• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.217-224
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• 2022

Due to the issue of the sustainability in transportation area, the number of electric vehicles has significantly increased. Most automakers have decided or planned to manufacture the electric vehicles rather than carbon fueled vehicles. However, there are still some problems to figure out for the electric vehicles such as long charging time, driving ranges, supply of charging stations. Since the speed of growing the number of electric vehicles is faster than that of the number of charging stations, there are lack of supplies of charging stations for electric vehicles and imbalances of the location of the charging stations. Thus, the location problem of charging stations is one of important issues for the electric vehicles. Studies have conducted to find the optimal locations for the charging stations. Most studies have formulated the problem with deterministic or hierarchical models. In this paper, we have investigated the fluctuations of locations and the capacity of charging stations. We proposed a mathematical model for the location problem of charging stations with the vehicle routing problem. Numerical examples provide the strategy for the location routing problems of the electric vehicles.

• International conference on construction engineering and project management
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• 2022.06a
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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.

• 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.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.3
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• pp.315-319
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• 2020

The modern transportation and mobility sector is expected to encounter high penetration of Electric Vehicles (EVs) because EVs contribute to reducing the harmful emissions from fossil fuel-powered vehicles. With the prospective growth of EVs, sufficient and convenient facilities for fast charging are crucial toward satisfying the EVs' quick charging demand during their trip. Therefore, the Fast Electric Vehicle Charging Stations (FECS) will be a similar role to gas stations. In this paper, we study a charging scheduling problem for the FECS with solar photovoltaic (PV) and an Energy Storage System (ESS). We formulate an optimization problem that minimizes the operational costs of FECS. There are two cost and one revenue terms that are buying cost from main grid power, ESS degradation cost, and revenue from the charging fee of the EVs. Simulation results show that the proposed scheduling algorithm reduces the daily operational cost by effectively using solar PV and ESS.

• 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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.1-14
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• 2021

It is highly challenging to measure the efficiency of electric vehicle charging stations (EVCSs) because factors affecting operational characteristics of EVCSs are time-varying in practice. For the efficiency measurement, environmental factors around the EVCSs can be considered because such factors affect charging behaviors of electric vehicle drivers, resulting in variations of accessibility and attractiveness for the EVCSs. Considering dynamics of the factors, this paper examines the technical efficiency of 622 electric vehicle charging stations in Seoul using data envelopment analysis (DEA). The DEA is formulated as a multi-period output-oriented constant return to scale model. Five inputs including floating population, number of nearby EVCSs, average distance of nearby EVCSs, traffic volume and traffic congestion are considered and the charging frequency of EVCSs is used as the output. The result of efficiency measurement shows that not many EVCSs has most of charging demand at certain periods of time, while the others are facing with anemic charging demand. Tobit regression analyses show that the traffic congestion negatively affects the efficiency of EVCSs, while the traffic volume and the number of nearby EVCSs are positive factors improving the efficiency around EVCSs. We draw some notable characteristics of efficient EVCSs by comparing means of the inputs related to the groups classified by K-means clustering algorithm. This analysis presents that efficient EVCSs can be generally characterized with the high number of nearby EVCSs and low level of the traffic congestion.

• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.6
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• pp.57-69
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• 2022

Even though demand to charge EV(electric vehicles) is increasing, there are some problems to construct EV charging stations and problems from deficient them. Typical problem of EV charging stations is discordance for EV charging station location with its demand. This study investigates methods to determine the optimized location for fast EV charging stations considering charging demand in Seoul. Firstly, variables influencing on determination of determine the optimized location for fast EV charging stations were decided, and then evaluation of weights of the variables and data collection were conducted. Using the weights, location potential scores for each area-cell were calculated and optimized locations for fast EV charging stations were resulted.

• 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.

• Journal of the Korean Society of Safety
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• v.34 no.4
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• pp.6-14
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• 2019

There are about 38,977 CNG cars and 247 natural gas vehicle charging stations in operation in order to improve the urban air environment. With the introduction of natural gas vehicles, the atmospheric environment, which was the main cause of air pollution in the metropolitan area, was remarkably improved. However, unlike these positive effects, CNG bus accidents, which occurred more than 10 times since 2005, have caused concern among the majority of citizens using public transportation. It is necessary to make a judgment on the feasibility and future direction of CNG pressure vessel safety management that can safeguard the safety of CNG pressure vessel at the time of starting. In this study, we investigates production and use of CNG vessel, the current status of safety management of CNG bus transportation companies & charging stations and then proposes measures to prevent accident recurrence and safety management based on the actual situation investigation and analysis.