• Proceedings of the Korean Society of Computer Information Conference
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• 2019.01a
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• pp.293-294
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• 2019

본 논문에서는 전기차 파생 IT융합 서비스의 일환으로 원활한 전기차 충전을 지원하기 위한 불법 주차 방지 시스템을 제안한다. 국내 전기차 관련 법에 따르면 전기차 충전소 앞에 전기차가 아닌 일반 차량이 불법으로 주차를 하게 되면 과태료를 내게 되어 있다. 따라서, 제안한 시스템에서는 전기차가 아닌 일반차가 주차를 하면 경광등 작동시켜 운전자에게 경고한다. 제안한 시스템에서는 딥러닝 기반의 영상인식 SW를 적용하였다. 다양한 조도 환경에서 인식 성공률을 분석하였고 어두운 저녁에는 주변 광량에 따라 인식이 잘 이뤄지지 않는 것을 확인하였다. 향후 추가 LED를 더해 광량의 부족함에 따른 인식률 저하를 개선하는 연구를 진행할 계획이다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2019.07a
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• pp.443-444
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• 2019

본 논문에서는 라즈베리파이(Raspberry Pi)와 실시간 객체 감지 기술인 YOLO를 이용한 전기차충전기앞불법주차 경고 영상인식 시스템을 제안한다. 최근 전기 자동차의 사용과 더불어 충전 인프라는 점점 늘어나는 중이지만, 여전히 전기차 충전기는 많지 않은 것이 현실이다. 전국 1,000여 곳이 넘는 전기차 충전소에 대해 법령으로 인한 규제를 시행 중임에도 불구하고 불법주차를 하는 일반차 오너들은 여전히 많다. 이로 인해 전기차 오너들은 충전에 많은 불편함이 있다. 이 시스템은 전기 자동차의 번호판을 인식하여 실시간 객체 감지 딥러닝 기법인 YOLO를 이용해 전기 자동차의 번호판에 특정 부분을 인식하고 특정 부분이 없는 일반 자동차가 전기차 충전기 앞 불법 주차를 하게 되면 부저와 LED경고를 통해 주차된 일반 차량에게 경고를 하여, 불법 주차자와 더불어 주변을 지나가는 행인들에게도 전기차 앞 불법 주차에 대해 각인을 시켜줄 수 있는 시스템이다.

• Journal of Internet Computing and Services
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• v.21 no.5
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• pp.119-127
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• 2020

As the electric vehicle (EV) market in South Korea grows, it is required to expand charging facilities to respond to rapidly increasing EV charging demand. In order to conduct a comprehensive facility planning, it is necessary to forecast future demand for electricity and systematically analyze the impact on the load capacity of facilities based on this. In this paper, we design and develop a Long Short-Term Memory (LSTM) neural network model that predicts the daily peak electric load at each charging station using the EV charging data of KEPCO. First, we obtain refined data through data preprocessing and outlier removal. Next, our model is trained by extracting daily features per charging station and constructing a training set. Finally, our model is verified through performance analysis using a test set for each charging station type, and the limitations of our model are discussed.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.279-280
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• 2023

최근 지구온난화로 인해 온도가 점점 상승하면서 홍수, 가뭄, 해수면 상승 등 이상 기후가 나타나고 있다. 이러한 상황을 막기 위해 기업과 국가 더 나아가 전 세계적으로 탄소 중립 활동을 실천하고 있다, 본 논문에서는 탄소 중립 활동에 도움을 주고자 전기차 충전소의 위치와 현재 상태를 실시간으로 확인할 수 있는 웹사이트를 서비스한다. 또한 사용자의 걷기 활동을 통해 이벤트를 진행하여 탄소 중립 활동을 장려하며, 다양한 교통정보 등을 서비스한다,

• Information Systems Review
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• v.18 no.4
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• pp.1-15
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• 2016

Electric cars are expected to increase quality of life by reducing air pollution and to contribute to economic growth by creating new businesses. However, electric car adoption has lagged and has not satisfied public expectation. One of the primary reasons for this outcome is the slow charging speed or inconvenience of charging a battery. Under the insufficient diffusion of electric cars, pushing business entities to construct charging facilities is undesirable for a policy maker to increase the adoption rate because of cost and management issues. This study adopts the design science methodology to interpret the problem of deploying electric car charging stations in the view of information systems. A trip planning algorithm is suggested on the basis of the theory of range anxiety. We investigate issues related to the current charging locations using data from drivers' car navigation devices. We also review its applicability to trip planning to obtain insights.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06d
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• pp.159-162
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• 2011

스마트그리드는 기존의 전력 생산, 운반, 소비의 과정에 정보통신 기술을 접목하여 에너지 절감 및 전기 품질 향상 등을 제공하는 차세대 전력망으로써 스마트 미터 중심의 AMI, 에너지 관리 시스템, 전기 자동차 및 충전소, 재생에너지, 양방향 정보통신 기술, 배전 자동화 시스템 등으로 구성된다. 이중 미터기, 수용가 전력기기, 근거리 통신기술, 데이터 관리 시스템 등은 "제주도 실증단지구축"사업의 핵심 요소로써, 국내 기업들의 활발한 연구가 이루어지고 있다. 하지만 국내에서 연구되고 있는 스마트그리드 구축과 관련된 소프트웨어들은 외산 솔루션에 기반하고 있거나 자체개발을 통해 이루어지고 있어 기술 지원 부재 및 개발 소요 시간이 길다는 문제점을 가지고 있다. 따라서 본 논문에서는 이러한 문제점을 해결하기 위해 오픈 소스 소프트웨어 기반의 스마트그리드 통합시설관제시스템을 제안하고, 구축하도록 한다.

• Transactions of the Korean hydrogen and new energy society
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• v.28 no.6
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• pp.642-648
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• 2017

The use of fossil is causing enviromental all over the world. So hydrogen energy is attracting attention as one of the alternative. The government announced that 30% of the air pollution is because of the Internal Combustion Engine Vehicle. In addition, they plans to reduce Internal Combustion Engine Vehicles by 2030 and increase (electric vehicles, EV) or (fuel cell vehicle, FCV). The FCV is evaluated as a next-generation green car because it has a long driving distance and short charging time. However, the hydrogen industry is not able to expand due to the lack of refueling infrastrucutre. This paper predicts the site of hydrogen refueling stations for the expansion of the hydrogen industry and proposes a method to supply hydrogen multi energy filling stations.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.171-180
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• 2023

Hydrogen energy technology is gaining importance in the era of the Fourth Industrial Revolution, offering military advantages when applied to military vehicles due to its characteristics such as reduced greenhouse gas emissions, noise, and low vibration. Korea's military has initiated the Army Tiger 4.0 plan, focusing on hydrogen application, downsizing, and AI-based smart features. The Ministry of National Defense plans to collaborate with the Ministry of Environment to expand hydrogen charging stations nationwide, anticipating increased deployment of military hydrogen vehicles. However, considering the Jet Fire and VCE(Vapor Cloud Explosion) nature of hydrogen, ensuring safety during installation is crucial. Current military guidelines specify a minimum safety distance of 2m from adjacent buildings for charging stations. Scientific methods have been employed to quantitatively assess the accident damage range of hydrogen, proposing a minimum safety distance beyond the affected area.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.3
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• pp.53-60
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• 2020

Evaluating the operational efficiency of electric vehicle charging stations (EVCSs) is important to understand charging network evolution and the charging behavior of electric vehicle users. However, aggregation of efficiency performance metrics poses a significant challenge to practitioners and researchers. In general, the operational efficiency of EVCSs can be measured as a complicated function of various factors with multiple criteria. Such a complex aspect of managing EVCSs becomes one of the challenging issues to measure their operational efficiency. Considering the difficulty in the efficiency measurement, this paper suggests a way to measure the operational efficiency of EVCSs based on data envelopment analysis (DEA). The DEA model is formulated as constant returns of output-oriented model with five types of inputs, four of them are the numbers of floating population and nearby charging stations, distance of nearby charging stations and traffic volume as desirable inputs and the other is the traffic speed in congestion as undesirable one. Meanwhile, the output is given by the charging frequency of EVCSs in a day. Using real-world data obtained from reliable sources, we suggest operational efficiencies of EVCSs in Seoul and discuss implications on the development of electric vehicle charging network. The result of efficiency measurement shows that most of EVCSs in Seoul are inefficient, while some districts (Nowon-gu, Dongdaemun-gu, Dongjak-gu, Songpa-gu, Guro-gu) have relatively more efficient EVCSs than the others.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.4
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• pp.9-21
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• 2018

In South Korea, Jeju Island has a role as a test bed for electric vehicles (EVs). All conventional cars on the island are supposed to be replaced with EVs by 2030. Accordingly, how to effectively set up EV charging stations (EVCSs) that can charge EVs is an urgent research issue. In this paper, we present a case study on planning the locations of EVCS for Jeju Island, South Korea. The objective is to determine where EVCSs to be installed so as to balance the load of EVCSs while satisfying demands. For a public service with EVCSs by some government or non-profit organization, load balancing between EVCS locations may be one of major measures to evaluate or publicize the associated service network. Nevertheless, this measure has not been receiving much attention in the related literature. Thus, we consider the measure as a constraint and an objective in a mixed integer programming model. The model also considers the maximum allowed distance that drivers would detour to recharge their EV instead of using the shortest path to their destination. To solve the problem effectively, we develop a heuristic algorithm. With the proposed heuristic algorithm, a variety of numerical analysis is conducted to identify effects of the maximum allowed detour distance and the tightness of budget for installing EVCSs. From the analysis, we discuss the effects and draw practical implications.