• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.349-350
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• 2018

본 논문에서는 전기 자동차 충전소의 전력 소모량 추정 알고리즘을 웹 서버에 도입하여, 충전소에 의한 전력소비가 주변 전력 계통에 미치는 영향을 모니터링할 수 있는 시스템을 제안한다. 우선, 관련 기관으로부터 공급 받는 지역 내 실시간 충전소 별 이용 상태 정보로부터 충전 시간과 그 횟수를 도출하고, 이를 충전소 마다 누적하여 소비 전력을 추정한다. 이렇게 추정된 충전소 별 전력 소모량을 웹 페이지를 통해 사용자에게 시각화하여 제공한다. 또한 같은 지역의 구간별 실시간 교통량 또한 같은 방식으로 제공하여, 전기 자동차 충전소 전력소모량의 변화 추이와 교통량의 변화 추이 간 상관관계를 확인할 수 있도록 한다. 따라서 제안하는 시스템은 지역 내 전기 자동차 충전소의 전력 소모량 및 그 변화 추이 관측하고 이를 바탕으로 지역 내 충전소 추가 설치 필요성, 전력 계통 부하 예측, 충전소 재배치 등 전기 자동차 충전소 운영 전략을 수립하는데 사용할 수 있다.

• Journal of Korean Society of Transportation
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• v.35 no.3
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• pp.210-219
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• 2017

Electric vehicles, which are attracting attention as eco-friendly vehicles, have been increasing in number since 2011 in Korea. The purpose of this study is to analyze the efficient operation of existing charging stations and factors to consider when installing additional charging stations based on the case of Jeju Island where the electric vehicle penetration rate is high and the charging infrastructure is relatively well established. The characteristics of using electric car charging stations by region, type of facility, and time of day are analyzed. As a result of analyzing the frequency of using the charger installed in Jeju Island, the utilization of both the fast charger and the slow charger is found to be concentrated in a specific area. The usage rate of charger installed in a business facility and a public parking lot is high in both fast charger and slow charger. However, according to the usage rate by time of day, the fast charger has a high utilization rate throughout the afternoon, while the use of a slow charger is concentrated in the morning. In order to enable users to utilize the electric vehicle charging station efficiently, it is necessary to provide a publicity guide for the charging station having a low utilization rate, a notice for using the charger, and a notification of completion of charging. Considering the charging demand, the area where the charger is not yet installed should be considered as the area to install the charger, and in addition, the additional installation should be considered in the area and the facility where the amount of charge is large. Service improvement is expected to be possible by utilizing actual electric vehicle charging behavior analysis result.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.8
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• pp.1575-1580
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• 2017

The electric vehicle business is important because it can reduce 30% of the fine dust generated in the metropolitan area and it can solve the air pollution problem by replacing automobile exhaust gas from an internal combustion engine with eco-friendly electric cars. For the construction of the electric charging station infrastructure, which is the core part of the electric car business, we focus to select the optimal location of the electric car charging station in Seoul. The goal of this paper is to utilize and analyze the traffic statistics of T-Map navigation users data and Seoul Metropolitan Transportation Policy Department to deploy the electric cars charging station with optimal location to increase the efficiency. In this paper, the proposed algorithm is composed of two parts of electric charging station selection. First, we analyze real traffic statistics and area. Second, we utilize T-Map navigation data distribution. To select optimal electric charging station location, we apply these two algorithms.

• Journal of Korean Association for Spatial Structures
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• v.11 no.1
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• pp.105-112
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• 2011

Fundamental Electric vehicle charge system is urgently needed for commercialization of electric vehicles. Car parking building is equipped with PV system for providing electricity to charge electric vehicles, because it must be charged at least for 30 minutes. In parking lots abroad, electric car charging stations are installed to charge electric cars by the electricity gained from PV systems which are also installed. Also, charge infrastructure construction plans and electric car charging facility support standards are being set and proposed, but there are no cases like abroad of electric car charging stations using PV systems and only electric car charging stations using ordinary electricity are being proposed. Therefore, this paper prepares establishment of domestic electric car charging networks. By researching inside outside solar parking lots and cases of abroad PV system electric car charging stations, and by analysis and comparative analysis of structural systems, structural material, and etc., many cantilever structure and small-size types were installed in PV system electric car charging stations.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.2
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• pp.131-138
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• 2023

Globally, the eco-friendly industry is developing due to the climate crisis. Electric vehicles are an eco-friendly industry that is attracting attention as it is expected to reduce carbon emissions by 30~70% or more compared to internal combustion engine vehicles. As electric vehicles become more popular, charging stations have become an important factor for purchasing electric vehicles. Recent research is using artificial intelligence to identify local demand for charging stations and select locations that can maximize economic impact. In this study, in order to contribute to the improvement of the performance of the electric vehicle charging station demand prediction model, nationwide data that can be used in the artificial intelligence model was defined and a pre-processing technique was proposed. In addition, a preprocessor, artificial intelligence model, and service web were implemented for real charging station demand prediction, and the value of data as a location selection factor was verified.

• Proceedings of the Korean Society of Computer Information Conference
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• 2022.01a
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• pp.241-242
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• 2022

지속 가능한 발전을 위해 전기자동차의 관심 및 수요가 늘어나는 상황에서 전기자동차 충전소 및 주차공간에 대한 정보 습득은 더욱 중요해졌다. 서비스 이용자는 본인의 위치를 기반으로 하여 가까운 주차장과 전기 충전소의 유무를 확인할 수 있는 DBMS를 설계하고 구축하였다. 이용자에게 주차장 및 전기 충전소에 대한 정보를 얻는 과정에서 더욱 편리함을 안겨주는 것을 목표로 하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.07a
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• pp.239-240
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• 2017

에너지 신산업 8대 산업 중 핵심 산업인 전기자동차에 대하여 전문가들의 2025년 전기자동차 600조원의 시장 형성 예측을 하고 있고 2017년 국토부는 전기자동차 전용 번호판 도입을 추진하고 있다. 이에 따른 전기자동차 수요와 공급 증가에 따른 사용자들의 증가를 예측하고 사용자 요구사항을 충족시켜줄 수 있는 홈페이지를 미리구축함으로 충전소의 길 찾기를 좀 더 쉽게 알 수 있기를 위하여 해당 프로젝트를 진행하게 되었다.

• Journal of Korean Society of Disaster and Security
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• v.14 no.2
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• pp.35-42
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• 2021

In order to produce electric vehicle demand forecasting information, which is an important element of the plan to expand charging facilities for electric vehicles, a model for predicting electric vehicle demand was proposed using Exponential Smoothing. In order to establish input data for the model, the monthly power demand of cities and counties was applied as independent variables, monthly electric vehicle charging stations, monthly electric vehicle charging stations, and monthly electric vehicle registration data. To verify the accuracy of the electric vehicle power demand prediction model, we compare the results of the statistical methods Exponential Smoothing (ETS) and ARIMA models with error rates of 12% and 21%, confirming that the ETS presented in this paper is 9% more accurate as electric vehicle power demand prediction models. It is expected that it will be used in terms of operation and management from planning to install charging stations for electric vehicles using this model in the future.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.10a
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• pp.370-372
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• 2017

Recently, at home and abroad, as the demand and supply of electric vehicles have increased, the spread of charging stations for electric vehicles is accordingly spreading out. In this paper, we provide the location, price, and service information of the electric car charging station through the big data analysis by using Open API of the public data and evaluation service provided by KEPCO, thereby inducing communication among users.

• 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.