• 제목/요약/키워드: Energy demand model

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통합수요관리 효과분석을 위한 한국형 Energy System Management 모형 개발에 관한 연구 (A study on Development of Korean - Energy System Management Model for Effect Analysis of Integrated Demand Management)

  • 김용하;조현미;김의경;유정희;김동근;우성민
    • 전기학회논문지
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    • 제60권6호
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    • pp.1103-1111
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    • 2011
  • This paper is developed to Energy Balance Flow show the flow of total energy resource be used nationally. The Energy Balance Flow is applicable of demand management factor through the analysis of foreign energy model of supply and demand and energy statistic data in the country. This study is based on and developed to Energy system management model is able to appraisal efficient of energy cost cutting, CO2 emission reduction and Energy saving at the national level calculated effect reached amount of primary energy to change of energy flow followed application of demand side management factor is able to appraisal quantitatively at the total energy to model of demand and supply.

투광형 박막 BIPV 창호 적용에 따른 냉난방 및 조명 부하 저감에 관한 연구 (A Study on Analysis for Energy Demand of the Heating, Cooling and Lighting in Office Building with Transparent Thin-film a-Si BIPV Window)

  • 윤종호;안영섭;박장우;김빛나
    • KIEAE Journal
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    • 제13권3호
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    • pp.91-96
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    • 2013
  • The purpose of this study was to analyze the annual energy demand including heating, cooling and lighting according to kind of windows with transparent thin-film a-Si Building Integrated Photovoltaic(a-Si BIPV) for office building. The analysis results of the annual energy demand indicated that the a-si BIPV window was reduced by 8.4% than the clear gazing window. The base model A was combinate with a-Si BIPV window area of 67% and clear window area of 33% among the total exterior area. The model B is to be applied with low-e clear glass instead of clear glass of the base model A. The model B was reduced to annual energy demand of 1% more than the model A. Therefore, By using a-si BIPV solar module, the cooling energy demand can be reduced by 53%(3.4MWh) and the heating energy demand can be increase by 58%(2.4MWh) than clear glazing window in office building. Also, Model C applied to the high efficient lighting device to the model B was reduced to annual energy demand of 14.4% more than the Model D applied to the high efficient lighting device to the model A. The Model E applied with daylight dimming control system to the Model C was reduced to annual energy demand of 5.9% more than Model C.

병원 건물의 에너지 부하모델 개발 (Development of Energy Demand Models for Hospitals)

  • 박화춘;정모
    • 설비공학논문집
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    • 제21권11호
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    • pp.636-642
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    • 2009
  • Energy consumption data are surveyed and measured to develop energy demand models for hospital buildings as part of a complete package. Daily consumption profiles for electricity, heating, cooling and hot water are surveyed for 14 carefully chosen hospitals to establish energy demand patterns for a time span of a year. Then the hourly demand patterns of the 4 loads are field-measured for different seasons and statistically analyzed to provide higher resolution models. Used in conjunction with energy demand models for other types of buildings, the high resolution of 8760 hour energy demand models for a hospital for a typical year will serve as building blocks for the comprehensive model that allows the estimation of the combined loads for arbitrary mixtures of buildings.

Energy Balance Flow 구축에 의한 에너지효율향상 효과분석 (Effect Analysis on Energy Efficiency Improvement for Establishing Energy Balance Flow)

  • 김용하;조현미;신형철;김형중;우성민;김영길
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2011년도 제42회 하계학술대회
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    • pp.679-680
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    • 2011
  • This paper is developed to Energy Balance Flow show the flow of total energy resource be used nationally. The Energy Balance Flow is applicable of demand management factor through the analysis of foreign energy model of supply and demand and energy statistic data in the country. This study is based on and developed to Energy system management model is able to appraisal efficient of energy cost cutting, CO2 emission reduction and Energy saving at the national level calculated effect reached amount of primary energy to change of energy flow followed application of demand side management factor is able to appraisal quantitatively at the total energy to model of demand and supply.

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Energy System Management 모형을 통한 통합 수요관리 효과분석에 관한 연구 (A Study on Effect Analysis of Integrated Demand Management According to Energy System Management Model)

  • 김용하;조현미;김영길;박화용;김형중;우성민
    • 전기학회논문지
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    • 제60권7호
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    • pp.1339-1346
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    • 2011
  • This paper is developed to demand management scenario of energy consumption efficiency improvement, electricity generation efficiency improvement, network efficiency improvement, change of distribution ratio, movement of energy source, change of heating system, put of CHP to quantitatively assess to impact on energy use of demand management at the national level. This scenario can be applied Energy System Management model was developed based on Energy Balance Flow. In addition, effect analysis through built demand management scenario was quantitatively evaluated integrated demand management effectiveness of energy cost saving, CO2 emission reduction and energy savings of national level by calculating to primary energy source usage change in terms of integration demand management effect more often than not a single energy source separated electricity, heat and gas.

머신러닝 기반 수소 충전소 에너지 수요 예측 모델 (Machine Learning-based hydrogen charging station energy demand prediction model)

  • 황민우;하예림;박상욱
    • 인터넷정보학회논문지
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    • 제24권2호
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    • pp.47-56
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    • 2023
  • 수소 에너지는 높은 에너지 효율로 열과 전기를 생산하면서도 온실가스와 미세먼지 등 유해물질 배출이 없는 친환경 에너지로서, 전 세계적으로 탄소중립으로의 전환을 위한 핵심으로 주목받고 있다. 특히 스마트 수소에너지는 경제적이고 지속 가능하며, 안전한 미래 스마트 수소에너지 서비스로써 수소 에너지의 기반 시설이 디지털로 통합되어 '데이터' 기반으로 안정적으로 운영되는 서비스를 의미한다. 본 논문에서는 데이터 기반 수소 충전소 수요예측 모델 구현을 위해 강원도 내 설치되어 있는 수소 충전소 3곳(춘천, 속초, 평창)을 선정, 수소 충전소의 수요공급 데이터를 확보하였고, 머신러닝 및 딥러닝 알고리즘 7개를 선정하여 총 27종 입력 데이터(기상데이터+수소 충전소 수요량)로 모델을 학습하였고, 평균 제곱근 오차(RMSE)로 모델을 평가하였다. 이를 통해 본 논문에서는 최적의 수소 에너지 수요공급을 위한 머신러닝 기반 수소 충전소 에너지 수요 예측 모델을 제안한다.

A neural network model to assess the hysteretic energy demand in steel moment resisting frames

  • Akbas, Bulent
    • Structural Engineering and Mechanics
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    • 제23권2호
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    • pp.177-193
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    • 2006
  • Determining the hysteretic energy demand and dissipation capacity and level of damage of the structure to a predefined earthquake ground motion is a highly non-linear problem and is one of the questions involved in predicting the structure's response for low-performance levels (life safe, near collapse, collapse) in performance-based earthquake resistant design. Neural Network (NN) analysis offers an alternative approach for investigation of non-linear relationships in engineering problems. The results of NN yield a more realistic and accurate prediction. A NN model can help the engineer to predict the seismic performance of the structure and to design the structural elements, even when there is not adequate information at the early stages of the design process. The principal aim of this study is to develop and test multi-layered feedforward NNs trained with the back-propagation algorithm to model the non-linear relationship between the structural and ground motion parameters and the hysteretic energy demand in steel moment resisting frames. The approach adapted in this study was shown to be capable of providing accurate estimates of hysteretic energy demand by using the six design parameters.

A new practical equivalent linear model for estimating seismic hysteretic energy demand of bilinear systems

  • Samimifar, Maryam;Massumi, Ali;Moghadam, Abdolreza S.
    • Structural Engineering and Mechanics
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    • 제70권3호
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    • pp.289-301
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    • 2019
  • Hysteretic energy is defined as energy dissipated through inelastic deformations during a ground motion by the system. It includes frequency content and duration of ground motion as two remarkable parameters, while these characteristics are not seen in displacement spectrum. Since maximum displacement individually cannot be the appropriate criterion for damage assessment, hysteretic energy has been evaluated in this research as a more comprehensive seismic demand parameter. An innovative methodology has been proposed to establish a new equivalent linear model to estimate hysteretic energy spectrum for bilinear SDOF models under two different sets of earthquake excitations. Error minimization has been defined in the space of equivalent linearization concept, which resulted in equivalent damping and equivalent period as representative parameters of the linear model. Nonlinear regression analysis was carried out for predicting these equivalent parameter as a function of ductility. The results also indicate differences between seismic demand characteristics of far-field and near-field ground motions, which are not identified by most of previous equations presented for predicting seismic energy. The main advantage of the proposed model is its independency on parameters related to earthquake and response characteristics, which has led to more efficiency as well as simplicity. The capability of providing a practical energy based seismic performance evaluation is another outstanding feature of the proposed model.

기후변화와 사회·경제적 요소를 고려한 가정 부문 냉난방 에너지 사용량 변화 예측 (Prediction of Heating and Cooling Energy Consumption in Residential Sector Considering Climate Change and Socio-Economic)

  • 이미진;이동근;박찬;박진한;정태용;김상균;홍성철
    • 환경영향평가
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    • 제24권5호
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    • pp.487-498
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    • 2015
  • 기온상승과 인구 및 GDP 증가의 영향으로 인해 에너지 문제가 발생하고 있다. 이러한 문제에 대응하기 위해 에너지 수요에 대한 예측이 필요하다. 따라서 본 연구는 에너지 수요관리, 특히 전력부하를 유발하는 냉난방 에너지 수요 관리에 도움이 되고자 가정 부문 냉난방 에너지의 미래 사용량을 예측하고자 한다. 에너지 사용량을 산정하는데 있어 서비스 수요의 산출이 필요하다. 따라서 서비스 수요 산정식을 이용하여 이를 먼저 도출하고, AIM/end-use 모델을 이용하여 에너지 사용량을 산정하였다. 산정 결과 냉난방 서비스 수요는 2010년에 비해 2050년에 모두 증가하는 추세를 보였다. 하지만 에너지 사용량에서 난방은 감소하고, 냉방은 증가하는 것으로 예측되었다.

기상 예보 데이터와 일사 예측 모델식을 활용한 실시간 에너지 수요예측 (Real-time Energy Demand Prediction Method Using Weather Forecasting Data and Solar Model)

  • 곽영훈;천세환;장철용;허정호
    • 설비공학논문집
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    • 제25권6호
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    • pp.310-316
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    • 2013
  • This study was designed to investigate a method for short-term, real-time energy demand prediction, to cope with changing loads for the effective operation and management of buildings. Through a case study, a novel methodology for real-time energy demand prediction with the use of weather forecasting data was suggested. To perform the input and output operations of weather data, and to calculate solar radiation and EnergyPlus, the BCVTB (Building Control Virtual Test Bed) was designed. Through the BCVTB, energy demand prediction for the next 24 hours was carried out, based on 4 real-time weather data and 2 solar radiation calculations. The weather parameters used in a model equation to calculate solar radiation were sourced from the weather data of the KMA (Korea Meteorological Administration). Depending on the local weather forecast data, the results showed their corresponding predicted values. Thus, this methodology was successfully applicable to anywhere that local weather forecast data is available.