• Journal of Electrical Engineering and Technology
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• 제10권3호
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• pp.859-864
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• 2015

This paper analyzes the impact of Plug-in Electric vehicles(PEVs) on power demand and voltage change when PEVs are connected to the domestic distribution system. Specifically, it assesses PEVs charging load by charging method in accordance with PEVs penetration scenarios, its percentage of total load, and voltage range under load conditions. Concretely, we develop EMTDC modelling to perform a voltage distribution analysis when the PEVs charging system by their charging scenario was connected to the distribution system under the load condition. Furthermore we present evaluation algorithm to determine whether it is possible to adjust it such that it is in the allowed range by applying ULTC when the voltage change rate by PEVs charging scenario exceed its allowed range. Also, detailed analysis of the impact of PEVs on power distribution system was carried out by calculating existing electric power load and additional PEVs charge load by each scenario on new-town in Korea to estimate total load increases, and also by interpreting the subsequent voltage range for system circuits and demonstrating conditions for countermeasures. It was concluded that total loads including PEVs charging load on new-town distribution system in Korea by PEVs penetration scenario increase significantly, and the voltage range when considering ULTC, is allowable in terms of voltage tolerance range up to a PEVs penetration of 20% by scenario. Finally, we propose the charging capacity of PEVs that can delay the reinforcement of power distribution system while satisfying the permitted voltage change rate conditions when PEVs charging load is connected to the power distribution system by their charging penetration scenario.

• 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.

• 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.

• Journal of Communications and Networks
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• 제14권6호
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• pp.672-681
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• 2012

A potential breakthrough of the electrification of the vehicle fleet will incur a steep rise in the load on the electrical power grid. To avoid huge grid investments, coordinated charging of those vehicles is a must. In this paper, we assess algorithms to schedule charging of plug-in (hybrid) electric vehicles as to minimize the additional peak load they might cause. We first introduce two approaches, one based on a classical optimization approach using quadratic programming, and a second one, market based coordination, which is a multi-agent system that uses bidding on a virtual market to reach an equilibrium price that matches demand and supply. We benchmark these two methods against each other, as well as to a baseline scenario of uncontrolled charging. Our simulation results covering a residential area with 63 households show that controlled charging reduces peak load, load variability, and deviations from the nominal grid voltage.

• 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.

• 전력전자학회논문지
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• 제22권4호
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• pp.330-335
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• 2017

Increased fossil fuel consumption causes global warming, environmental pollution, and abnormal climate change. Wind-generated power installation is proposed to solve this problem. Recently, the wind power plant construction case encourages the installation of the energy storage system (ESS) to improve the intermittency of wind power. The maximized ESS operation profits connected to wind power are not generated in the simplest operation pattern of charging at night and discharging at day. The battery charging efficiency improvement should be considered to get more profits. Thus, there is a possibility of increasing ESS operation profits by analyzing the battery AC and DC charging/discharging efficiency and the yearly average sealed maintenance free (SMP) in hours. In this paper, the battery impedance characteristic, AC and DC charging/discharging efficiency, and the yearly average SMP are analyzed. The operation scenario to improve the ESS battery charging efficiency connected to wind power is proposed and verified via simulation.

• 항공우주기술
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• 제8권2호
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• pp.122-126
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• 2009

KSLV-I은 100kg급 소형 인공위성을 지구 저궤도에 진입시키는 임무를 수행하여야 하며, 이를 위해 상단의 3축 자세제어를 위한 자세제어 시스템이 요구된다. 추력기 노즐을 통해 질소가스를 방출함으로써 발생하는 작용 반작용 모멘트를 제어모멘트로 사용하는 냉가스 추력기 자세제어 시스템을 KSLV-I 상단의 3축 자세제어 시스템으로 선정하였다. 충전 시스템의 유량 검증 및 충전 시나리오 작성을 위해 지상 충전 시스템 개발 전단계로 충전모사 시스템의 개발이 필요하다. 본 논문에서는 KSLV-I 충전 모사 시스템의 오리피스 설계, 시스템 개발, 충전 시험에 관한 것이다.

• 한국인터넷방송통신학회논문지
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• 제23권4호
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• pp.171-176
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• 2023

21세기 현대사회에 있어서 이차전지 배터리(Battery)를 이용한 휴대용 전자제품은 계속해서 경량, 소형화되어가는 추세 속에서 있다. 그리고 이러한 추세와 더불어 우리는 몸에 착용할 수 있는 전자 장비를 이용하여 하루 일상생활에서 정보를 수집, 공유하는 4차 산업혁명 시대에 활동하고 있다. 따라서 소형 가전제품 및 디지털 기기를 사용하면서 재충전할 수 있는 이차전지 배터리의 역할은 점점 더 중요하게 증가하고 있다. 이러한 증가와 더불어 이차전지 배터리 성능시험은 특성, 수명, 고장진단, 재활용 등의 다양한 시험방법을 요구하고 있으며 있다. 또한 배터리의 안전과 적절한 기능을 보장하기 위한 배터리 테스트 시스템 구축과 이에 따른 지침 및 올바른 기본지식이 고려되고 있다. 따라서 본 논문에서는 배터리의 성능과 직접으로 연결된 시나리오별 충방전에 따른 이차전지 리튬이온(Li-ion) 배터리의 특성에 대해 살펴보고자 한다.

• 한국ITS학회 논문지
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• 제23권2호
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• pp.142-156
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• 2024

교통부문 탄소중립을 위한 전기자동차로의 전환에 있어 충분한 충전 인프라의 구축은 중요한 선행요소이다. 특히, 거주지의 충전 인프라 구축은 필수적이다. 우리나라의 주거형태는 주로 공동주택이며, 다수의 거주민을 위한 공공 충전기가 공급되어야 한다. 정부는 충전시설과 전기자동차 전용주차구역의 확보를 법적으로 규정하고 있으나, 주차면수만을 산출근거로 한다. 완속 충전기는 3.5kW 과금형 콘센트와 7kW 완속 충전기가 주를 이룬다. 전자가 충전기 설치 및 이용에 유리하지만, 충전속도가 느려 두 가지 형태의 충전기는 양립이 필요하다. 본 연구에서는 일일 주행거리를 기반으로 산정한 전기자동차의 충전 수요에 대응할 수 있는 충전기를 할당하는 최적화 모형을 제시하였다. 또한, 메타 휴리스틱 알고리즘인 Tabu Search를 사용하여 최적화 모형을 만족하는 것과 동시에 충전기 공급 및 충전 비용을 최소화할 수 있는 완속 충전기 공급량을 산정하였다. 사례 분석을 위해 개인통행실태조사자료를 사용해 주행거리를 산정하였으며, 가상의 충전 시나리오 및 환경을 설정하여 100대의 전기자동차 충전 수요에 대응하는 22대의 3.5kW 과금형 콘센트를 최적 공급량으로 산정하였다.

• Journal of Electrical Engineering and Technology
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• 제9권3호
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• pp.803-811
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• 2014

The moment when Electrical Vehicle (EV) starts charging or discharging is one of the most important parameters in estimating the impact of EV load on the grid. In this paper, a decision-making problem of determining the start time of charging and discharging during allowed period is proposed and studied under the uncertainty of real-time price. Prospect theory is utilized in the decision-making problem of this paper for it describes a kind of decision making behaviors under uncertainty. The case study uses the parameters of Springo SGM7001EV and adopts the historical realtime locational marginal pricing (LMP) data of PJM market for scenario reduction. Prospect values are calculated for every possible start time in the allowed charging or discharging period. By comparing the calculated prospect values, the optimal decisions are obtained accordingly and the results are compared with those based on Expected Utility Theory. Results show that with different initial State-of-Charge ($SoC_0$) and different reference points, the optimal start time of charging can be the one between 12 a.m. to 3 a.m. and optimal discharging starts at 2 p.m. or 3p.m. Moreover, the decision results of Prospect Theory may differ from that of the Expected Utility Theory with the reference points changing.