서울시 공공건축물 에너지 성능개선 리모델링 의사결정을 위한 에너지 사용량 데이터 분석
Energy Performance Assessment for Remodeling Decision-Making based on Energy Usage Data of Existing Public Buildings in Seoul
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초록
The Seoul Metropolitan Government announced a 2050 greenhouse gas reduction strategy through the Green New Deal promotion and proposed a plan to achieve carbon neutrality through the five major areas of green building, green mobility, green forest, green energy, and green cycles. Among them, it is of utmost importance to prepare for the transition of low-carbon zero-energy buildings in the building sector, which accounts for 67% of the total energy consumption and 68.2% of greenhouse gas emissions in Seoul. In particular, 71.4% of the 454,000 buildings in Seoul are aged, and measures to expand to the private sector are needed to overcome the economic crisis caused by COVID-19. Therefore, to prepare a decision-making plan to improve the energy performance of existing buildings, the operation status and energy usage survey were conducted on public buildings with a total floor area of 3,000 m2 or more. The uses of the buildings were classified as cultural, educational, medical, office, and training facilities. A regression analysis algorithm was used to analyze the energy usage patterns and conduct a relative evaluation. The study results are intended to be used as a decision-making method for the energy diagnosis and remodeling of existing buildings.
Abstract
The Seoul Metropolitan Government announced a 2050 greenhouse gas reduction strategy through the Green New Deal promotion and proposed a plan to achieve carbon neutrality through the five major areas of green building, green mobility, green forest, green energy, and green cycles. Among them, it is of utmost importance to prepare for the transition of low-carbon zero-energy buildings in the building sector, which accounts for 67% of the total energy consumption and 68.2% of greenhouse gas emissions in Seoul. In particular, 71.4% of the 454,000 buildings in Seoul are aged, and measures to expand to the private sector are needed to overcome the economic crisis caused by COVID-19. Therefore, to prepare a decision-making plan to improve the energy performance of existing buildings, the operation status and energy usage survey were conducted on public buildings with a total floor area of 3,000 m2 or more. The uses of the buildings were classified as cultural, educational, medical, office, and training facilities. A regression analysis algorithm was used to analyze the energy usage patterns and conduct a relative evaluation. The study results are intended to be used as a decision-making method for the energy diagnosis and remodeling of existing buildings.
참고문헌 (9)
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- Suzuki, K., "Artificial Neural Networks-Architectures and Applications" (2013), IntechOpen Limited
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