This study, the urban energy used office building green roof type composition of the target by analyze building energy reductions. Green roof is total 6 types(type A~F) were selected, EnergyPlus the energy simulation programs were used. Top floor of green roof types evaluation, the reduction of the cooling peak load type E(1.26%), type D(1.30%), type C(1.37%), type B(1.45%), type F(1.49%), and heating peak load is type D(1.32%), type E(1.40%), type C(1.47%), type F(1.69%), type B(2.13%) order. Annual cooling load of heating load is reduced more than about 1% effect. The heating load reduction ratio for a maximum of 9% respectively. Cooling peak load of the building energy performance evaluation of type F ＞type B ＞type C ＞type D ＞type E in the order and in the case of peak loads heating type B ＞type F ＞type D ＞type E ＞type C order. Annual total energy use reduction of 1.07 to 1.22% and earn, type B in the best good. In primary energy use reductions in the presence of a green roof were in the 4249~4876 kWh/yr. Annual CO2 emissions reductions of unapplied type A were analyzed on average 469.78 kg.

To estimate the benefit of high-resolution meteorological data for building energy estimation, a building energy analysis has been conducted over Busan metropolitan areas. The heating and cooling load has been calculated at seven observational sites by using temperature, wind and relative humidity data provided by WRF model combined with the inner building data produced by American Society of Heating Refrigeration and Air-conditioning Engineers (ASHRAE). The building energy shows differences 2-3% in winter and 10-30% in summer depending on locations. This result implicates that high spatiotemporal resolution of meteorological model data is significantly important for building energy analysis.

EnergyPlus is a whole building energy simulation program that engineers, architects, and researchers use to model energy and water use in buildings. Modeling the performance of a building with EnergyPlus enables building professionals to optimize the building design to use less energy and water. This program provides energy analysis of building and needs weather data for simulation. Weather data is available for over 2,000 locations in a file format that can be read by EnergyPlus. However, only five locations are avaliable in Korea. This study intends to use AWS data for having high spatial resolution to simulate building energy. The result of this study shows the possibility of using AWS data for energy simulation of building.

해양에너지를 지역냉난방설비의 에너지원으로 활용하기 위한 방법론적 관점에서 출발한 본 연구의 목적은 부산시의 지리정보를 이용하여 500m×500m 메시를 개발하고, 메시 특성에 따른 유형별 분포도를 작성하는 것이다. 연구성과를 정리하면 다음과 같다. 부산광역시의 총 16개 단위행정구역 중 연제구, 중구, 해운대구를 제외한 13개 구군(區郡), 108개 동(洞)별 유효 건축정보와 수치지도를 이용하여 500m×500m 메시를 개발하였다. 총 3,289개 메시가 유효한 건물바닥면적을 갖고 있으며, 그 중 용적률 50% 이상인 메시는 325개(9.9%), 100% 이상인 메시는 59개(1.8%), 200% 이상인 메시는 30개(0.9%), 300% 이상인 메시는 25개(0.8%)로 나타났다. 용적률 50% 이상인 325개 메시를 주성분분석과 클러스터분석에 의해 5개 유형으로 분류하였고 이를 500m×500m 메시 맵 위에 분포도를 작성한 결과, 상업시설 중심의 1유형은 수영구 광안동, 주거시설 중심의 4, 5유형은 남구 용호동 등이 대표 지역으로 나타났으며, 부산의 대표 유형으로써 주거중심의 주상복합 특성을 갖는 3유형은 남구, 동래구, 북구, 사상구 등 부산 전역에 고르게 분포하는 것으로 나타났다.

Buildings nowadays are increasingly expected to need higher and more economic performance requirements. Energy consumption in buildings accounts for over 30% of total energy use. The Building Energy Management System (BEMS) and renewable energy (RE) technologies are considered as a potential measure to improve energy efficiency and reduce use of grid-power. It is, however, a challenge to utilise the intermittent energy supply of RE in building energy systems. This paper presents an experimental study on a RE-embedded BEMS. A control algorithm for the RE-embedded BEMS was designed to maximise the utilisation of RE and eventually to reduce electrical utility bill. The proposed system is tested at a laboratorial chamber with an air conditioner, fan and heater. The contribution of RE in building energy system is discussed to this end.