• The KIPS Transactions:PartD
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• v.12D no.7 s.103
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• pp.1031-1038
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• 2005

In this paper, the maximum traffic quantity and actual traffic quantify of the data which are needed to grasp the statement of a system will be measured more accurately. A concrete quality measurement will be conducted by analysing a change of traffic quantity according to a protocol change and traffic under an overload condition when there is an accident. As a result can make an opportunity to maximize safety of power SCADA. Furthermore, future traffic quantity can be prospected by knowing current traffic quantity and grasping the rate of increase by the analysis and the information can be used as data to secure the band width in advance. It can make stable operation of power SCADA by arranging the limited network resources efficiently by information analysis of a network and expects more confidence.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.6
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• pp.37-42
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• 2008

In H.264/AVC decoder, intra predictor, motion compensator, and deblocking filter need to read reference images in external frame memory in decoding process. They read external frame memory very frequently, which lowers system operation speed and increases power consumption. This paper proposes a intra predictor integrated with motion compensator without external frame memory. It achieves power reduction and memory bandwidth minimization by exploiting data reuse of common and repetitive pixels. The proposed infra predictor achieves more than $45%\;{\sim}\;75%$ cycle time reduction compared with conventional intra predictors.

• Proceedings of the KIPE Conference
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• 2007.07a
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• pp.482-484
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• 2007

철도차량이 운행될 때 회생제동 구간에서는 회생에너지가 발생한다. 1500[V] DC급전시스템에서 회생된 에너지는 가선 전압을 상승시킨다. 상승된 가선전압은 급전시스템에 악영향을 주기 때문에 회생에너지를 활용하는 방법을 이용하여 가선전압을 안정화 한다. 회생에너지 활용방법의 하나인 회생에너지 저장 시스템을 적용할 때 고려해야 될 사항은 회생에너지의 발생양이다. 회생에너지의 양이 적어 활용가치가 떨어지는 구간에서는 적용하지 않기 때문에 회생량에 대한 사전 정보가 필요하다. 회생에너지의 양은 실측을 통해 얻을 수 있지만 측정을 위한 시간이나 고가의 장비를 사용해야하는 단점이 있다. 본 논문에서는 회생에너지 예측이 가능한 직류지하철 시스템의 모델링을 통해 실측시 발생하는 시간 및 비용적인 문제점을 해결할 수 있다. 회생에너지의 예측은 시뮬레이터를 이용하여 구배 및 곡선, 차량 데이터 등의 운전특성을 바탕으로 이루어진다.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.163-165
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• 1996

In this paper, we are proposed development of electric energy method and load curve. A daily electric energy is forecasted using artificial neural network. The load curve is obtained by combining forecasted electric energy and typical daily load patterns which are classified using KSOM and Fuzzy system. As a result, we know that we could get more accurate results and easier application than the results from based on the hourly historical data.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.8
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• pp.2963-2967
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• 2010

In this paper, we have predicted and analyzed the MSX 60 photovoltaic module's output according to the temperature and solar radiation conditions by MATLAB program. 2 and 3-dimensional I-V curves of the PV module considered temperature, series resistance and solar radiation variation. are shown. Also, calculated PV's electrical parameters are Isc = 3.8 A, Voc = 21 V, Pmax = 60 W. Compared with the actual photovoltaic module's data, these simulated results agreed well with within the manufacturer's maximum error range 3%.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.5
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• pp.859-866
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• 2021

Agricultural Photovoltaic power generation is a new model that installs solar power generation facilities on top of farmland. Through this, it is possible to increase farm household income by producing crops and electricity at the same time. Recently, various attempts have been made to utilize agricultural solar power generation. Agricultural photovoltaic power generation has a disadvantage in that maintenance is relatively difficult because it is installed on a relatively high structure unlike conventional photovoltaic power generation. To solve these problems, intelligent and efficient operation and diagnostic functions are required. In this paper, we discuss the design and implementation of a prediction and diagnosis system to collect and store the power output of agricultural solar power generation facilities and implement an intelligent prediction model. The proposed system predicts the amount of power generation based on the amount of solar power generation and environmental sensor data, determines whether there is an abnormality in the facility, calculates the aging degree of the facility and provides it to the user.

• Proceedings of the KIEE Conference
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• 2006.10d
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• pp.31-33
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• 2006

전력수요의 증가에 대하여 전력을 공급하는 발전기의 대용량화, 고전압화 소형경량화 됨에 따라 발전기 고장 예방을 위한 진단이 더욱더 중요시되고 있다. 이들 발전기의 전기적 고장의 대부분은 고정자 및 회전자 권선에서 발생하며 이의 고장을 복구하는데 장시간이 요구되므로, 발전기의 예측진단에 따른 정비와 더불어 고장을 미연에 발견하고 불시정지에 따른 파급을 막기 위해서는 상시감시가 요구된다. 본 연구에서는 소용량 동기발전기를 이용하여 발전기 회전자권선의 단락 고장진단을 위한 공극에서의 자속패턴을 상용 전자장해석 전문프로그램을 이용하여 수치적으로 계산하여 도출하였으며, 또한 실제 회전자 권선 단락 실험을 통하여 실제 공극에서의 자속패턴과 전자장 해석결과와 비교를 하여 전자장 해석결과의 신뢰성을 확보 하였다.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.475-478
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• 2003

본 논문에서는 쿠르노 모형을 적용한 양방향입찰 전력 풀시장에서 입찰에 참여하는 발전기가 최대 이익을 얻기 위한 입찰전략으로서 신경회로망의 오차 역전파 알고리즘을 이용하여 최적 입찰발전량과 입찰가격을 수립하는 기법에 관하여 연구한다. 전력시장 환경은 n 개의 발전기들이 참여하는 비협조적 불완전정보 시장으로 설정하고 Bayesian의 조건부 확률이론을 적용하여 상대 발전기들의 발전비용함수와 시장의 수요함수를 추정하여 발전기 상호간 쿠르노-내쉬균형점을 이루는 최적 입찰발전량을 예측한다. 그리고 이익을 극대화시키기 위해 오차 역전파 알고리즘을 이용하여 시장의 가격 탄력성과 쿠르노 시장균형가격에 연결가중치를 조절함으로써 입찰가격이 계통한계가격에 근접하도록 최적 입찰전략을 수립한다.

• Journal of the Korea institute for structural maintenance and inspection
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• v.20 no.5
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• pp.102-108
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• 2016

The purpose of this study is to examine the reduction effect of shrinkage reducing agent for drying shrinkage induced cracking and suggest the method of controlling the cracking in concrete box culvert for power transmission. Based on drying shrinkage cracking mechanism, it is necessary to perform the numerical analysis, which involves shrinkage reducing effect of shrinkage reducing agent. From the numerical results, it is found that cracking behavior for longitudinal direction and transverse direction due to differential drying shrinkage of box culvert can occur and the experimental observation of concrete cracks support the numerical predictions. The shrinkage reducing agent reduced the concrete cracking by 40~50%, which shows the methodology of controlling of drying shrinkage cracks in box culverts in real construction site.

• 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.