Building energy codes are key policy tools for improving building energy efficiency by defining the minimum requirement for the energy performance of new buildings. In Korea, the building energy code was focused on prescriptive criteria for a long time but is now gradually introducing performance criteria. However, switching to performance criteria is not straightforward because of the resistance of the market to abandoning the well-consolidated prescriptive criteria. The objective of this study is to derive appropriate measures to strengthen the prescriptive criteria and the performance criteria, considering both the energy-saving effect and the economic efficiency for new office buildings and educational buildings to increase the market acceptance of the building energy codes. To this end, the energy-saving effects of reference buildings resulting from the reinforcement of the prescriptive criteria in the past have been first analyzed. Then, based on the collected energy performance parameters and cost data, the economic efficiency relative to the energy saving deriving from the application of passive and active energy conservation measures (ECMs) were analyzed, and future building energy code’s reinforcement measures were derived.

The energy consumption of existing buildings depends on their physical features, climatic conditions, and business activities, such as operating hours and occupancy characteristics. It is necessary to perform a fair assessment of building energy performance considering the business activities. It has become especially necessary to collect and manage information on business activities in hospitals since hospitals operate continuously throughout the year, treating patients and using various medical equipment. This study aimed to develop a benchmark that considers business activities and to perform building energy performance assessments in hospitals using the developed benchmark. Initially, the necessary data from hospitals for assessing energy performance and developing an energy benchmark were identified. Then, survey items regarding the business activities and energy consumption of buildings were designed, and a survey was conducted at 48 general hospitals. Secondly, multiple linear regression was used to identify and normalize the major business activities affecting energy use and to develop a benchmark for energy performance assessment. Thereafter, the Energy Efficiency Ratio (EER), the result of comparing the actual energy consumption with the benchmark, was used as an index for the energy performance assessment. Thirdly, additional general hospitals were surveyed to validate the benchmark. The EER of the additional surveyed hospitals was calculated with the developed benchmark. The Energy Use Intensity (EUI) and EER of buildings were reviewed, and analysis was performed to identify why some buildings had a similar EUI but a different EER. Finally, a method to improve the benchmark is presented, and the improved benchmark model is compared with the existing model.