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논문 기본 정보

자료유형
학위논문
저자정보

이성진, 이진숙, 장철용 (충남대학교, 忠南大學校 大學院)

지도교수
이진숙, 장철용
발행연도
2016
저작권
충남대학교 논문은 저작권에 의해 보호받습니다.

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이 논문의 연구 히스토리 (3)

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Improving the energy efficiency of low-income houses has become a national issue in order to establish a social welfare system and to eliminate the energy poverty of the low-income class of people. The purposes of this study are to analyze previous building energy calculation methods and simulation tools in literature, and then, based on the results of reviewing, to develop a simulation program which is conveniently applicable to calculation of the heating and cooling energy of the low-income houses. Also the applicability of the developed simulation program is evaluated by investigating the characteristics of the heating and cooling energy demands of a reference low-income house using our typical meteorological data.
The quasi steady-state calculation method was the most appropriate for calculating the heating and cooling energies of low-income houses, because it contained the dynamic effect as well as simplicity. This study developed Eco House ver.2 program based on the ISO 13790 for its application to calculating the energy efficiency of low-income houses. The Eco House ver.2 program was verified through comparing with Energy Plus (E+) program. The results of both calculations showed a good agreement for the heating energy demand, while there was a little difference for the cooling energy demand. The latter is likely attributed to different numerical simulation algorithms and different input parameters which are provided to the programs.
The application study of the Eco-House ver.2 calculated typical meteorological years using domestic weather data for the last 10 years, and then investigated the influence of the corresponding typical meteorological factors on the heating and cooling demands of a reference low-income house. As the results of the application study, dry bulb temperature was ranked in the order of Seoul <Daejeon <Busan <Jeju. It indicated that the temperature went higher in the lower-latitude regions. Irradiance and direct normal irradiance were listed in the order of Seoul <Jeju <Daejeon <Busan. Jeju had less Irradiance than Busan. It is supposed that Jeju had less irradiance by much clouds and rainy days due to island nature. The dry bulb temperature influenced more on the heating and cooling energy demand than the irradiance. The heating energy demand was concentrated between December and March(in the heating period), and on the other hand, the cooling energy demand is between July and September(in the cooling period). The regional heating energy demand was in the order of Seoul >Daejeon >Jeju >Busan, while the cooling energy demand was in Busan >Jeju >Daejeon >Seoul.

목차

제1장 서론 1
1.1 연구의 배경 및 목적 1
1.2 연구의 범위와 방법 2
제2장 이론적 배경 4
2.1 건물에너지 해석 방법 4
2.1.1 정적 해석법 4
2.1.2 동적 해석법 8
2.1.3 준-정상상태 해석법 9
2.2 건물에너지 성능 평가도구 10
2.2.1 Energy Plus(E+) 10
2.2.2 ECO2 12
2.2.3 Eco House 13
제3장 Eco House ver.2 프로그램 알고리즘 개발 15
3.1 ISO 13790 준-정상상태 해석법 15
3.2 Eco house ver.2 프로그램 알고리즘 18
3.2.1 냉·난방 에너지 계산 18
3.2.1.1 난방 에너지요구량 19
3.2.1.2 냉방 에너지요구량 20
3.2.1.3 관류열손실 22
3.2.1.4 환기열손실 23
3.2.1.5 내부열획득 25
3.2.1.6 일사에 의한 열획득 25
3.2.1.7 동적변수 26
3.2.2 급탕에너지요구량 계산 30
3.2.3 조명에너지요구량 계산 31
3.2.4 적용 및 분석범위 32
제4장 프로그램 검증 및 시뮬레이션 34
4.1 평가주택 선정 34
4.2 입력데이터 38
4.3 Energy Plus를 이용한 Eco House ver.2 검증 41
4.3.1 계산결과 41
4.3.2 Energy Plus와의 결과 비교 및 고찰 45
4.4 적용사례 : 국내 표준기상데이터를 이용한 저소득층 주택의 냉·난방 에너지요구량 특성 분석 48
4.4.1 개요 48
4.4.2 표준기상년도 산출모델 48
4.4.3 표준기상년도(TRY) 산출 방법 49
4.4.4 국내 기상데이터의 표준년도 산출 51
4.4.5 주요 기상인자 데이터의 지역별특성 분석 54
4.4.6 표준 기상데이터를 적용한 건물에너지 평가 63
제5장 결론 70
참 고 문 헌 72
ABSTRACT 75

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