• Journal of Electrical Engineering and Technology
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• 제9권3호
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• pp.1132-1136
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• 2014

In the context of increasing electric energy consumption in a data center, energy efficiency improvement is strongly emphasized. In a data center, electric energy is largely consumed by DC power supply system, which is based on a rectifier composed by multiple parallel converters. Therefore, rectifier efficiency must be improved for minimizing loss of DC power supply system. Rectifier efficiency can be modulated by load allocation to converters because converter efficiency depends on input AC power. In this paper, we propose a new control method to maximize rectifier efficiency. The method can control load allocation to converters by introducing active power converter control scheme and start-and-stop of converters. In order to illustrate optimal load allocations in a rectifier, a maximization problem of rectifier efficiency is formulated as a nonlinear optimization one. The problem is solved by Lagrangian relaxation method and the computation results provide the validity of proposed method.

• 설비공학논문집
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• 제12권4호
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• pp.354-362
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• 2000

Optimal supervisory control strategy for the set points of controlled variables in the central cooling system has been studied by computer simulation. A quadratic linear regression equation for predicting the total cooling system power in terms of the controlled and uncontrolled variables was developed using simulated data collected under different values of controlled and uncontrolled variables. The optimal set temperatures such as supply air temperature, chilled water temperature, and condenser water temperature, are determined such that energy consumption is minimized as uncontrolled variables, load, ambient wet bulb temperature, and sensible heat ratio, are changed. The chilled water loop pump and cooling tower fan speeds are controlled by the PID controller such that the supply air and condenser water set temperatures reach the set points designated by the optimal supervisory controller. The influences of the controlled variables on the total system and component power consumption was determined. It is possible to minimize total energy consumption by selecting the optimal set temperatures through the trade-off among the component powers. The total system power is minimized at lower supply, higher chilled water, and lower condenser water set temperature conditions.

• 한국태양에너지학회:학술대회논문집
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• 한국태양에너지학회 2012년도 춘계학술발표대회 논문집
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• pp.522-528
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• 2012

Currently, the energy consumption of electric lighting in an office building is accounted for more than 30% of the total energy consumption. In order to reduce the energy consumed by the indoor lighting, the daylight as a natural energy resource can play an important role in energy savings. The daylight can have positive impacts on improvement of work efficiency and productivity, and also make people feel more psychologically stable. Moreover, by using the daylight, we can definitely reduce the energy consumption in office buildings. Thus, the purpose of this study is to determine the LED dimming ratio depending on the ratio by calculating the amount of artificial illumination required according to the change of daylight by using the light simulation software that can quantify and visualize the performance of daylight. As a result, the energy savings could be obtained up to 30%.

• 한국통신학회논문지
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• 제32권4A호
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• pp.365-372
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• 2007

IEEE 802.l1b 무선 네트워크에서 스테이션들이 저전력 모드로 동작할 때, 스테이션들은 액세스 포인트 (AP)가 주기적으로 전송하는 비콘(beacon)에 동기를 맞춘다. 잡음이나 이웃한 무선 네트워크의 트래픽으로 인해 비콘 수신에 장애가 발생하는 경우 다음 번 비콘까지 깨어서 에너지를 소모하게 된다. 이 논문에서 에너지를 적게 소모하면서 다음 비콘을 탐지하기 위한 방법을 제안한다. IEEE 802.l1b 무선 인터페이스의 저전력 모드에서 비콘 수신 장애 문제점이 설명되었고 에너지 소모를 줄이기 위한 새로운 탐지 방법이 제안되었다. 네트워크 시뮬레이터인 ns2를 이용하여 제안된 방법에 대해 모의실험이 수행되었고 IEEE 802.l1b의 저전력 모드와 비교했다. 스테이션이 깨어있는 시간으로 측정된 결과는 무선 네트워크에서 프레임의 수신오류가 발생할 때 에너지 소모가 개선되는 것을 보여준다.

• Journal of Electrochemical Science and Technology
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• 제9권1호
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• pp.37-43
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• 2018

In order to improve current efficiency and decrease energy consumption in the electrosynthesis of ammonium persulfate, electrolytic properties of four cation exchange membranes, namely, the $JCM-II^{(R)}$ membrane, $Nafion^{(R)}$ 324 membrane CMI-$7000^{(R)}$ membrane and a self-made perfluorosulfonic ion exchange membrane (PGN membrane) were investigated using a sintered platinized titanium anode and a Pb-Sb-Sn alloy cathode in a self-made electrolytic cell. The effect of cell voltage and electrolyte flow rate on the current efficiency and the energy consumption were investigated. The results indicated that the PGN membrane could improve current efficiency to 94.85% and decrease energy consumption to $1119kWh\;t^{-1}$ (energy consumption per ton of the ammonium persulfate generated) under the optimal operating conditions and the highest current efficiency of the $JCM-II^{(R)}$ membrane, $Nafion^{(R)}$ 324 membrane and CMI-$7000^{(R)}$ membrane were 80.73%, 77.76% and 73.22% with their lowest energy consumption of $1323kWh\;t^{-1}$, $1539kWh\;t^{-1}$ and $2256kWh\;t^{-1}$, respectively. The PGN membrane has the advantages of high current efficiency and energy power consumption and has sufficient mechanical strength with the reinforced mesh. Therefore the PGN membrane will has good value in popularization in the industrial electrosynthesis of ammonium persulfate in the future.

• 한국조명전기설비학회:학술대회논문집
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• 한국조명전기설비학회 2008년도 추계학술대회 논문집
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• pp.289-292
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• 2008

This paper represents the electric energy saving using light control system. Without Light Control System(LCS), it is very hard to classify the amount of electric energy saving for lighting, since it is determined by the end-user's preference in times. Typical LCS has an fixed algorithm to control each light's intensity by ON/Off Control, Step Control, or Dimming Control. We have studied the electric energy saving effect in a LCS equiped building with natural lighting. The electric power consumption at the peak power consumption time with LCS reduced up to 65% of the non-controled case.

• 전기전자학회논문지
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• 제22권3호
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• pp.822-828
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• 2018

최근 전력 사용량의 증가로 인한 대규모 블랙아웃 등 에너지 문제가 대두되고 있으며, 이 문제들로 인해 전력 소비량 예측에 대한 정확도를 개선할 필요성이 부각되었다. 본 연구에서는 딥 러닝 기반의 전력 사용량 예측 실험을 통해서 실제 전력 소비량과 예측된 전력 소비량의 차이를 계산하고, 이를 통해서 전력 예비율을 기존 대비 하향 조정할 수 있는 가능성에 대해서 살펴본다. 예비 전력은 사용하지 않으면 손실되는 전력으로, 본 논문에서의 딥 러닝 기반 전력 소비량 예측을 통해서 여분의 전력을 과도하게 생산하지 않도록 오차범위 내에서 전력 예비율을 감소시킬 수 있는 기반을 마련할 수 있다. 본 논문에서 사용하는 딥 러닝 기법은 시계열 데이터를 처리하는 Long-Short-Term-Memory(LSTM) 구조의 학습 모델을 이용한다. 컴퓨터 시뮬레이션에서는 임의 생성한 전력 소비 데이터를 토대로 모델을 학습시키고, 학습된 모델을 토대로 전력 사용 예측값을 구하고 실제 전력 소비량 간에 오차를 계산한 결과 오차율 21.37%를 얻을 수 있었다. 이는 최근의 전력 예비율 45.9%를 고려할 때, 본 연구에서 제안한 전력 소비량 예측 알고리즘을 적용하는 경우 20% 포인트 정도의 예비율 감축이 가능하다.

• 대한기계학회논문집B
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• 제33권8호
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• pp.629-634
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• 2009

In this paper, drying mechanism is analyzed for improving the energy efficiency of an electric clothes dryer which consumes more electric power than other appliances. For the purpose, characteristic curves of the dryer such as temperature, relative humidity, evaporation rate, mass transfer coefficient, remaining moisture content curves are experimentally obtained. Based on the experimental results and analysis of drying mechanism, the effect of power of a heater and heat loss on the power consumption of an electric clothes dryer are systematically presented. These results demonstrate the feasibility of controlling heat loss at the heater as well as the backduct component to decrease the power consumption of an electric clothes dryer.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2008년도 추계학술대회B
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• pp.2262-2267
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• 2008

In this paper, drying mechanism is analyzed for improving the energy efficiency of an electric clothes dryer which consumes more electric power than other appliances. For the purpose, characteristic curves of the dryer such as temperature, relative humidity, evaporation rate, mass transfer coefficient, remaining moisture content curves are experimentally obtained. Based on the experimental results and analysis of drying mechanism, the effect of power of a heater and heat loss on the power consumption of an electric clothes dryer are systematically presented. These results demonstrate the feasibility of controlling heat loss at the heater as well as backduct component to decrease the power consumption of an electric clothes dryer.

• 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.