• Journal of Electrical Engineering and Technology
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• 제11권2호
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• pp.300-308
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• 2016

Application of demand-side resources to automatic generation control (AGC) has a great significance for improving the dynamic control performance of power system frequency regulation. This paper investigates the possibility of providing regulation services by demand-side energy storage in electric vehicle battery swapping stations (BSS). An interaction framework, namely station-to-grid (S2G), is presented to integrate BSS energy storage into power grid for giving benefits to frequency regulation. The BSS can be regarded as a lumped battery energy storage station through S2G framework. A supplementary AGC method using demand-side BSS energy storage is developed considering the vehicle user demand of battery swapping. The effects to the AGC performance are evaluated through simulations by using a two-area interconnected power grid model with step and random load disturbance. The results show that the demand-side BSS can significantly suppress the frequency deviation and tie-line power fluctuations.

• Journal of Electrical Engineering and Technology
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• 제13권2호
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• pp.580-590
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• 2018

Active distribution system (ADS) considering distributed generation (DG) and electric vehicle (EV) is an effective way to cut carbon emission and improve system benefits. ADS is an evolving, complex and uncertain system, thus comprehensive model and effective optimization algorithms are needed. Battery swapping station (BSS) for EV service is an essential type of flexible load (FL). This paper establishes ADS planning model considering BSS firstly for the minimization of total cost including feeder investment, operation and maintenance, net loss and carbon tax. Meanwhile, immune binary firefly algorithm (IBFA) is proposed to optimize ADS planning. Firefly algorithm (FA) is a novel intelligent algorithm with simple structure and good convergence. By involving biological immune system into FA, IBFA adjusts antibody population scale to increase diversity and global search capability. To validate proposed algorithm, IBFA is compared with particle swarm optimization (PSO) algorithm on IEEE 39-bus system. The results prove that IBFA performs better than PSO in global search and convergence in ADS planning.

• 한국기후변화학회지
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• 제8권3호
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• pp.265-273
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• 2017

Recently the Paris Climate Change Accord has been officially put into effect, making global efforts to implement Greenhouse Gas (GHG) reductions, and also International environmental regulations in the automotive sector will be further strengthened. The electric vehicle, which minimizes the particulate matter generated by existing internal combustion engine automobiles, is evaluated as a representative eco-friendly automobile. However, charging the battery of an electric vehicle is not fully environment-friendly if it is fueled by electricity that is being generated by fossil fuels as an energy source. The energy generated by the photovoltaic power generation system, which is an infinite clean energy, can be used to charge an electric vehicle's battery. Currently, shortage of charging facilities, time of charging, and high battery prices are the problem of activating the supply of electric vehicles. This study is to build a conjunction between the EVBSS (Electric Vehicle Battery Supply System) and ESS (Energy Storage System), which can quickly supply the photovoltaic charged battery to the required demand. If the charged battery in the Battery Swapping Station (BSS) is swapped swiftly, it will dramatically shorten the waiting time for charging the battery. As a result, if the battery is rented when it is needed, electric vehicles can be sold without the cost of a battery, which accounts for a large portion of the total cost, then the supply of electric vehicles are expected to expand. Furthermore, it will be an important alternative to maneuver climate change by minimizing GHG emissions from internal combustion engine vehicles.

• 한국ITS학회 논문지
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• 제12권1호
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• pp.121-135
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• 2013

전 세계적으로 지구온난화로 인한 환경문제가 심각한 위기로 인식되어지면서 세계 각국에서는 전 산업분야에 걸쳐 이산화탄소 배출을 줄이고자 노력하고 있다. 국내 에너지 부문 CO2 배출량의 약 20%를 차지하는 수송 분야의 이산화탄소 배출을 감소시키기 위해서는 전기자동차 보급 확산이 필수적이다. 최근 정부에서 전기자동차 보급 활성화를 위해 많은 노력을 기울이고 있으나 긴 충전시간과 배터리의 가격에 의한 비싼 차량가격, 짧고 불규칙한 운행거리와 부족한 충전 인프라 등으로 인하여 향후 전기자동차의 보급 확대는 매우 불투명한 상태이다. 이러한 단점을 해결하고 효과적으로 전기자동차를 보급할 수 있는 방법 중 하나가 바로 배터리 공용제 기반의 배터리 자동교환형 전기자동차 시스템이다. 이를 위해서는 배터리를 자동으로 교환해주는 시설인 배터리 교환소 (BSS: Battery Swapping Stations)가 필요하게 되는데, BSS는 배터리 교환을 통해 전기자동차가 긴 충전시간을 소모할 필요 없이 짧은 시간 내에 배터리를 충전하고 이동할 수 있도록 하는 시스템이다. 이러한 시스템을 대중교통, 특히 공공버스에 적용함으로써 보다 빠른 시간 안에 전기자동차를 보급, 확산시키는 것이 가능하다. 일반버스를 전기버스로 전환하여 버스 노선을 운영할 경우 전기버스가 중간에 멈추지 않도록 적절한 위치에 충전시설을 구축할 필요가 있다. 전기버스에 대한 충전시설은 버스 노선의 기 종점 및 기존 버스정류장에 추가로 설치하여 버스가 승객의 승 하차를 위해 정차할 때 신속하게 배터리를 교환할 수 있게 구축해야 한다. 본 연구에서는 전기버스를 위한 배터리 자동교환충전시설의 위치선정 문제를 Set Covering Problem에 적용하여 해결하였다. 배터리 충전 시 최대 주행거리를 영향권으로 설정하였으며 메타 휴리스틱 기법인 그리디 알고리즘을 활용하여 배터리 교환형 충전인프라 배치 최적화 모델을 개발하였고 현재 운영 중인 서울시의 버스노선을 대상으로 실제 충전시설의 위치를 선정하였다.