Alternative Selection Method for Energy Efficiency Improvement of Old Detached House

노후 단독주택의 난방에너지 효율 개선을 위한 대안 선정 방법에 관한 연구

Abstract

More than 76% of the detached houses in Korea are over 20 years old. These old detached houses have poor energy efficiency. According to the 2017 Housing Census (Statistics Korea), more than 50% of low-income families live in detached houses. Therefore, the improvement of energy efficiency in old detached houses is needed from the viewpoint of energy welfare. The general method of building energy modelling for the verification of energy efficiency is based on the construction year data of "Building Design Criteria for Energy Saving" due to the cost and time involved in collecting the thermal performance data of buildings. There is poor accuracy with the deterioration of long-term aging of building materials. Also, the selection of alternatives for energy performance improvement is based on the items to be applied, not a performance improvement goal. It is difficult to calculate energy performance that reflects variations in various parameters with dynamic energy simulations. In this study, the influence of long-term aging is used to accurately predict the energy performance of old detached houses. The building energy modelling method is called ENERGY#, which is a static analysis method based on ISO13790. Energy performance is evaluated by a combination of input variables including building orientation, insulation of walls and roof, thermal performance of windows and window/wall ratio, and infiltration rate. Finally, this study provides a way to determine alternatives that meet energy performance improvement goals.

Fig. 1 Heat gains through windows and heating load by building orientation

Fig. 2 Heating load by performance level of exterior walls and roof

Fig. 3 U-value variate by additional insulation thickness

Fig. 4 Heating load by performance level of windows

Fig. 5 Heating load by variation of window / wall ratio

Fig. 6 Heating load by performance level of infiltration

Fig. 7 Heat gains through windows and building heating load by building orientation

Table 1 Dimensions of standard model

Table 2 U-value criteria for a residential buildings (central region)

Table 3 Thermal properties of window (PVC frame, 12mm gap)

Table 4 Infiltration rate with years building is used

Table 5 Simulation cases

Table 6 Overview of simulation conditions