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건물의 실측 에너지 데이터를 통한 건물 에너지 소비 패턴 분류에 관한 연구
우혜지(Woo, Hei-Jee),최기원(Choi, Ki-Won),김현수(Kim, Hyeon Soo),어진선(Auh, Jin Sun),조수연(Cho, Soo Youn),백주미(Baek, Jumi),김기석(Kim, Gi-Seok),이승복(Leigh, Seung-Bok) 대한건축학회 2016 대한건축학회논문집 Vol.32 No.5
The pattern of energy consumption in a building varies based on its characteristic features and the behavior of the occupants; therefore, it is difficult to classify buildings in terms of energy consumption. This study used only outdoor temperature and energy consumption as a parameter to analyze the energy consumption by a building, and thus the approach is different from the conventional methods that use complex computer simulations, data on energy consumptions related to heating cooling, and energy audits etc. First, raw data on the operational schedules of the buildings and internal-external dependency factor are developed as the primary analytical data. The preferred analytical data were categorized into four categories: internal-external factors, energy consumption, operational condition of the building, and energy consumption by outdoor temperature. A matrix that can be used as a relative indicator of a building’s energy consumption in relation to its characteristics was also developed in this work. Using this energy pattern matrix, the obtained data could be used for retrofitting buildings, and a classification scheme based on the energy consumption pattern of buildings can be also prepared.
Change Point Model을 활용한 대학건물의 에너지 소비패턴 분류 및 에너지 영향인자에 따른 분석
윤진하(Yoon, Jin-Ha),이병희(Lee, Byung-Hee),여명석(Yeo, Myung-Souk),김광우(Kim, Kwang-Woo) 대한건축학회 2017 大韓建築學會論文集 : 構造系 Vol.33 No.11
As part of reducing greenhouse gas emissions, energy saving is required for buildings that consume a large amount of energy, including university buildings. However, because university buildings consist of several buildings having varying purposes, it is difficult to manage building energy for overall energy saving at the campus level. Therefore, this paper presents an intuitive presentation of building energy management direction by investigating the actual energy consumption patterns of university buildings at the campus level. Energy consumption data used are expressed using the Change Point Model, and energy consumption parameters such as energy use intensity, base energy use ratio, cooling sensitivity, and heating sensitivity are derived. Further, the energy consumption of buildings was classified into 16 patterns by using the energy consumption parameters. Each pattern was analyzed according to the building energy impact factors and the building energy management direction by applying the science and engineering buildings.
황광일(Kwang-il Hwang) 한국항해항만학회 2012 한국항해항만학회지 Vol.36 No.6
해양에너지를 비롯한 신재생에너지를 이용한 분산형 발전시스템 설계의 기초자료로 활용하기 위해 본 연구에서는 도서 주민의 전력소비량을 실측 분석하고 시기별 전력소비 패턴을 개발하였다. 실측조사는 남해안에 위치한 곤리도의 5가구를 대상으로 2010년 10월부터 2012년 2월까지 수행되었다. 월평균 전력소비량은 가구에 따라 12월 혹은 1월에 최대값이 발생하였다. 가구별 월간 전력소비량은 H가구가 J가구보다 2~3배 많았지만 가구별 1인당 월평균 전력소비량은 J가구가 H가구보다 10~30% 가량 많은 것으로 조사되었다. 시각별 전력소비패턴을 개발한 결과 여름철에는 20시에서 자정 사이에 최대 전력소비가 발생하고, 겨울철은 여름철에 비하여 하루 동안의 전력소비 변화는 완만하지만 18시 이후 자정까지의 시간대에 전력소비가 증가하는 경향을 보였다. 가구별 주중과 주말의 전력소비 패턴은 매우 유사한 것으로 나타났다. To serve basic data for the design of capacity and management of Distributed(or On-site) Power Generation System using renewable energies, this study measured the electric power consumption(hereafter abbreviated as EPC) of 5 families of fishing village located at island in southeastern area of Korea. The results are as following. The maximum monthly average EPC occurred in December or January. Although the total monthly EPC of H family is 2~3 times more than J family, individual monthly EPC of J family is 10~30 % more than H family. Hourly EPC pattern shows that the maximum EPC occurred between 20~24 o’clock in summer season, but it occurred between 18~24 o’clock in winter season. Compared to summer, the height of fluctuation through a day is small. And the EPC patterns of weekdays and weekend estimated as very similar.
공동주택관리정보시스템과 원격검침시스템 데이터를 이용한 지역난방방식 공동주택에서의 에너지원별 소비패턴 분석
엄지영(Ji-Young Eum),김원욱(Won-Uk Kim),김용기(Yong-Ki Kim) 한국퍼실리티매니지먼트학회 2018 한국퍼실리티매니지먼트학회지 Vol.13 No.1
The world is currently facing energy and environmental problems. Building sector is accounting for 22 % of the total energy use in Korea. Also, apartment houses account for 45 % of the total energy use in residential buildings. Five utilities that is causing energy consumption in the residential building are electricity, heating, hot water, water, and city gas. In this study, the annual and daily consumption patterns of five utilities were analyzed using the management cost data of K-apt(apartment housing management information system) and AMR(Automatic Meter Reading) data of a A-apartment in Suwon. According to K-apt’s data, the average annual utility fee of 60 apartment complexes that use district heating system is the order of electricity bill > heating bill > hot water bill > water bill, except for city gas for cooking. As a result of analyzing the electricity consumption of a A-apartment located in Suwon city, the base load which is always consumed regardless of whether the resident is active or not is more than 65% of total daily electricity consumption. Therefore, it is very necessary to reduce the base load in order to reduce electricity consumption in apartment houses.
서울지역 아파트 세대별 전력소비패턴 및 발코니 태양광 설비의 발전량 분석
엄지영,김용기 한국태양에너지학회 2023 한국태양에너지학회 논문집 Vol.43 No.4
For apartments with 30 or more households, the government is implementing a zero-energybuilding mandate from 2023 in the public sector and 2024 in the private sector. Many localgovernments are promoting mini-photovoltaic (PV) system supply support projects that can beinstalled on apartment balconies. An apartment mini-PV system is a concept that installs a PVmodule on a balcony and directly supplies the power from the PV to the household outletthrough a plug. In this study, we analyzed real-time power consumption patterns forapproximately one year for apartments in the Seoul area and analyzed the amount of powergenerated by mini-PV systems installed on balconies. The power consumption pattern byhousehold and the amount of PV power on the balcony showed significant differences owing tothe influence of life patterns of the residents, PV installation capacity, and installationenvironment. However, power consumption was the highest during the evening and summer,and balcony PV power was highest during spring and autumn. In addition, a large amount ofsurplus power is generated during the PV generation. The balcony photovoltaic systemcontributes to a household electricity energy self-sufficiency rate of 26%, on average, for fourhouseholds by electricity production.