• 정보통신설비학회논문지
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• 제9권3호
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• pp.107-111
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• 2010

This paper is concerned with data center remote management service for demanding forecasting and reduction of energy usage. More particularly, intelligent server rack, mounted on inside of the data center, collects information about energy usage and temperature per server. Using this information, management platform forecasts energy demand in the future and automatically makes report according green environment raw. By providing the remote management service through remote terminals, users are not tied to a time and place to control device inside the data center. In this way, the data center remote management service enhances operability of the facility.

• 한국지열·수열에너지학회논문집
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• 제14권1호
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• pp.8-15
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• 2018

The purpose of this study was to analyze the energy consumption according to the HVAC systems in 122 elementary schools. To do this, we classified schools according to the HVAC systems. Selected schools were classified to the following groups by the HVAC equipments: EHP, EHP and GHP together and GHP. In addition we divided schools by the number of classes. The main results are as follow: 1) Annual average energy consumption at schools was about 300~900(kWh/students), $30{\sim}50(kWh/m^2)$, 9,000~29,000((kWh/class) 2) The smaller schools, the higher the energy consumption per class; energy usage of 10~19 classes's schools were approximately 3 times higher than 40 classes's schools. 3) Schools where the EHP was installed had the lowest energy costs and energy usage. The difference in energy costs was lower than the difference in energy usage because of the fuel price and the ratio of energy sources.

• 대한설비공학회:학술대회논문집
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• 대한설비공학회 2009년도 하계학술발표대회 논문집
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• pp.1343-1347
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• 2009

In order to comply with the global energy crisis and environment problem, it is necessary to research and develop the energy utilization technology with the reduction of the primary energy usage. Although the increasing rate of energy consumption started to attenuate, the entire consumption of energy as well as $CO_2$ emission rate tends to increase steadily along with an economic growth in Korea. The energy demand in Korea increases by annual 3.7% during the period from 2000 to 2006. And it is expected that we should take a charge of the greenhouse gas reduction obligation by the Climatic Change Convention(Kyoto Protocol) during the 2nd pledge period($2013{\sim}2017$). According to the IEA report in 2005, the emission amount of carbon dioxide is the 10th place in the world, and the increasing rate is 4.7% annually. Considering the economic scale of Korea, the degradation of energy usage is inevitable when the greenhouse gas reduction obligation come into effect. Therefore, effective energy usage is a very important issue to minimize baneful influence on industrial and economic activities.

• 스마트미디어저널
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• 제13권1호
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• pp.18-23
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• 2024

스마트팜의 전력 효율 관리는 기후 변화와의 연계로 중요성을 가지고 있다. 기후 변화가 농업에 부정적인 영향을 미치는 가운데, 미래의 농업은 스마트팜을 활용하여 기후 영향을 최소화할 것으로 예상되고 있으나 스마트팜의 전력 소비는 현재의 전기 생산 체제로 인해 기후 위기를 악화시킬 우려가 있다. 이에 따라 스마트팜의 전력 사용을 효율적으로 관리하고 최적화하는 것이 필수적이다. 본 연구에서는 스마트팜 장비의 전력 사용량을 실시간으로 모니터링하고, GRU를 활용하여 1시간 뒤의 전력 사용량을 예측하는 시스템을 제안한다. CT 센서를 설치하여 전력량을 수집하고, 이를 분석하여 이상 패턴을 탐지하고 예방한다. 또한 IoT 기술과 결합하여 전체 전력 사용량을 효율적으로 관리하고 모니터링한다. 이를 통해 전력 사용을 최적화하고, 에너지 효율성을 향상시켜 탄소 배출을 줄일 수 있다. 이 시스템은 스마트팜의 에너지 관리뿐아니라 전반적인 에너지 사용 효율성을 향상시킬 것으로 기대된다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권8호
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• pp.2490-2506
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• 2022

In Mobile Edge Computing (MEC), attackers can speculate and mine sensitive user information by eavesdropping wireless channel status and offloading usage pattern, leading to user privacy leakage. To solve this problem, this paper proposes a Privacy-preserving and Energy-efficient Offloading Algorithm (PEOA) based on Lyapunov optimization. In this method, a continuous Markov process offloading model with a buffer queue strategy is built first. Then the amount of privacy of offloading usage pattern in wireless channel is defined. Finally, by introducing the Lyapunov optimization, the problem of minimum average energy consumption in continuous state transition process with privacy constraints in the infinite time domain is transformed into the minimum value problem of each timeslot, which reduces the complexity of algorithms and helps obtain the optimal solution while maintaining low energy consumption. The experimental results show that, compared with other methods, PEOA can maintain the amount of privacy accumulation in the system near zero, while sustaining low average energy consumption costs. This makes it difficult for attackers to infer sensitive user information through offloading usage patterns, thus effectively protecting user privacy and safety.

• 전기학회논문지P
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• 제64권2호
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• pp.85-91
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• 2015

With the increasing popularity of Smart Grid infrastructure, it is much easier to collect energy usage data using AMI (Advanced Measuring Instrument) from residential housing, buildings and factories. Several researches have been done to improve an energy efficiency by analyzing the collected energy usage data. However, it is not easy to store and analyze the energy data using a traditional relational database management system since the data size grows exponentially with an increasing popularity of Smart grid infrastructure. In this paper, we are proposing a Hadoop based Big data system to store and analyze energy usage data. Based on our limited experiments, Hadoop based energy data analysis is three times faster than that of a relational database management system based approach with the current system.

• 한국수소및신에너지학회논문집
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• 제23권5호
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• pp.551-558
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• 2012

Due to high oil prices and global warming problems, researching an alternative energy source and decreasing the energy usage will be the key in the future. Unlike other alternative energy sources, geothermal energy is less dependent on the surrounding environment. Geothermal energy is the ideal energy source for buildings due to the simple and space saving installation. The system is semi permanent once it is installed and this will help reduce the energy usage in controlling the climate in buildings. Geothermal energy does not emit carbon dioxide and other gases that are harmful to the environment. Therefore geothermal energy will be the key in solving high oil prices and a decrease in fossil fuels by applying the geothermal energy system to homes to counter future energy crisis.

• 한국기후변화학회지
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• 제3권3호
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• pp.183-193
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• 2012

에너지분석모형인 LEAP을 활용하여 국내 대학을 대상으로 에너지 사용 및 온실가스 배출 현황과 감축 잠재량을 분석하였다. 대학의 온실가스 감축 잠재량 산정을 위해 먼저 에너지 사용을 용도별로 구분하고, 용도별 저감 방법을 제시하여 LEAP 모형을 통해 2020년까지의 감축 잠재량을 산정하였다. 온실가스 감축 잠재량 예측을 위한 시나리오는 총 4개로, 추가적인 에너지 감축 활동이 없을 때의 에너지 수요량을 예측한 기준 시나리오와 LED로의 조명 교체, 고효율 기기로의 교체를 통한 에너지 저감 시나리오, 두 가지를 모두 시행한 통합 시나리오로 구성하였다. 시나리오에 따른 결과로는 통합 시나리오를 통해 2020년 온실가스 배출량이 $14,916tCO_2eq$로 2010년 대비 43.7% 증가하는 데 그치는 것을 확인할 수 있었다. 즉, S대학교의 온실가스 배출량은 에너지 사용 저감 노력으로 기준 시나리오 대비 약 23.7%의 온실가스 배출량을 줄일 수 있었다. 또한 전자제품의 효율 향상 연구를 통해 더 많은 에너지 절감 효과를 확인하였다. 이와 함께 대학 구성원들의 의식 변화 및 직접적인 에너지 절약 실천이 이루어진다면 그 효과를 극대화 시킬 수 있을 것으로 기대된다.

• 대한건축학회논문집:구조계
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• 제34권9호
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• pp.27-34
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• 2018

The purpose of this study is to demonstrate and analyze the function of a Smart Plug before and after it is applied on the electrical appliances by controlling standby power usage. The research measures and analyzes the amount of electrical energy used while activating the Smart Plug with two types of appliances in a university facilities. The smart plugs were applied into a Group 1 appliances (Multi-function device, computer, laptop, Air con) which completely hinder the standby power, and a Group 2 appliances (Refrigerator, cold and hot water dispenser) which does not completely hinder the standby powers due to the characteristics of the function. First, the total standby power saving of all electrical appliances (Group 1 and Group 2) using the Smart plug was measured as 4.59%. Second, the energy saving of the Group 1 products was analyzed as 26.43%. Third, the standby power saving of the air conditioners from mid October to early December was measured as 31.06%, during the seasons when air conditioning was not actively in use. The research indicates that all specified appliances did have better energy efficiency with the Smart plug regardless of the amount of energy usage.

• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.401-407
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• 2022

Central heating, ventilation and air conditioning (HVAC) is one of the largest consumers of energy in the residential sector. This project explores the use of multiple HVAC units and/or Zoning in a single residence to reduce energy loads. The energy consumption data of a detached single-family home using two HVAC units, one primary for the main house and a secondary HVAC for a casita, was collected for the same month for two consecutive years, along with details related to the outdoor temperature and the square footage being air-conditioned by each HVAC. A regression algorithm was trained using the above details to find the relation between the parameters. Next, based on the occupancy and usage patterns, the HVAC was redesigned assuming more area under the secondary HVAC unit. The trained algorithm was then used to make energy usage predictions for the revised primary HVAC area, with the assumption that the secondary HVAC unit was turned off. The results were compared with existing energy usage data. It was determined that there were significant energy savings in the second scenario. It is expected that this study and its findings will help future research projects explore more ideas as alternatives to central HVAC, in improving the economic viability of existing options, and in developing a savings calculation tool that will help consumers make informed decisions on their best alternatives to central HVAC.