• 국제학술발표논문집
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• The 9th International Conference on Construction Engineering and Project Management
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• pp.937-944
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• 2022

Electric vehicles (EVs) have been growing to reduce energy consumption and greenhouse gas (GHG) emissions in the transportation sector. The increasing number of EVs requires adequate recharging infrastructure, and at the same time, adopts low- or zero-emission electricity production because the GHG emissions are highly dependent on primary sources of electricity production. Although previous research has studied solar photovoltaic (PV) -integrated EV charging stations, it is challenging to optimize spatial areas between where the charging stations are required and where the renewable energy sources (i.e., solar photovoltaic (PV)) are accessible. Therefore, the primary objective of this research is to support decisions of siting EV charging stations using a spatial data clustering method integrated with Geographic Information System (GIS). This research explores spatial relationships of PV power outputs (i.e., supply) and traffic flow (i.e., demand) and tests a community in the state of Indiana, USA for optimal sitting of EV charging stations. Under the assumption that EV charging stations should be placed where the potential electricity production and traffic flow are high to match supply and demand, this research identified three areas for installing EV charging stations powered by rooftop PV in the study area. The proposed strategies will drive the transition of existing energy infrastructure into decentralized power systems. This research will ultimately contribute to enhancing economic efficiency and environmental sustainability by enabling significant reductions in electricity distribution loss and GHG emissions driven by transportation energy.

• 한국ITS학회 논문지
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• 제21권6호
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• pp.57-69
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• 2022

최근 다양한 전기차 판매와 향상된 서비스는 전기차 이용량을 급격히 증가시켰고, 이에 따라 전기차 충전수요가 증가하고 있다. 하지만 전기차 충전소는 부족하고 충전서비스가 필요한 위치와 설치·운영되고 있는 충전소의 위치에 차이가 있어 충전서비스의 효율성이 낮은 실정이다. 이에 본 연구에서는 이용자의 충전수요를 고려한 전기차 급속충전소의 최적입지를 선정하는 방법을 개발하였다. 충전수요를 고려할 수 있는 변수를 도출하고 데이터를 수집하였으며, AHP설문을 통해 각 변수의 가중치를 구하여 셀(cell)별로 가중평균된 입지잠재력점수를 산정하여 서울시 전역의 전기차 충전수요를 고려한 충전소의 최적입지를 도출하였다.

• Design & Manufacturing
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• 제16권2호
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• pp.13-19
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• 2022

Recently, electric vehicles are gaining popularity among many domestic and foreign users due to their eco-friendly advantages of reducing fine dust and environmental greenhouse gases. As the demand and supply of electric vehicles increase, the demand for electric vehicle charging infrastructure is also growing together. Many users are experiencing inconvenience due to poor charging infrastructure, which makes them hesitant to buy electric vehicles. Research on the user experience of chargers in apartment complexes, a common residential type in Korea, is being conducted somewhat, but research on the design of electric vehicle charging devices in public places is insufficient. The purpose of this research is to identify user requirements and complaints based on the product design of the electric vehicle charger in public places and propose a new electric vehicle product design concept that meets the requirements. The research method understood the charging base and status of electric vehicles in public places through literature research and examined and analyzed the characteristics and problems of product design cases that improved the charging problem of electric vehicles recently released in the market. It is intended to identify and analyze the problems of the charging device product design through user interviews, a qualitative research method, and based on this, it is intended to propose a user-centered product design concept that improves major complaints.

• 인터넷정보학회논문지
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• 제21권5호
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• pp.119-127
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• 2020

국내 전기차 (EV: Electric Vehicle) 시장이 성장함에 따라, 빠르게 증가하는 EV 충전 수요에 대응하기 위한 충전설비의 확충이 요구되고 있다. 이와 관련하여, 종합적인 설비 계획을 수립하기 위해서는 미래 시점의 충전 수요량을 예측하고 이를 바탕으로 전력설비 부하에 미치는 영향을 체계적으로 분석하는 것이 필요하다. 본 논문에서는 한국전력공사의 EV 충전 데이터를 이용하여 충전소 단위의 일별최대부하를 예측하는 LSTM(Long Short-Term Memory) 신경망 모델을 설계 및 개발한다. 이를 위해, 먼저 데이터 전처리 및 이상치 제거를 통해 정제된 데이터를 얻는다. 다음으로, 충전소 단위의 일별 특징들을 추출하여 훈련 데이터 집합을 구성하여 일별 최대 전력부하 예측 모델을 학습시킨다. 마지막으로 충전소 유형 별 테스트 집합을 이용한 성능 분석을 통해 예측 모델을 검증하고 이의 한계점을 논의한다.

• Journal of Electrical Engineering and Technology
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• 제13권2호
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• pp.742-751
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• 2018

Electric vehicles (EV) are emerging as the future transportation vehicle reflecting their potential safe environmental advantages. Vehicle to Grid (V2G) system describes the hybrid system in which the EV can communicate with the utility grid and the energy flows with insignificant effect between the utility grid and the EV. The paper presents an optimal power control and energy management strategy for Plug-In Electric Vehicle (PEV) charging stations using Wind-PV-FC-Battery renewable energy sources. The energy management optimization is structured and solved using Multi-Objective Particle Swarm Optimization (MOPSO) to determine and distribute at each time step the charging power among all accessible vehicles. The Model-Based Predictive (MPC) control strategy is used to plan PEV charging energy to increase the utilization of the wind, the FC and solar energy, decrease power taken from the power grid, and fulfil the charging power requirement of all vehicles. Desired features for EV battery chargers such as the near unity power factor with negligible harmonics for the ac source, well-regulated charging current for the battery, maximum output power, high efficiency, and high reliability are fully confirmed by the proposed solution.

• 농촌계획
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• 제21권1호
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• pp.19-28
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• 2015

As environmental concerns including climate change drive the strong regulations for car exhaust emissions, electric vehicles attract the public eye. The purpose of this study is to identify rural areas vulnerable for charging infrastructures based on the spatial distributions of the current gas stations and provide the target dissemination rates for promoting electric cars. In addition, we develop various scenarios for finding optimal way to expand the charging infrastructures through the administrative districts data including 11,677 gas stations, the number of whole national gas stations. Gas stations for charging infrastructures are randomly selected using the Monte Carlo Simulation (MCS) method. Evaluation criteria for vulnerability assessment include five considering the characteristic of rural areas. The optimal penetration rate is determined to 21% in rural areas considering dissemination efficiency. To reduce the vulnerability, the charging systems should be strategically installed in rural areas considering geographical characteristics and regional EV demands.

• Journal of Electrical Engineering and Technology
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• 제8권5호
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• pp.1234-1242
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• 2013

To verify the effectiveness of the proposed system, the charges in power demand are analyzed for an AC and DC distribution system for the existing V2G concept and electric vehicle charging stations connected to a Battery Energy Storage System. In addition, since many power-converter-based chargers are operated simultaneously in an EV charging station, the change in the system harmonics when several EV chargers are connected at a single point is analyzed through simulations.

• Current Photovoltaic Research
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• 제11권4호
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• pp.124-133
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• 2023

In order to deploy the large-scale energy storage (ES) service in the various industry, it is very important to develop a business model with high technological and economic feasibility through detailed valuation of cost and expected benefits. In relation to this, this paper established an optimal scheduling plan for electric vehicle charging stations connected with photovoltaic (PV) and ES technologies in Korea using the distributed energy resource valuation tool and analyzed the feasibility of the project. In addition, the impact of incentives such as REC (Renewable Energy Certificate) to be given to electric vehicle charging stations in accordance with the relevant laws to be revised in the future was analyzed. As a results, the methodology presented in this paper are expected to be used in various ways to analyze the feasibility of various business models linked to renewable energy and ES technologies as well as the electric vehicle market.

• 한국경영과학회지
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• 제37권4호
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• pp.51-65
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• 2012

Battery switching EVs are considered to be a promising alternative to overcome long charging time problems in the EV adoption. The purpose of this research is to develop integrated model for battery inventory and battery switching waiting times. Due to complexity of exact analysis, a practical approximation method is developed, which provides close results to exact values. Numerical experiments show that there exist trade-offs between the battery inventory level and the number of switching stations. The proposed model can be applied to evaluate and select the minimum cost alternative in implementing the battery switching stations.

• 산업경영시스템학회지
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• 제41권4호
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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.