• Title/Summary/Keyword: Building energy consumption characteristics

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Analysis of Effects of Building Energy Consumption Characteristics on the Optimization Ratio for New and Renewable Energy Systems (건물에너지사용특성이 신재생에너지시스템 최적화 비율에 미치는 영향분석)

  • Lee, Yong-Ho;Hong, Jun-Ho;Kim, Yong-Kyoung;Cho, Young-Hum;Hwang, Jung-Ha
    • Journal of the Korean Solar Energy Society
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    • v.34 no.5
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    • pp.117-126
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    • 2014
  • This study developed a KRESS program designed to find the optimization ratio for new and renewable energy systems and analyze the effects of building energy consumption characteristics on the ratio. In spite of clear differences in predicted energy consumption and energy consumption by the loads among 18 facilities, the current formula for obligatory supply ratios applies a correction coefficient according to the building purposes based on energy consumption per each unit area in medical facilities and thus reflects no energy consumption characteristics according to the building purposes. The optimization ratio for new and renewable energy systems was the same for all facilities when the correction coefficients by the building purposes and new and renewable energy sources were all applied. When the correction coefficients were not applied, however, the optimization ratio varied according to building energy consumption characteristics. The findings raise a need to test the correction coefficients in order to select new and renewable energy systems that take into account energy consumption characteristics by the building purposes and loads and reflect economy, environmental performance, and technology.

Characteristics of Energy Consumption in an Office Building located in Seoul (사무소건물의 용도 및 측정기간에 따른 에너지 소비 특성)

  • Park Byung-Yoon;Chung Kwang-Seop
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.17 no.1
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    • pp.82-87
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    • 2005
  • The purpose of this study is to suggest the characteristics and actual state of energy consumption by the analysis of energy consumption data in an office building. This study examines and analyzes daily and monthly energy consumption of an office building located in Seoul, Korea regarding type of load and business classification within a building. The results are as follows. 1) Energy consumption of office building for each type of load show similar consumption patterns, regardless of seasons such as cooling period and heating period. 2) Out of all annual energy consumption, consumption for lighting took about $43\;\%,$ general electric Power about $23\;\%,$ emergency power $25\;\%,$ computer center $5\;\%$ and cooling power $4\;\%,$ showing that the consumption for lighting was highest, and the percentage of energy consumption for cooling power for operation of cooling facilities took the lowest percentage. 3) Annual gas consumption used for heating and hot water supply were $38,\;36\;\%$ for officetel and office respectively, and $26\;\%$ for arcade. 4) Electricity consumptions used for cooling power for each use of building, office and officetel recorded in July and August of cooling seasons. Even though it shows different patterns for each month, energy consumption showed unique pattern throughout the cooling seasons.

An Analysis of Energy Consumption Types Considering Life Patterns of Single-person Households (1인 가구 거주자의 생활패턴이 고려된 에너지소요량 유형 분석)

  • Lee, Seunghui;Jung, Sungwon;Lim, Ki-Taek
    • Journal of the Architectural Institute of Korea Planning & Design
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    • v.35 no.1
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    • pp.37-46
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    • 2019
  • The energy of the building is influenced by the user 's activity due to the population, society, and economic characteristics of the building user. In order to obtain accurate energy information, the difference in the amount of energy consumption by the activities and characteristics of building users should be identified. The purpose of the study is to identify the difference in the amount of energy consumption by the user's activities in the same building, and to analyse the relationship between user's activities and demographic, social and economic characteristics. For research, energy simulation is performed based on actual user activity schedule. The results of the simulation were clustered by using K-Means clustering, a machine learning technique. As a result, four types of users were derived based on the amount of energy consumption. The more energy used in a cluster, the lower the user's income level and older. The longer a user's indoor activity times, the higher the energy use, and these activities relate to the user's characteristics. There is more than twice the difference between the group that uses the least energy consumption and the group that uses the most energy consumption.

A Study on the Perfomance Analysis of Low Energy Cooling Systems in Office building (사무소건물의 에너지절약형 냉방시스템 성능분석에 관한 연구)

  • Park, Chang-Bong;Rhee, Eon-Gu
    • Journal of the Korean Solar Energy Society
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    • v.30 no.6
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    • pp.89-94
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    • 2010
  • A large portion of the energy cost of a building is cooling and heating to maintain a comfortable indoor environment. Air conditioning is now one of the important parts in the building design, as increase in energy consumption and pollutant emission in energy conversion process. In this study, elements that affects the energy consumption of model building are identified and the perfomance analysis of the alternative a Low Energy Cooling Systems considering characteristics of model building and energy saving performance is analyzed. In this study, elements that affect the energy consumption of office building are identified and energy saving performance of the alternative air conditioning system is analyzed. As a result, applied to earn and suggest basic data for energy saving measures. In this study, EnergyPlus simulation program was used to evaluate the energy load when alternative Low Energy Cooling Systems are applied to the model building. The reliability of simulation program is verified by comparing actual energy load from operation data of building management office and predicted energy load using simulation program. For Low Energy Cooling System application which considers the purpose and characteristics of the building, reasonable and energy-saving air conditioning method obtained by analyzing energy consumption elements for each expected air conditioning methods is used to deduct result of this study.

A study on the energy consumption and management of an U-based city considering the characteristics of building energy in a city - Focused on Daegu·Gyeongbuk Area - (도시 내 건축물에너지 소비특성을 고려한 U-기반 도시에너지 수요 및 관리방안 연구 - 대구·경북을 중심으로 -)

  • Lee, Kang-Guk;Kim, Tae-Woo;Hyun, Taek-Soo;Hong, Won-Hwa
    • KIEAE Journal
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    • v.10 no.6
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    • pp.21-26
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    • 2010
  • This study is to suggest basic data for the policy on the energy demand and management of an U-based city compliant with characteristics of regions and districts in future city by conducting research on the energy consumption and management of an U-based city, considering city energy demand characteristics focused on the center district of Daegu metropolitan city. U-based city energy consumption and management solution is considered to be effective in establishing the guideline of environment-friendly urban architecture planning as well as the assessment of energy consumption characteristics in a city.

The Relationship between Energy Consumption and Factors Affecting Heating and Cooling

  • Park, Kwon Sook;Kim, Seiyong
    • Architectural research
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    • v.19 no.1
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    • pp.7-11
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    • 2017
  • Energy consumption in university building has steadily increased over the last decade, and a strong upward trend in recent years. This study was undertaken to analyze the relationship between energy consumption and their affecting factors, six academic buildings were considered. The factors limited to heating and cooling, which is the main end use (nearly 60 per cent of total energy consumption in university buildings), encompassing system and operating schedules (user activity) and area use. To understand how to building is used, operated and managed, walk-through assessment was conducted as well as interview with university staff. The results show that the energy consumption of the humanities building was somewhat smaller than the consumption of the science and engineering building, and its range was from $31.26kgoe/m^2$ to $23.52kgoe/m^2$, depending on heating and cooling system and area use. And the energy consumption of the science and engineering building was related to operating schedules (user activity) as well as laboratory equipment characteristics. More analysis on a larger number of buildings is required in the future, including building form and material performance level to generalize the significant factors influencing building energy consumption.

Case Study for Energy Conservation Measures of Hospital Buildings Using the Analysis of Energy Consumption Structure (의료시설 에너지절약 운영방법 도출을 위한 사례분석을 통한 에너지 영향요소 분석)

  • Lee, Sangmoon;Cho, Jinkyun
    • Journal of the Korean Solar Energy Society
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    • v.39 no.2
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    • pp.57-69
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    • 2019
  • Because the hospital building operates 24 hours a day, 365 days a year for treatment and restoration of patients, it has a different pattern of energy use than that of ordinary buildings. Hospitals contribute to energy consumption and have a negative environmental impact. This study aims to find how meaningful energy performance, reflecting good energy management and ECMs, can be operated for hospital buildings, a category encompassing complex buildings with different systems and large differences between them. In this study, we proposed the energy diagnosis & evaluation method and energy management process to verify energy saving through operation data based on system & facility characteristics, operation pattern and energy consumption characteristics of hospital building. Energy consumption structures were surveyed throughout 4 reference hospital in Seoul, Korea. Findings confirm that different hospital departments have hugely different energy-demand profiles. Energy efficiency and energy saving potentials are presented. The energy performance analysis can be applied to a wide range of problems in energy-system operation.

Applying Neural Networks to Model Monthly Energy Consumption of Commercial Buildings in Singapore(ICCAS2004)

  • Dong, Bing;Lee, Siew Eang;Sapar, Majid Hajid;Sun, Han Song
    • 제어로봇시스템학회:학술대회논문집
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    • 2004.08a
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    • pp.1330-1333
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    • 2004
  • The methodology for modeling building energy consumption is well established for energy saving calculation in the temperate zone both for performance-based energy retrofitting contracts and measurement and verification (M&V) projects. Mostly, statistical regression models based on utility bills and outdoor dry-bulb temperature have been applied to baseline monthly and annual whole building energy use. This paper presents the application of neural networks (NN) to model landlord energy consumption of commercial buildings in Singapore. Firstly, a brief background information on NN and its application on the building energy research is provided. Secondly, five commercial buildings with various characteristics were selected for case studies. Monthly mean outdoor dry-bulb temperature ($T_0$), Relative Humidity (RH) and Global Solar Radiation (GSR) are used as network inputs and the landlord monthly energy consumption of the same period is the output. Up to three years monthly data are taken as training data. A forecast has been made for another year for all the five buildings. The performance of the NN analysis was evaluated using coefficient of variance (CV). The results show that NNs is powerful at predicting annual landlord energy consumption with high accuracy.

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The Analysis of Energy Consumption Characteristics of the Apartment (공동주택 에너지 소비 경향 분석에 관한 연구)

  • Lee, Hyun-Jung;Park, Sun-Hyo;Bae, Sang-Hwan;Lee, Byung-Seok;Kim, Yang-Sub
    • 한국태양에너지학회:학술대회논문집
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    • 2012.03a
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    • pp.305-310
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    • 2012
  • In 2009, The Ministry of Land, Transport and Maritime Affairs, Korea opens apartment maintenance fee to public in "Apartment Management Info System". The high energy consumption component of apartment, which is hot water, water, electricity and heating, is released to public on this system. Through this system, apartment energy consumption and greenhouse gas emissions data can be compiled and expected to be accurately analyzed. Energy consumption and greenhouse gas emissions statistics of the apartment are collected being made to reduce energy and gas emissions. However, The accurate survey of energy consumption trends have not been accomplished. The energy consumption and greenhouse gas emissions survey in Apartment should be made first in order to reduce energy consumption. and then the correlation factors analysis which is affecting energy consumption is required. The purpose of this study is to analyze energy consumption characteristics of apartment in Bundann-gu, Seongnam, Korea in monthly, unit area and building built year basis. And then the research can be used as the basis of policy to Reduce energy consumption and greenhouse gas emissions.

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A Study on the Energy Consumption Characteristics for Use and Operation Period in Office Buildings (업무용 건물의 용도 및 운전 기간별 에너지 소비 특성 연구)

  • Park, Byung Hun;Kim, Si Heon
    • Korean Journal of Air-Conditioning and Refrigeration Engineering
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    • v.29 no.11
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    • pp.605-611
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    • 2017
  • The purpose of this study is to calculate the energy consumption rate based on data regarding energy use in office buildings, and to confirm the general characteristics of energy consumption. The energy consumption rate of the building is calculated by dividing the energy consumption by the floor area. The energy consumption rate of small-sized office buildings was calculated as $101.48{\sim}201.55kWh/m^2{\cdot}year$ and in the case of medium-sized buildings, the range was $92.77{\sim}177.89kWh/m^2{\cdot}year$. In the case of small buildings, it was found that the energy consumption was $73.24kWh/m^2{\cdot}year$ in electronic device, $34.31kWh/m^2{\cdot}year$ in hot water supply, and $18.37kWh/m^2{\cdot}year$ in heating. In the case of medium-sized buildings, electronic devices was $73.08kWh/m^2{\cdot}year$, lighting was $18.35kWh/m^2{\cdot}year$ and heating, $15.37kWh/m^2{\cdot}year$. In all of the study buildings, the peak heating energy use was observed from 8:00 a.m. to 10:00 a.m during the winter, and the peak power management was required. Energy use at and around the midnight hour is confirmed to be 40~60% of weekly working hours, so it is necessary to manage power use at night time as well as during the day. In order to improve the accuracy of future studies, it is necessary to make efforts to secure the data with standardized energy measuring units for the various type of buildings.