• Journal of Electrical Engineering and Technology
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• 제8권2호
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• pp.244-251
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• 2013

This paper presents a study the change of the load profile on the power system by the charging impact of electric vehicles (EVs) in 2020. The impact of charging EVs on the load demand is determined not only by the number of EVs in usage pattern, but also by the number of EVs being charged at once. The charging load is determined on an hourly basis using the number of the EVs based on different scenarios considering battery size, model, the use of vehicles, charging at home or work, and the method of charging, which is either fast or slow. Focusing on the impact of future load profile in Korea with EVs reaching up 10 and 20 percentage, increased power demand by EVs charging is analyzed. Also, this paper analyzes the impact of a time-of-use (TOU) tariff system on the charging of EVs in Korea. The results demonstrate how the penetration of EVs increases the load profile and decreases charging demand by TOU tariff system on the future power system.

• 한국ITS학회 논문지
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• 제11권3호
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• pp.81-91
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• 2012

최근 기후변화에 따른 위기감으로 인해 세계 각국은 화석연료의 자동차를 전기자동차로 대체하기 위한 노력을 기울이고 있다. 정부는 2020년까지 소형차의 10% 이상을 전기자동차 보급 목표로 설정하였고 '주택건설 기준 등에 관한 규정'을 개정하여 전기자동차 충전설비를 공동주택의 부대설비에 포함시키는 등 충전 인프라 구축에도 노력하고 있다. 공동주택에서 전기자동차의 충전 인프라 및 주차 공간 등의 확보는 전기자동차 보급에 있어 핵심이 되지만, 이들에 대한 합리적 용량 산정 등에 필요한 전기자동차의 수요예측 연구는 미미한 상태이다. 이를 위해 본 연구는 수도권의 공동주택 거주자(분양과 임대 구분)를 대상으로, 통계자료의 시계열분석과 선호도 결과를 이용하여 전기자동차 수요를 예측하였다. 그 결과 2020년 공동주택 거주자의 전기자동차 비율은 임대아파트의 경우 6～21%, 분양아파트는 21～39% 수준이며, 이들의 사용을 지원할 최대전력량은 1,000가구 1일 기준으로 임대아파트 4,200kwh, 분양아파트 7,800kwh로 예측되었다.

• 전기학회논문지
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• 제65권9호
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• pp.1577-1582
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• 2016

Now we are facing severe environmental issues such as global warming. Due to these, the concerns about eco-friendly energy have been increased. Kyoto protocol and Copenhagen climate change conference are circumstantial evidence of it. With these trends, the interests for the Electric Vehicles(EVs) which do not emit any harmful gases have gradually been raised. Unfortunately, however, massive connection of EVs to the power system could cause negative impacts such as voltage variations, frequency variations and increase of demand power. To prevent the mentioned issues, KEPCO adopts Time-of-Use(ToU) price for EVs charging. Nevertheless, it is important to verify the propriety of the charging system. In this paper, therefore, we used pre-introduced price elasticity concept to predict possible Demand Response(DR) on charging of EVs. And analyzed possible demand power increase according to various price elasticities. Simulation results show that given ToU based charging system would not enough to control the increase of demand power by EVs on the power system. It is concluded, therefore, additional methods and/or algorithms are required.

• 디지털융복합연구
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• 제11권11호
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• pp.767-774
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• 2013

전기자동차 보급이 확대됨과 동시에 충전이 특정 시간대에 몰리거나 전력수요가 높은 시간대에 늘어나면 전력수급 균형이 불안해질 수 있다. 따라서 전기자동차 충전으로 인한 전력수요가 증가함과 동시에, 전기자동차의 전력수요를 분산시키고, 전기자동차 배터리의 여분의 전기를 활용할 수 있는 스마트그리드 구축이 중요해진다. 아직 국내에서 스마트그리드가 전기자동차의 전력망 영향 관리에 어느 정도 영향을 미치는지에 대해서는 정량적 연구가 미흡한 실정이다. 본 연구는 스마트그리드를 통한 전기자동차의 전력망 영향 관리 효과를 정량적으로 분석하고 정책적 시사점을 제시하였다. 결과적으로 스마트그리드는 전기자동차의 전력망 영향을 효과적으로 관리할 수 있었다. 전력시장 구조와 규제 프레임워크는 스마트그리드 기술의 실증과 상용화 촉진을 뒷받침할 수 있어야 할 것이다.

• 전기학회논문지
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• 제67권11호
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• pp.1455-1462
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• 2018

As the interests in eco-friendly energy has increased, the interests in Electric Vehicles(EVs) are increasing as well. Moreover, due to the government's economic support for EVs, penetration level of it has rapidly increased. These sharp increases, however, induce various problems in distribution system, such as voltage/frequency variations, peak demand increasement, demand control, etc. To minimize these possible matters, lots of research have conducted. Nevertheless, most of it assumed extremely important factors, such as numbers and charging patterns of EVs. It inevitably results in errors in their research, and thus make it difficult to prevent the possible matters from EVs. In this paper, therefore, we use actual EVs charging data from KEPCO, and analysis and deduction of it were conducted. The simulations were carried out for four aspect(season, region, purpose).

• 대한전기학회:학술대회논문집
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• 대한전기학회 2015년도 제46회 하계학술대회
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• pp.521-522
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• 2015

Many countries concern about environmental problems. Therefore, they have made regulation for mandatory reduction of greenhouse gases. Electric Vehicles(EVs) are one of the most effective counterproposals for it. EVs are usually charging for it by using actual distribution system of the Korea Electric Power Corporation(KEPCO). However, it could cause adverse effects such as increase of the power demand and voltage variation on the distribution system. To reduce adverse effects for demand power side, in this paper, charging for EVs by using PV(Photovolatic Power Generation) connected with ESS(Energy Storage System) are modeled by using Electro Magnetic Transient Program(EMTP). And then, the simulation results are compared with EVs that are connected to the distribution system of KEPCO for using charge.

• 전기학회논문지
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• 제61권6호
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• pp.783-790
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• 2012

Electric Vehicles(EVs) and Plug-in Hybrid Electric Vehicles(PHEVs) which have the grid connection capability, represent an important power system issue of charging demands. Analyzing impacts EVs charging demands of the power system such as increased peak demands, developed by means of modeling a stochastic distribution of charging and a demand dispatch calculation. Optimization processes proposed to determine optimal demand distribution portions so that charging costs and demand can possibly be managed. In order to solve the problems due to increasing charging demand at the peak time, alternative electricity rate such as Time-of-Use(TOU) rate has been in effect since last year. The TOU rate would in practice change the tendencies of charging time at the peak time. Nevertheless, since it focus only minimizing costs of charging from owners of the EVs, loads would be concentrated at times which have a lowest charging rate and would form a new peak load. The purpose of this paper is that to suggest a scenario of load leveling for a power system operator side. In case study results, the vehicles as regular load with time constraints, battery charging patterns and changed daily demand in the charging areas are investigated and optimization results are analyzed regarding cost and operation aspects by determining optimal demand distribution portions.

• Journal of Electrical Engineering and Technology
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• 제12권1호
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• pp.1-10
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• 2017

With the current global need for eco-friendly energies, the large scale use of Electric Vehicles (EVs) is predicted. However, the need to frequently charge EVs to an electrical power system involves risks such as rapid increase of demand power. Therefore, in this paper, we propose a practical smart EV charging scheme considering a Time-of-Use (ToU) price to prevent the rapid increase of demand power and provide load leveling function. For a more practical analysis, we conduct simulations based on the actual distribution system and driving patterns in the Republic of Korea. Results show that the proposed method provides a proper load leveling function while preventing a rapid increase of demand power of the system.

• 전기학회논문지
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• 제65권12호
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• pp.1949-1957
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• 2016

Rapid Expansion of EVs(Electric Vehicles) is inevitable trends, to comply with eco-friendly energy paradigm according to Paris Agreement and to solve the environment problems such as global warming. In this paper, we analyze the limit point of transformer acceptable capacity as the increase of power demand considering EVs supply in the near future. Through the analysis of transformer utilization, we suggest methods to analyze the spare capacity of transformer for the case of optimal efficiency operation and emergency operation respectively. We have the results of 18.4~29% spare capacity for the charging infrastructure to the rated capacity of transformer by analyzing the existing sample apartments. It is analyzed that the acceptable number of EVs is 0.09~0.14 for optimal efficiency operation and 0.06~0.13 for emergency operation. Therefore, it is analyzed the power demand of EV will exceed the existing transformer spare capacity in 7~8 years as the annual growth rate of EVs is prospected 112.5% considering current annual growth rate of EVs and the government EV supply policy.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권3호
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• pp.551-569
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• 2024

With the rapid development of electric vehicles (EVs) industry, EV charging service becomes more and more important. Especially, in the case of suddenly drop of air temperature or open holidays that large-scale EVs seeking for charging devices (CDs) in a short time. In such scenario, inefficient EV charging scheduling algorithm might lead to a bad service quality, for example, long queueing times for EVs and unreasonable idling time for charging devices. To deal with this issue, this paper propose a Deep-Q-Network (DQN) based two-stage scheduling method for the large-scale EVs charging service. Fine-grained states with two delicate neural networks are proposed to optimize the sequencing of EVs and charging station (CS) arrangement. Two efficient algorithms are presented to obtain the optimal EVs charging scheduling scheme for large-scale EVs charging demand. Three case studies show the superiority of our proposal, in terms of a high service quality (minimized average queuing time of EVs and maximized charging performance at both EV and CS sides) and achieve greater scheduling efficiency. The code and data are available at THE CODE AND DATA.