• 제목/요약/키워드: energy demand

검색결과 2,400건 처리시간 0.026초

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.

Power Sharing and Cost Optimization of Hybrid Renewable Energy System for Academic Research Building

  • Singh, Anand;Baredar, Prashant
    • Journal of Electrical Engineering and Technology
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    • 제12권4호
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    • pp.1511-1518
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    • 2017
  • Renewable energy hybrid systems look into the process of choosing the finest arrangement of components and their sizing with suitable operation approach to deliver effective, consistent and cost effective energy source. This paper presents hybrid renewable energy system (HRES) solar photovoltaic, downdraft biomass gasifier, and fuel cell based generation system. HRES electrical power to supply the electrical load demand of academic research building sited in $23^{\circ}12^{\prime}N$ latitude and $77^{\circ}24^{\prime}E$ longitude, India. Fuzzy logic programming discover the most effective capital and replacement value on components of HRES. The cause regarding fuzzy logic rule usage on HOMER pro (Hybrid optimization model for multiple energy resources) software program finds the optimum performance of HRES. HRES is designed as well as simulated to average energy demand 56.52 kWh/day with a peak energy demand 4.4 kW. The results shows the fuel cell and battery bank are the most significant modules of the HRES to meet load demand at late night and early morning hours. The total power generation of HRES is 23,794 kWh/year to the supply of the load demand is 20,631 kWh/year with 0% capacity shortage.

Earthquake effects on the energy demand of tall reinforced concrete walls with buckling-restrained brace outriggers

  • Beiraghi, Hamid
    • Structural Engineering and Mechanics
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    • 제63권4호
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    • pp.521-536
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    • 2017
  • Reinforced concrete core-wall structures with buckling-restrained brace outriggers are interesting systems which have the ability to absorb and dissipate energy during strong earthquakes. Outriggers can change the energy demand in a tall building. In this paper, the energy demand was studied by using the nonlinear time history analysis for the mentioned systems. First, the structures were designed according to the prescriptive codes. In the dynamic analysis, three approaches for the core-wall were investigated: single plastic hinge (SPH), three plastic hinge (TPH) and extended plastic hinge (EPH). For SPH approach, only one plastic hinge is allowed at the core-wall base. For TPH approach, three plastic hinges are allowed, one at the base and two others at the upper levels. For EPH approach, the plasticity can extend anywhere in the wall. The kinetic, elastic strain, inelastic and damping energy demand subjected to forward directivity near-fault and ordinary far-fault earthquakes were studied. In SPH approach for all near-fault and far-fault events, on average, more than 65 percent of inelastic energy is absorbed by buckling-restrained braces in outrigger. While in TPH and EPH approaches, outrigger contribution to inelastic energy demand is reduced. The contribution of outrigger to inelastic energy absorption for the TPH and EPH approaches does not differ significantly. The values are approximately 25 and 30 percent, respectively.

스마트 그리드 환경에서 가전기기의 에너지 저감을 위한 SEP 2.0 기반의 자동수요반응 시스템 개발 (The Development of the Automatic Demand Response Systems Based on SEP 2.0 for the Appliances's Energy Reduction on Smart Grid Environments)

  • 정진욱;김수홍;진교홍
    • 한국정보통신학회논문지
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    • 제20권9호
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    • pp.1799-1807
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    • 2016
  • 본 논문에서는 기존의 가입자가 직접 전력량을 조절하는 수동수요반응과는 달리 정해진 시간에 자동적으로 전력량 소모를 줄이는 자동수요반응 시스템을 제안하였다. 제안된 시스템은 SEP 2.0을 기반으로 동작하며 수요반응 관리 프로그램과 수요반응 서버, 수요반응 클라이언트로 구성된다. 수요반응 관리 프로그램은 가입자에게 전력사용현황을 알려주고 관리자에게는 수요반응 이벤트를 생성 및 취소할 수 있게 한다. 수요반응 서버는 수요반응 관리 프로그램에서 수신한 수요반응 이벤트를 SEP 2.0을 통해 수요반응 클라이언트로 전송하고 수요반응 클라이언트가 주기적으로 전송하는 미터링 데이터를 데이터베이스에 저장한다. 그리고 수요반응 클라이언트는 수신한 수요반응 이벤트에서 수요반응 이벤트 시작시간과 지속시간, 감소레벨을 추출한 뒤, 특정 기간 동안 전력소모를 감소시킨다.

Planning ESS Managemt Pattern Algorithm for Saving Energy Through Predicting the Amount of Photovoltaic Generation

  • Shin, Seung-Uk;Park, Jeong-Min;Moon, Eun-A
    • 통합자연과학논문집
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    • 제12권1호
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    • pp.20-23
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    • 2019
  • Demand response is usually operated through using the power rates and incentives. Demand management based on power charges is the most rational and efficient demand management method, and such methods include rolling base charges with peak time, sliding scaling charges depending on time, sliding scaling charges depending on seasons, and nighttime power charges. Search for other methods to stimulate resources on demand by actively deriving the demand reaction of loads to increase the energy efficiency of loads. In this paper, ESS algorithm for saving energy based on predicting the amount of solar power generation that can be used for buildings with small loads not under electrical grid.

The Consumer Rationality Assumption in Incentive Based Demand Response Program via Reduction Bidding

  • Babar, Muhammad;Imthias Ahamed, T.P.;Alammar, Essam A.
    • Journal of Electrical Engineering and Technology
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    • 제10권1호
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    • pp.64-74
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    • 2015
  • Because of the burgeoning demand of the energy, the countries are finding sustainable solutions for these emerging challenges. Demand Side Management is playing a significant role in managing the demand with an aim to support the electrical grid during the peak hours. However, advancement in controls and communication technologies, the aggregators are appearing as a third party entity in implementing demand response program. In this paper, a detailed mathematical framework is discussed in which the aggregator acts as an energy service provider between the utility and the consumers, and facilitate the consumers to actively participate in demand side management by introducing the new concept of demand reduction bidding (DRB) under constrained direct load control. Paper also presented an algorithm for the proposed framework and demonstrated the efficacy of the algorithm by considering few case studies and concluded with simulation results and discussions.

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.

Provision of Two-area Automatic Generation Control by Demand-side Electric Vehicle Battery Swapping Stations

  • Xie, Pingping;Shi, Dongyuan;Li, Yinhong
    • Journal of Electrical Engineering and Technology
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    • 제11권2호
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    • pp.300-308
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    • 2016
  • Application of demand-side resources to automatic generation control (AGC) has a great significance for improving the dynamic control performance of power system frequency regulation. This paper investigates the possibility of providing regulation services by demand-side energy storage in electric vehicle battery swapping stations (BSS). An interaction framework, namely station-to-grid (S2G), is presented to integrate BSS energy storage into power grid for giving benefits to frequency regulation. The BSS can be regarded as a lumped battery energy storage station through S2G framework. A supplementary AGC method using demand-side BSS energy storage is developed considering the vehicle user demand of battery swapping. The effects to the AGC performance are evaluated through simulations by using a two-area interconnected power grid model with step and random load disturbance. The results show that the demand-side BSS can significantly suppress the frequency deviation and tie-line power fluctuations.

도시화율 및 산업 구성 차이에 따른 딥러닝 기반 전력 수요 변동 예측 및 전력망 운영 (Deep Learning Based Electricity Demand Prediction and Power Grid Operation according to Urbanization Rate and Industrial Differences)

  • 김가영;이상훈
    • 한국수소및신에너지학회논문집
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    • 제33권5호
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    • pp.591-597
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    • 2022
  • Recently, technologies for efficient power grid operation have become important due to climate change. For this reason, predicting power demand using deep learning is being considered, and it is necessary to understand the influence of characteristics of each region, industrial structure, and climate. This study analyzed the power demand of New Jersey in US, with a high urbanization rate and a large service industry, and West Virginia in US, a low urbanization rate and a large coal, energy, and chemical industries. Using recurrent neural network algorithm, the power demand from January 2020 to August 2022 was learned, and the daily and weekly power demand was predicted. In addition, the power grid operation based on the power demand forecast was discussed. Unlike previous studies that have focused on the deep learning algorithm itself, this study analyzes the regional power demand characteristics and deep learning algorithm application, and power grid operation strategy.

수요탄력성 추정을 통한 2차 에너지 세제개편의 성과평가 (Estimation of the Elasticity of Energy Demand and Performance of the Second Energy Tax Reform in Korea)

  • 강만옥;이상용;조장율
    • 자원ㆍ환경경제연구
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    • 제17권3호
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    • pp.1-29
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    • 2008
  • 본 연구는 자기회귀시차분포(ARDL)모형을 이용하여 우리나라 수송용 에너지(휘발유, 경유, LPG부탄)의 수요탄력성 추정을 통해 1차 에너지 세제개편 대비 2차 에너지 세제개편에 따른 수송용 에너지의 상대가격 변화가 에너지 수요량 및 환경오염물질(대기오염물질 및 이산화탄소) 배출량에 미치는 영향을 실증적으로 분석하여 2차 에너지 세제개편이 원래의 정책목표를 달성하고 있는가를 검증하고자 하였다. 분석결과, 2007년 이후 가격이 동일할 경우 경유 수요량은 연간 382만 배럴이 감소하고, LPG부탄 수요량은 연간 20만 배럴이 증가하는 것으로 나타났다. 2차 에너지 세제개편으로 인한 수송부문의 오염물질 배출저감량은 1차 에너지 세제개편 대비 LPG부탄의 경우가격 인하로 인해 연간 398톤 정도 증가하나 경유의 경우 연간 27,744톤이 저감되어 총저감량은 연간 27,346톤으로 추정된다. 또한 이산화탄소 저감량은 약 96만 톤으로 추정되어 이산화탄소 배출량 저감에도 상당부분 기여하는 것으로 나타났다. 따라서, 2차 에너지 세제개편은 에너지 사용량 감소 및 환경개선에도 기여하는 것으로 나타나 원래의 정책 목표를 어느 정도 달성하고 있는 것으로 평가된다.

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