• Journal of Communications and Networks
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• v.14 no.6
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• pp.662-671
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• 2012

Plug-in hybrid electric vehicles (PHEVs) will be widely used in future transportation systems to reduce oil fuel consumption. Therefore, the electrical energy demand will be increased due to the charging of a large number of vehicles. Without intelligent control strategies, the charging process can easily overload the electricity grid at peak hours. In this paper, we consider a smart charging and discharging process for multiple PHEVs in a building's garage to optimize the energy consumption profile of the building. We formulate a centralized optimization problem in which the building controller or planner aims to minimize the square Euclidean distance between the instantaneous energy demand and the average demand of the building by controlling the charging and discharging schedules of PHEVs (or 'users'). The PHEVs' batteries will be charged during low-demand periods and discharged during high-demand periods in order to reduce the peak load of the building. In a decentralized system, we design an energy cost-sharing model and apply a non-cooperative approach to formulate an energy charging and discharging scheduling game, in which the players are the users, their strategies are the battery charging and discharging schedules, and the utility function of each user is defined as the negative total energy payment to the building. Based on the game theory setup, we also propose a distributed algorithm in which each PHEV independently selects its best strategy to maximize the utility function. The PHEVs update the building planner with their energy charging and discharging schedules. We also show that the PHEV owners will have an incentive to participate in the energy charging and discharging game. Simulation results verify that the proposed distributed algorithm will minimize the peak load and the total energy cost simultaneously.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.11
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• pp.1793-1799
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• 2016

As one of the main trends in global industries is eco-friendly energy, the interest on Electric Vehicle(EV) has been increased. However, if large amount of EVs start to charging, it could cause rapid increase in demand power of the power system. To guarantee stable operation of the power system, those unpredictable power consume should be mitigated. In this paper, therefore, we propose a practical smart EVs charging scheme to prevent the rapid increase of the demand power and also provide load flattening function. For that we considered Time-of-Use(ToU) price and actual data such as driving pattern and parameters of distribution system. Simulation results show that the proposed method provides proper load flattening function while preventing the rapid increase of the demand power of the power system.

• Journal of the Korea Society for Simulation
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• v.24 no.1
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• pp.35-43
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• 2015

This research proposed a new method to evaluate the objective validity to launch smart transportation services that various stakeholders are complicatedly inter-connected. First of all, we have designed the fundamental business model to form the smart transportation services and defined the stakeholders taking part in the services. Also, the criteria to evaluate the economical validity has been proposed based on the relationship among stakeholders. Especially, in the case EV drivers and charging service providers, the economical validity depends on the scale of spreading. Therefore, we have compared the two extreme scenarios, the poor and stable level of EV spreading. According to the result, it may be said that EV drivers and charging service providers cannot be guaranteed the economical validity due to the burden of initial investment. On the contrary to this, suppliers of EV and charging gears may secure more than a certain level of profit. In addition, the government may have great profit due to reducing the CO2 emission and cost for importing energy sources. Therefore, it is needed to enhance the level of supporting EV drivers and charging service providers at the first stage. Also, the impact of the ratio of EV and charging service stations on the economical validity of smart transportation should be further investigated.

• 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 Information Technology Services
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• v.21 no.6
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• pp.117-125
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• 2022

In respond to climate change caused by global environmental problems, countries around the world are actively promoting the advancement of new electricity industries. The new energy business is being applied to energy storage systems (ESS), electric vehicle charging business, and power demand response using cutting edge technologies. In 2022, the Korean government is also establishing a policy stance to foster new energy industries and making efforts to improve its responsiveness to power demand response with the innovative technologies. In Korea, attempts to commercialize energy power are also being made in the private and public sectors to control energy power in houses, buildings, and industries. For example, private companies, local governments, and central government are making all-out efforts to develop new energy industry models through joint investment. There are forms such as establishing energy-independent facilities by region, establishing an electric vehicle charging system, controlling urban lighting systems with Information technologies, and managing demand between power suppliers and power consumers. This study examined the business model applied with energy storage system, electric vehicle charging business, smart lighting, and power demand response based on information communication technology to examine the site where smart energy system was introduced. According to this study, company missions and government tasks are suggested to apply new energy business technologies as economical energy solutions that meet the purpose of use by region, industry, and company.

• Journal of Electrical Engineering and Technology
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• v.11 no.4
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• pp.810-819
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• 2016

Uncoordinated charging of large-scale electric vehicles (EVs) will have a negative impact on the secure and economic operation of the power system, especially at the distribution level. Given that the charging load of EVs can be controlled to some extent, research on the optimal charging control of EVs has been extensively carried out. In this paper, two possible smart charging scenarios in China are studied: centralized optimal charging operated by an aggregator and decentralized optimal charging managed by individual users. Under the assumption that the aggregators and individual users only concern the economic benefits, new load peaks will arise under time of use (TOU) pricing which is extensively employed in China. To solve this problem, a simple incentive mechanism is proposed for centralized optimal charging while a rolling-update pricing scheme is devised for decentralized optimal charging. The original optimal charging models are modified to account for the developed schemes. Simulated tests corroborate the efficacy of optimal scheduling for charging EVs in various scenarios.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.22 no.5
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• pp.1027-1037
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• 2012

With response to the critical issue of global warming, Smart Grid system has been extensively investigated as next efficient power grid system. Domestically, Korean is trying to expand the usage of Electric Vehicles (EVs) and the charging infrastructure in order to replace the current transportation using fossil fuels holding 20% of overall CO2 emission. The EVs charging infrastructures are combined with IT technologies to build intelligent environments but have considerable number of cyber security issues because of its inherent nature of the technologies. This work not only provides logical architecture of EV charging infrastructures with security threats based on them but also analyses security requirements against security threats in order to overcome the adversarial activities to Smart Grid.

• Journal of Advanced Navigation Technology
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• v.21 no.6
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• pp.620-625
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• 2017

Recently, the solar module for charging internet devices is installed in crowded areas to offers services so that people can charge their smartphones or tablets. But this charging module can not be linked with the information related to a bus approach so people are subject to let their belongings such as smartphone, tablet pc at the bus stop while they are still charging it. This paper proposes a system to inform the smart phone when the bus is accessed by using the LPWA technology and BLE technology to resolve such under-failures. This experimental result showed that the power usage of LPWA based bus entry systems is an average of X, confirming that the long period usage of low-power can be possible for low power consumption in this results, enabling information on the bus to be transmitted to smart phones using Advertising mode of BLE.

• 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.

• Smart Media Journal
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• v.9 no.1
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• pp.67-74
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• 2020

As the demand of electric vehicles has been increased recently, their related industries are developing. In particular, the market of electric vehicles charging infrastructure is expanding rapidly and users have much demand in convenience of electric vehicles charging site. Because an charging site using electric pole of KEPCO can make use of that installed nearby public parking lots, there are many commercial construction and convenient facilities near around it. In this situation, users can do shopping or their personal business during charging. In this paper, we proposed the design of charging platform for electric vehicles to support LBS for users to do shopping or personal business conveniently.