2011한국생태환경건축학회 학술발표대회 논문집Requires access

PHPP를 이용한 한국형 플러스에너지 주택의 건물 에너지 성능 분석

정선미, 권영철, 이성진

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Abstract

This study investigated energy performance of plus energy house and analyzed the energy efficiency of a two-storied residential building using Passive House Planning Package(PHPP), which was made by Passive House Institute in Germany. The specific space heating demand(PH/ATFA) of the house is 14.3㎾h/㎡ yr which meets passive house standards, and heating loads are not found from April to October. Its specific useful cooling energy demand(PC/ATFA) is 4.8㎾h/㎡ yr which also meets passive house standards, and there are no cooling loads from October to May.

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What this paper is about

This study investigated energy performance of plus energy house and analyzed the energy efficiency of a two-storied residential building using Passive House Planning Package(PHPP), which was made by Passive House Institute in Germany. The specific space heating demand(PH/ATFA) of the house is 14.3㎾h/㎡ yr which meets passive house standards, and heating loads are not found from April to October. Its specific useful cooling energy demand(PC/ATFA) is 4.8㎾h/㎡ yr which also meets passive house standards, and there are no cooling loads from October to May.

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Available abstract

This study investigated energy performance of plus energy house and analyzed the energy efficiency of a two-storied residential building using Passive House Planning Package(PHPP), which was made by Passive House Institute in Germany. The specific space heating demand(PH/ATFA) of the house is 14.3㎾h/㎡ yr which meets passive house standards, and heating loads are not found from April to October. Its specific useful cooling energy demand(PC/ATFA) is 4.8㎾h/㎡ yr which also meets passive house standards, and there are no cooling loads from October to May.

Key concepts: Passive house, Energy demand, Architectural engineering, Passive cooling, Environmental science, Efficient energy use, Engineering, Meteorology

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PHPP를 이용한 한국형 플러스에너지 주택의 건물 에너지 성능 분석 — Research Paper | ScholarLens