• Title/Summary/Keyword: 전력소비

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Power Consumption Modeling and Analysis of Urban Unmanned Aerial Vehicles Using Deep Neural Networ (심층신경망을 활용한 도심용 무인항공기의 전력소모 예측 모델링 및 분석)

  • Minji, Kim;Donkyu, Baek
    • Journal of Korea Society of Industrial Information Systems
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    • v.28 no.1
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    • pp.17-25
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    • 2023
  • As the range of use of urban unmanned aerial vehicles (UAV) expands, it is necessary to operate UAVs efficiently because of its limited battery capacity. For this, it is required to find the optimal flight profile with various simulations. Therefore, it is important to predict the power and energy consumption of the UAV battery. In this paper, we analyzed the relationship between the speed and acceleration of the UAV and power consumption during the flight. Then, we derived a linear model, which is easily utilized. In addition, we also derived an accurate power consumption model based on deep neural network learning. To find the efficient model, we used learning data as 1) the GPS 3-axis velocity and acceleration data, 2) the IMU 3-axis velocity only, and 3) the IMU 3-axis velocity and acceleration data. The final model shows 5.86% error rate for power consumption and 1.50% error rate for the cumulative energy consumption.

Switching and Leakage-Power Suppressed SRAM for Leakage-Dominant Deep-Submicron CMOS Technologies (초미세 CMOS 공정에서의 스위칭 및 누설전력 억제 SRAM 설계)

  • Choi Hoon-Dae;Min Kyeong-Sik
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.43 no.3 s.345
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    • pp.21-32
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    • 2006
  • A new SRAM circuit with row-by-row activation and low-swing write schemes is proposed to reduce switching power of active cells as well as leakage one of sleep cells in this paper. By driving source line of sleep cells by $V_{SSH}$ which is higher than $V_{SS}$, the leakage current can be reduced to 1/100 due to the cooperation of the reverse body-bias. Drain Induced Barrier Lowering (DIBL), and negative $V_{GS}$ effects. Moreover, the bit line leakage which may introduce a fault during the read operation can be eliminated in this new SRAM. Swing voltage on highly capacitive bit lines is reduced to $V_{DD}-to-V_{SSH}$ from the conventional $V_{DD}-to-V_{SS}$ during the write operation, greatly saving the bit line switching power. Combining the row-by-row activation scheme with the low-swing write does not require the additional area penalty. By the SPICE simulation with the Berkeley Predictive Technology Modes, 93% of leakage power and 43% of switching one are estimated to be saved in future leakage-dominant 70-un process. A test chip has been fabricated using $0.35-{\mu}m$ CMOS process to verify the effectiveness and feasibility of the new SRAM, where the switching power is measured to be 30% less than the conventional SRAM when the I/O bit width is only 8. The stored data is confirmed to be retained without loss until the retention voltage is reduced to 1.1V which is mainly due to the metal shield. The switching power will be expected to be more significant with increasing the I/O bit width.

멀티히트펌프 시스템의 동계 전력피크 기여도 분석

  • Jang, Yeong-Su;Gang, Byeong-Ha
    • The Magazine of the Society of Air-Conditioning and Refrigerating Engineers of Korea
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    • v.39 no.11
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    • pp.17-21
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    • 2010
  • 고효율 난방기기인 멀티히트펌프의 소비전력분석을 통해, 멀티히트펌프 보급이 동계 전력피크에 미치는 영향을 분석한다.

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Electric Power Situation in the ECAFE Region (ECAFE 지역의 전력사정)

  • 대한전기협회
    • JOURNAL OF ELECTRICAL WORLD
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    • no.12 s.14
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    • pp.30-41
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    • 1968
  • 이자료는 1968년 5월 30일$\~$6월 6일에 걸쳐 싱가포르에서 개최된 ECAFE의 제11회 에너지자원$\cdot$전력소위원회에 제출된 것으로서 ECAFE사무국이 작성한 것이다. ECAFE지역 각국의 발전설비(수력발전소, 화력발전소, 가스$\cdot$터어빈, 원자력발전소), 발전전력량, 연료문제, 송전계통 및 전력소비에 관해서 그 개요를 간결하게 기술한 것이다.

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Networked Smart Plug System for Power Management of PC & Peripherals (PC와 주변기기의 전력 관리를 위한 네트워크 기반의 스마트 플러그 시스템)

  • Ryu, Dae-Hyun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.16 no.10
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    • pp.2171-2176
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    • 2012
  • PCs and its peripherals uses more power in standby mode even if they are not actually being used. In particular, PCs and its peripherals used in school and office, plugged in at all times during working hours, but not used much time, even if turned off consume a portion of the power. In this paper, we developed Networked Smart Plug for Power Management of PC & Peripherals which is consist of EMS, Smart Plug, PC Agent and Smart Phone App. for power saving of PC and a variety of peripheral devices in office or home, and evaluated the performance of the system.

동경전력 대대적인 절전캠페인 실시!!

  • 대한전기협회
    • JOURNAL OF ELECTRICAL WORLD
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    • s.315
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    • pp.57-65
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    • 2003
  • 일본 최대 전력회사인 도쿄(동경)전력(주)는 후쿠시마 제1원자력발전소 제1호기의 격납용기 보수사실 은폐와 보수기록 허위작성 등의 협의로 2002년 10월 원자력안전$\cdot$보안원으로부터 1년간의 발전정지처분을 받았으며, 이에 대한 책임으로 도쿄전력의 회장(황목호), 사장(남직재) 등 경영간부들이 사직하였다. 또한 원자력발전소의 잦은 고장으로 인하여 국민들로부터 신뢰를 잃고 있다. 이에 모든 원자력발전소에 대하여 철저한 점검계획을 작성$\cdot$실시하는 등 신뢰회복에 심혈을 기울이고 있다. 한편, 도쿄전력은 기저부하를 담당하고 있던 원자력발전소 17기 중 12기가 발전정지 됨으로써 전력공급에 어려움을 겪고 있으며, 특히 금년 3월 이후에는 공급예비율이 $0\%$에 이를 것으로 전망되는 등 전력수급에 비상이 걸렸다. 이르 극복하기 위해 화력발전소의 O/H일정 조정, 부하조절 시행, 대국민 절전 홍보를 대대적으로 실시하고 있다. 이와같이 도쿄전력에서 절전캠페인을 실시하는 것은 1973년 오일쇼크 이래 처음 있는 일이다. 우리 나라도 전력소비 및 LNG 소비의 급증으로 에너지 수급에 많은 어려움을 겪고 있다. 특히 최근에는 미국$\cdot$이라크 전쟁위기감이 고조되면서 국제 유가가 급등하고 있어 ''에너지절약 강화대책 시행'' 등 에너지위기 극복을 위해 전국민적인 노력을 기울이고 있다. 이에 일본에서 벌어지고 있는 절전캠페인을 참고하여 우리 나라의 에너지위기 극복에 조금이나마 도움이 되었으면 하는 바램으로, 그중 일부 ''전력기기별 절전내용''을 소개한다.

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Machine Learning Approach for Pattern Analysis of Energy Consumption in Factory (머신러닝 기법을 활용한 공장 에너지 사용량 데이터 분석)

  • Sung, Jong Hoon;Cho, Yeong Sik
    • KIPS Transactions on Computer and Communication Systems
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    • v.8 no.4
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    • pp.87-92
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    • 2019
  • This paper describes the pattern analysis for data of the factory energy consumption by using machine learning method. While usual statistical methods or approaches require specific equations to represent the physical characteristics of the plant, machine learning based approach uses historical data and calculate the result effectively. Although rule-based approach calculates energy usage with the physical equations, it is hard to identify the exact equations that represent the factory's characteristics and hidden variables affecting the results. Whereas the machine learning approach is relatively useful to find the relations quickly between the data. The factory has several components directly affecting to the electricity consumption which are machines, light, computers and indoor systems like HVAC (heating, ventilation and air conditioning). The energy loads from those components are generated in real-time and these data can be shown in time-series. The various sensors were installed in the factory to construct the database by collecting the energy usage data from the components. After preliminary statistical analysis for data mining, time-series clustering techniques are applied to extract the energy load pattern. This research can attributes to develop Factory Energy Management System (FEMS).

해외동향

  • Korea Electrical Manufacturers Association
    • NEWSLETTER 전기공업
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    • no.97-15 s.184
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    • pp.9-23
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    • 1997
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