• 설비공학논문집
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• 제16권6호
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• pp.608-613
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• 2004

Artificial lighting accounts for a significant portion of the energy use in office buildings. Therefore, daylighting is considered one of the fundamental design features of energy-efficient buildings. However, complex daylighting simulation tools are not suitable for most designers to help in the decision-making process. This paper provides the results of a simulation analysis to determine the potential energy savings of daylighting effects reducing electrical energy consumption for office building. A whole building simulation tool is used to determine the effects of daylighting on lighting electricity use as well as total electricity use for typical office buildings. It was determined that daylighting does not provide significant additional lighting energy savings when glass transmittance is increased over 0.7 A simplified method is developed based on the analysis results to estimate the annual electrical energy savings attributed to daylighting.

• Journal of Microbiology and Biotechnology
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• 제15권2호
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• pp.281-286
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• 2005

We created a new graphite-Cu(II) electrode and found that the electrode could catalyze FADH$_2$ oxidation and FAD reduction coupled to electricity production and consumption, respectively. In a fuel cell with graphite-Cu(II) anode and graphite-Fe(III) cathode, the electricity was produced by coupling to the spontaneous oxidation of FADH$_2$ Fumarate and xylose were not produced from the enzymatic oxidation of succinate and xylitol without FAD, respectively, but produced with FAD. The production of fumarate and xylose in the reactor with FAD electrochemically regenerated was maximally 2- 5 times higher than that in the reactor with FAD. By using this new electrode with catalytic function, a bioelectrocatalysts can be engineered; namely, oxidoreductase (e.g., lactate dehydrogenase) and FAD can function for biotransformation without an electron mediator and second oxidoreductase for cofactors recycling.

• 조명전기설비학회논문지
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• 제28권6호
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• pp.40-44
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• 2014

In this paper, maximum power is the lowering device using the facility's energy use and peak load electricity through analyzing attitude should like to make it reduce its power base rate. Simulator to manage the demand for power, a maximum electric power base power from electronic watt-hour meters by a device's signal, predictive power, the current power by computing the goal of power for less than Maximum peak power and peak shift, so that you can manage, and peak York, which role you want a cut Metal heat treatment result which analyzes the data, demand for electricity company over the years of analyzing the characteristics of each load, and effects and Reducing power consumption device every month identified seven Sequence control to the load system and successful power control is about showing that the defined goals.

• 미래기술융합논문지
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• 제2권4호
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• pp.43-48
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• 2023

전세계적으로 기후변화 대응을 위한 글로벌 탄소중립을 공조하고 있다. 한국의 경우 온실가스 배출량이 빠른 속도로 증가하고 있어 해결이 시급한 상황이다. 이에 본 연구는 스팀트랩이라는 열 에너지 수집 디바이스를 개발하고, 스팀트랩으로 에너지 사용량을 데이터로 수집하여 향후 전력 사용량에 대해서 예측이 가능한 AI 모델을 개발하였다. 해당 AI 모델의 전력 사용량 예측 정확도 평균은 96.7%로 높은 정확도를 보여주었다. 따라서 해당 AI 모델을 통해 어느날 전력 사용량이 높은지와 어떤 설비에서 전력 사용량이 높은지를 예측하고 관리 할 수 있게 되었다. 향후 연구는 스팀트랩의 이상탐지를 통한 효율적인 장비 운용과 에너지 관리 시스템의 표준화를 통해 에너지 소비 효율을 최적화하여 온실가스 배출을 줄이고자 한다.

• ETRI Journal
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• 제37권1호
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• pp.197-202
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• 2015

A smart grid is a modernized electrical grid that uses information about the behaviors of suppliers and consumers in an automated fashion to improve the efficiency, reliability, economics, and sustainability of the production and distribution of electricity. In the operation of a smart grid, demand side management (DSM) plays an important role in allowing customers to make informed decisions regarding their energy consumption. In addition, it helps energy providers reduce peak load demand and reshapes the load profile. In this paper, we propose a new DSM scheduling scheme that makes use of the day-ahead pricing strategy. Based on the Rubinstein-Stahl bargaining model, our pricing strategy allows consumers to make informed decisions regarding their power consumption, while reducing the peak-to-average ratio. With a simulation study, it is demonstrated that the proposed scheme can increase the sustainability of a smart grid and reduce overall operational costs.

• 한국주거학회논문집
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• 제23권4호
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• pp.11-18
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• 2012

The amount of energy consumption in the buildings is approximately 20% of domestic energy consumption. The Carbon Point Program have been published on reduction of greenhouse gas emission in buildings under the paradigm of 'Low Carbon Green Growth'. This study focuses on the effect of 'Carbon Point Program' for residential buildings in Daegu. The amount of electricity and waterwork consumption and information of households were investigated to analyse the effect of carbon point program. The samples are situated in Deagu and are apartment in Bukgu and Suseonggu. The $CO_2$ emission is analysed by factors of energy resource and household organization between before participating and after participating in Carbon Point Program. The participation type has a difference of voluntary participation in Suseonggu and passive participation in Bukgu. Based on this investigation, average amount of $CO_2$ emission was reduced from voluntary participation households but all of them did not. To promote the effect of Carbon Point Program, this study proposes that needing the plans to raise will and activity of reducing carbon and to help participation which have disadvantage against achieving reduction.

• 정보처리학회논문지:컴퓨터 및 통신 시스템
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• 제1권3호
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• pp.133-142
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• 2012

쿠르노 모델은 경쟁적 전력시장을 게임이론 기반으로 모델링하기 위한 대표적인 모델이다. 이전 연구에서도 쿠르노 모델을 이용하여 전력시장을 모델링 하기 위한 다양한 시도가 이루어져 왔다. 쿠르노 모델은 몇 개의 주요 발전사업자들이 경쟁하고 그로 인해 시장지배력이 존재하는 과점 시장모델에 적합하다. 쿠르노 모델로 시장을 모델링함에 있어서는 우하향 하는 수요함수의 존재가 선결되어야 한다. 과점에서 시장참여자들은 시장지배력을 활용하여 그들의 이익을 극대화하려고 노력하지만, 우하향하는 시장수요함수에 의해 매출 역시 하락하기 때문에 적당한 지점에서 이러한 시장지배력의 행사를 제한하여야 한다. 스마트그리드에서는 실시간으로 변동하는 요금제와 다양한 전산기반 툴의 활용으로 인해 이러한 수요반응이 더욱 활성화될 것이고, 이 경우 쿠르노 모델은 수요반응 솔루션의 주요 모델로 활용될 것이다. 이에 본 논문은 실제 시장에서 계량경제학적인 접근으로 전력시장의 수요곡선을 추정하는 방법에 대해 제안한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권2호
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• pp.312-334
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• 2023

In large-scale computing, cloud computing plays an important role by sharing globally-distributed resources. The evolution of cloud has taken place in the development of data centers and numerous servers across the globe. But the cloud information centers incur huge operational costs, consume high electricity and emit tons of dioxides. It is possible for the cloud suppliers to leverage their resources and decrease the consumption of energy through various methods such as dynamic consolidation of Virtual Machines (VMs), by keeping idle nodes in sleep mode and mistreatment of live migration. But the performance may get affected in case of harsh consolidation of VMs. So, it is a desired trait to have associate degree energy-performance exchange without compromising the quality of service while at the same time reducing the power consumption. This research article details a number of novel algorithms that dynamically consolidate the VMs in cloud information centers. The primary objective of the study is to leverage the computing resources to its best and reduce the energy consumption way behind the Service Level Agreement (SLA)drawbacks relevant to CPU load, RAM capacity and information measure. The proposed VM consolidation Algorithm (PVMCA) is contained of four algorithms: over loaded host detection algorithm, VM selection algorithm, VM placement algorithm, and under loading host detection algorithm. PVMCA is dynamic because it uses dynamic thresholds instead of static thresholds values, which makes it suggestion for real, unpredictable workloads common in cloud data centers. Also, the Algorithms are adaptive because it inevitably adjusts its behavior based on the studies of historical data of host resource utilization for any application with diverse workload patterns. Finally, the proposed algorithm is online because the algorithms are achieved run time and make an action in response to each request. The proposed algorithms' efficiency was validated through different simulations of extensive nature. The output analysis depicts the projected algorithms scaled back the energy consumption up to some considerable level besides ensuring proper SLA. On the basis of the project algorithms, the energy consumption got reduced by 22% while there was an improvement observed in SLA up to 80% compared to other benchmark algorithms.

• 전기학회논문지
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• 제59권6호
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• pp.1046-1052
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• 2010

In residential house, photovoltaic (PV) system among various alternatives in renewable energy system is the most efficient and feasible solution for reducing energy consumption and electricity cost. However, relatively high initial cost make people reluctant to install PV system in their houses. Therefore, in the initial state for PV system installation in the house, it is very important to decide proper capacity of the PV system considering the expected energy usage and solar energy supplying condition with the house. This paper proposes a novel optimization model for deciding appropriate capacity of the PV system for residential house. The objective function of the model is to minimize the annual cost including electricity bill, operation and maintenance cost, and annual fixed cost calculated from the initial installation cost based on capital recovery factor (CRF). The model also shows the optimal inclining angle of PV panels of the system. In this paper, we estimate the PV output using PVWATTS (PV simulator of Office of Energy Efficiency and Renewable Energy) and find optimal solutions by Sequential Quadratic Programming (SQP) method using MATLAB software. The proposed approach is finally applied to a residential model house in Gangneung, Gangwon-Do and verified its feasibility for adopting to PV system design for residential houses.

• 대한설비공학회:학술대회논문집
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• 대한설비공학회 2009년도 하계학술발표대회 논문집
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• pp.934-939
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• 2009

To promote citizen's involvement in the GHG(Green House Gas) reduction policy, Busan city administration adopted an pilot energy incentive system called 'energy mileage'. The energy mileage system was designed to make energy end-users motivated to reduce domestic electricity use by providing financial rewards. Through the course of the pilot period, 5,3330 householders volunteerly participated the pilot system. About 66% of the participants managed to make energy saving against the same period of the previous year while 38.8% achieved the targeted reduction rate(i.e. over 10%) and received the equivalent rewards.