• The Magazine for Energy Service Companies
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• s.25
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• pp.52-59
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• 2003

에너지절약 성과배분 계약의 핵심적인 요소인 에너지절감량의 예측 및 측정방안에 대하여 일반적인 ESCO사업현장에서 빈번히 사용되는 고효율 조명기기교체, 고효율 전동기교체, 고효율 보일러교체, 냉동기 성적계수 개선 및 인버터제어 설치의 예제를 2회에 걸쳐 제시한다. 제시된 에너지절감량 측정 및 검증방안은 일반적으로 사용되는 방안이므로 현장특성이 고려되지는 않았지만 ESCO사업을 진행함에 있어서 에너지사용자와 ESCO가 최소한 공감해야 하는 에너지절감량에 대한 이해를 높이고자 작성되었다.

• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 2003.05a
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• pp.517-522
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• 2003

가스화 용융 기술은 주로 에너지 분야에 적용, 개발되어 온 기술로 폐기물의 에너지화라는 이론 연구에 머물러 왔지만, 최근에서야 효과적인 폐기물 이용을 위한 공정의 개발을 중심으로 발전되어 왔으며, 향후 연소반응에 근거한 공정을 점차 대체할 것으로 예측되고 있다. 폐기물을 대상으로 하는 가스화 용융 기술은 특히 환경 문제와 에너지 문제를 동시에 접근할 수 있는 것으로 가스화 공정을 거쳐 발생되는 생성가스에 포함된 유해 성분이 적고, 저급 에너지를 연료 가스나 연료유 둥의 고급에너지로 전환이 가능한 기술이다.(중략)

• Proceedings of the KIEE Conference
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• 2002.11b
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• pp.365-368
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• 2002

최근 몇 년간 전 세계적으로 전력 및 에너지 시장의 성장률은 매우 급격한 상승세를 기록하고 있어 가까운 장래에 전력 및 에너지 시장에서의 거래금액이 다른 어떤 상품 시장에서의 거래금액보다도 많아질 것으로 보인다. 전 세계적으로 가스 및 전기에너지 산업의 구조적 변화는 이러한 시장에 참여하고자 하는 많은 관전 기업들에게 사업상의 문제를 불러일으키고 있다. 전력 및 에너지시장은 매우 변화가 심하며, 이러한 변화에 장기적으로 대처하지 못할 경우 위험요소가 증대되어 큰 손실을 입을 수 있다. 또한 전력시장거래에서 소비자의 전력수요를 정확히 예측하고 그에 따른 최적의 발전량을 결정하는 것은 전력공급업체의 수익성을 높이는 절대적인 요소로 작용한다. 이미 오래전에 경쟁체제가 도입된 서구 국가들에서는 이러한 목적을 수행하기 위한 전력시장해석프로그램(computer-based tool)이 상용화되어 많은 업체들이 경쟁하고 있으며, 전 세계적인 구조개편 확산 움직임에 따라 시장규모가 빠른 속도로 확대되고 있다. 이러한 흐름에 따라, 우리나라에서도 일부 학계와 벤처기업 연구소를 중심으로 관련 연구가 시작되어 진행 중에 있다. 본 논문에서는 우리 연구실에서 전력시장해석 시뮬레이터 개발을 위해 벤치마킹 시뮬레이터로 도입한 PLEXOS에 대한 간단한 소개와 PLEXOS를 이용한 샘플 계통 및 시장의 전력시장가격 예측을 수행해 보고자 한다.

• Journal of the Korean Society of Radiology
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• v.17 no.2
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• pp.207-213
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• 2023

Computed tomography (CT) images are used as the basis for proton Bragg peak position estimation and treatment plan simulation. During the Hounsfield Unit (HU) based proton stopping power ratio (SPR) estimation, small differences in the patient's density and elemental composition lead to uncertainty in the Bragg peak positions along the path of the proton beam. In this study, we investigated the potential of dual-energy computed tomography image-based proton SPRs prediction accuracy to reduce the uncertainty of Bragg peak position prediction. Single- and dual-energy images of an electron density phantom (CIRS Model 062M electron density phantom, CIRS Inc., Norfolk, VA, USA) were acquired using a computed tomography system (Somatom Definition AS, Siemens Health Care, Forchheim, Germany) to estimate the SPRs of the proton beam. To validate the method, it was compared to the SPRs estimated from standard data provided by the National Institute of Standards and Technology (NIST). The results show that the dual-energy image-based method has the potential to improve accuracy in predicting the SPRs of proton beams, and it is expected that further improvements in predicting the position of the proton's Bragg peak will be possible if a wider variety of substitutes with different densities and elemental compositions of the human body are used to predict the SPRs.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.4
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• pp.332-337
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• 2013

National investment was performed in the research and development of renewable energy because of climate change by air pollution, exhaustion of energy sources, energy security, and so on. Biodiesel fuel of the renewable energy is highlighted as friendly environment energy, it is possible to operate in regular diesel engines when it is blended with invariable ratios without making any changes. Emission factors have been estimated for commercial ship from various research institutes; however, it is difficult to develop emission factors for military vessels. In this work, biodiesel blended fuel emission factors for sulfur dioxide and carbon dioxide were quantitatively estimated from propulsive diesel engine installed on naval vessel using fuel property analysis. In addition, exhaust emissions were quantitatively calculated on the basis of fuel consumption rate with biodiesel content by percentage.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.7
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• pp.867-872
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• 2010

Unused energy derived from sources in nature can be captured and stored for future use, for example, to recharge a battery or power a device; this process of capturing and storing energy is called energy harvesting. Extensive investigations are being carried out in order to use piezoelectricity to harvest the energy generated by body movements or machine vibrations. This paper presents a simple analytical model that describes the output voltage effectiveness of a Piezocomposite Generating Element (PCGE) from vibration and its experimental verification. PCGE is composed of carbon/epoxy, PZT, and glass/epoxy layers. During the manufacturing process, the stacked layers were cured at $177^{\circ}C$ in an autoclave, which created residual stresses in PCGE and altered the piezoelectric properties of the PZT layer. In the experiments, three kinds of lay-up configurations of PCGE were considered to verify the proposed prediction model and to investigate its capability to convert oscillatory mechanical energy into electrical energy. The predicted performance results are in good agreement with observed experimental ones.

• Korean Journal of Construction Engineering and Management
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• v.14 no.4
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• pp.152-163
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• 2013

In this research, we analyse the economic feasibility of a tidal power plant project which can efficiently generate mass, permanent, predictable, and homogeneous electric power. For the economic feasibility analysis, we used the RETScreen that is developed at the CANMET Energy Technology Center in Natural Resources Canada and widely utilized for analysing the economic feasibility and sensitivity of clean energy projects. Results from the feasibility and sensitivity analysis showd that the tidal power plant project in Korea has a enough economic feasibility, and its feasibility increases more as certified emission reductions price and electricity unit price increase. Based on the results from the feasibility study, we can solve the energy problems to be come in near future by constructing the tidal power plants in Korea more aggressively.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.1
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• pp.155-160
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• 2019

In this paper, we propose an efficient grid-independent ESS control system through the control of renewable energy and agricultural ICT by utilizing the prediction of energy production and consumption. The proposed system is an integrated management system that can perform maintenance and monitoring by visualizing the accurate phase and data of power system. It can automatically cope, collect, process, and control the data. Also, it can analyze the power generation of solar power generation, consumption pattern of installed facilities, and operation trend of facilities. Further, it can predict the consumption of energy production and present the optimal energy management method by using the OpenAPI of the Korea Meteorological Administration, thereby reducing unnecessary energy consumption and operating cost.

• Journal of Advanced Technology Convergence
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• v.2 no.4
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• pp.43-48
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• 2023

Globally, there is a collaborative effort to achieve global carbon neutrality in response to climate change. In the case of South Korea, greenhouse gas emissions are rapidly increasing, presenting an urgent situation that requires resolution. In this context, this study developed a thermal energy collection device named a 'steam trap' and created an AI model capable of predicting future electricity usage by collecting energy usage data through steam traps. The average accuracy of electricity usage prediction with this AI model was 96.7%, demonstrating high precision. Consequently, the AI model enables the prediction and management of days with high electricity consumption and identifies which facilities contribute to elevated power usage. Future research aims to optimize energy consumption efficiency through efficient equipment operation using anomaly detection in steam traps and standardizing energy management systems, with the ultimate goal of reducing greenhouse gas emissions.

• Economic and Environmental Geology
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• v.23 no.3
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• pp.323-328
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• 1990

This study explores that learning model that has been employed for many years in the description of and projection of system or process performance promises to be very useful in long-term forecasting, especially of technology or related productivity measures, in mineral and energy industries. This study also provides some empirical results on the measurement of the learning curve in U. S. petroleum resource assessment and demonstrates how the learning system can be used as an economic forecasting tool.