better than linear least square fit. This work allows two EUI benchmark measures to be determined and they have average values of 2035kWh/person/year and 56kWh/m2/year.
Developing building benchmarking for Brunei Darussalam
Shabunko, V. (author) / Lim, C.M. (author) / Brahim, S. (author) / Mathew, S. (author)
Energy and Buildings ; 85 ; 79-85
2014-08-20
7 pages
Article (Journal)
Electronic Resource
English
Developing building benchmarking for Brunei Darussalam
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