Abstract
The building sector contributes to about 40% of total energy consumption in South Korea. In particular, existing buildings older than 15 years account for 75% of the energy consumption by the entire building sector in South Korea. When assessing energy performance of existing buildings by the use of dynamic simulation tools, there are a variety of barriers, e.g. cost, time, expertise, lack of building information, etc. In this study, the authors developed a building energy profiling system that provides quick and easy energy performance assessment of existing buildings. The building energy profiling system is based on a number of EnergyPlus simulation runs and Artificial Neural Network models. For the ANN models, a series of EnergyPlus pre-simulations were sampled by a Monte Carlo technique. Though the profiling system requires minimalistic inputs, it can provide information on (1) energy performance level of a given building, (2) energy benchmarking against peer buildings, and (3) quantification of energy conservation measures.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Journal of the Architectural Institute of Korea Structure & Construction
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
