• 제목/요약/키워드: ESS lithium battery

검색결과 52건 처리시간 0.032초

리튬이온 배터리를 이용한 에너지저장장치 시스템의 잠재수익 산출 기법 (Potential Revenue Prediction Method of ESS using Lithium-ion Battery)

  • 원일권;김도윤;장영희;추경민;홍성우;원충연
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 2016년도 전력전자학술대회 논문집
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    • pp.423-424
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    • 2016
  • Recently, the mass production of Energy storage system (ESS) is actively perform around world. Energy storage system is a technique that stores power to energy storage device to supply energy into grid and load at peak-load. Therefore, the efficient energy management is available by using ESS system. The life of Lithium-ion battery is varied corresponding to the power usage, especially selected depth of discharge (DOD). The lifetime of battery is the one of the most issue of the ESS system because of its stability and reliability. Therefore, lifetime management of battery and power converter of ESS module is required. In this paper, the battery lifetime management method estimating residual power and lifetime of lithium ion battery of ESS system is proposed. Also, total avenue prediction of ESS system is simulated considering the total lifetime of battery.

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Lifetime Management Method of Lithium-ion battery for Energy Storage System

  • Won, Il-Kuen;Choo, Kyoung-Min;Lee, Soon-Ryung;Lee, Jung-Hyo;Won, Chung-Yuen
    • Journal of Electrical Engineering and Technology
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    • 제13권3호
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    • pp.1173-1184
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    • 2018
  • The lifetime of a lithium-ion battery is one of the most important issues of the energy storage system (ESS) because of its stable and reliable operation. In this paper, the lifetime management method of the lithium-ion battery for energy storage system is proposed. The lifetime of the lithium-ion battery varies, depending on the power usage, operation condition, and, especially the selected depth of discharge (DOD). The proposed method estimates the total lifetime of the lithium-ion battery by calculating the total transferable energy corresponding to the selected DOD and achievable cycle (ACC) data. It is also demonstrated that the battery model can obtain state of charge (SOC) corresponding to the ESS operation simultaneously. The simulation results are presented performing the proposed lifetime management method. Also, the total revenue and entire lifetime prediction of a lithium-ion battery of ESS are presented considering the DOD, operation and various condition for the nations of USA and Korea using the proposed method.

VRFB-LFPB 하이브리드 배터리 기반의 ESS 개발에 관한 연구 (Development of ESS Based on VRFB-LFPB Hybrid Batteries)

  • 천영식;박진수;유진호;이진
    • 한국전기전자재료학회논문지
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    • 제31권1호
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    • pp.61-67
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    • 2018
  • High-power lithium batteries are suitable for equipment with high power output needs, such as for ESS's initial start-up. However, their management cost is increased by the installation of air-conditioning to minimize the risk of explosion due to internal temperature rise and also by a restriction on the number of charge/discharge cycles. High-capacity flow batteries, on the other hand, have many advantages. They can be used for over 20 years due to their low management costs, resulting from no risk of explosion and a high number of charge/discharge cycles. In this paper, we propose an ESS based on hybrid batteries that uses a lithium iron phosphate battery (LiFePO) at the initial startup and a vanadium redox flow battery (VRFB) from the end of the transient period, with a bi-directional PCS to operate two batteries with different DC voltage levels and using an efficient energy management control algorithm.

재사용 ESS를 위한 리튬 배터리 덴드라이트 보호 알고리즘 제안 (Proposal Protection Algorithm of Dendritic Lithium for Battery Second Use ESS)

  • 송정용;허창수
    • 한국전기전자재료학회논문지
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    • 제31권6호
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    • pp.422-426
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    • 2018
  • The lithium-ion battery pack of an electric vehicle (EV) deserves to be considered for an alternative use within smart-grid infrastructure. Despite the long automotive service life, EV batteries retain over 70~80% of their initial capacity. These battery packs must be managed for their reliability and safety. Therefore, a battery management system (BMS) should use specific algorithms to measure and estimate the status of the battery. Most importantly, the BMS of a grid-connected energy storage system (ESS) must ensure that the lithium-ion battery does not catch fire or explode due to an internal short from uncontrolled dendrite growth. In other words, the BMS of a lithium-ion battery pack should be capable of detecting the battery's status based on the electrochemical reaction continuously until the end of the battery's lifespan. In this paper, we propose a new protection algorithm for a dendritic lithium battery. The proposed algorithm has applied a parameter from battery pack aging results and has control power managing.

연축전지와 리튬이온전지용 하이브리드 ESS의 최적구성방안에 관한 연구 (A Study on Estimation Method for Optimal Composition Rate of Hybrid ESS Using Lead-acid and Lithium-ion Batteries)

  • 박수영;유상원;박재범;김병기;김미영;노대석
    • 전기학회논문지
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    • 제65권6호
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    • pp.962-968
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    • 2016
  • The large scaled lead-acid battery is widely used for efficient operation of the photovoltaic system in many islands. However, lithium-ion battery is now being introduced to mitigate the fluctuation of wind power and to replace lead-acid battery. Therefore, hybrid ESS(Energy Storage system) that combines lithium-ion battery with lead-acid battery is being required because lithium-ion battery is costly in present stage. Under this circumstance, this paper presents the optimal algorithm to create composition rate of hybrid ESS by considering fixed and variable costs in order to maximize advantage of each battery. With minimization of total cost including fixed and variable costs, the optimal composition rate can be calculated based on the various scenarios such as load variation, life cycle and cost trend. From simulation results, it is confirmed that the proposed algorithms are an effective tool to produce a optimal composition rate.

변동부하 공급을 위한 하이브리드 ESS의 연축전지와 리튬이온전지의 최적구성방안에 관한 연구 (A Study on Optimal Configuration Method of Hybrid ESS using Lead-acid and Lithium-ion Batteries for Supply of Variation Loads)

  • 노대석;최성식;이후동;장병훈;김수열
    • KEPCO Journal on Electric Power and Energy
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    • 제2권1호
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    • pp.49-54
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    • 2016
  • 현재 대부분의 도서지역에서는 태양광발전을 효율적으로 운용하기 위하여 대용량 연축전지가 많이 사용되고 있지만, 풍력발전의 도입, 축전지 교체로 인하여 리튬이온전지의 도입이 증가하고 있다. 따라서 본 논문에서는 기존에 많이 보급되어 사용되고 있는 연축전지와 리튬이온전지의 장점을 최대한 활용하기 위하여, 연축전지와 리튬이온전지용 하이브리드 ESS의 최적 운용평가를 할 수 있는 알고리즘을 제시하였다. 상기의 알고리즘을 이용하여 시뮬레이션을 수행한 결과, 각 전지의 도입비용과 운용비용이 최소화 되는 운용조건에서 최적구성비를 산출하였다. 이에 따라 본 논문에서 제안한 하이브리드 ESS의 최적구성 알고리즘에 대한 유용성을 확인하였다.

ESS(Energy Storage System) 기술동향에 관한 연구 (The Study on the Technical Trends of ESS(Energy Storage System))

  • 배진용;김용;권순도;이은영;조규만;엄태민;홍성진
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2015년도 제46회 하계학술대회
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    • pp.637-638
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    • 2015
  • This paper review the technical trends of ESS(Energy Storage System). The ESS has been displaced by cathode, anode, electrolyte, and separator. The lithium-ion battery is getting the most attention in the ESS. In this paper, we especially want to review a look at technology trends of the cathode and the separator for lithium-ion battery.

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리튬이온전지 열폭주에 대해 양극활물질이 미치는 영향에 대한 수치해석적 연구 (Numerical analysis on thermal runaway by cathode active materials in lithium-ion batteries)

  • 강명보;김남진
    • 한국지열·수열에너지학회논문집
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    • 제17권2호
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    • pp.1-10
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    • 2021
  • Lithium-ion batteries with high energy density, long cycle life and other advantages, have been widely used to energy storage systems(ESS). But as ESS fires frequently occur, the safety concern has become the main obstacle that hinders the large-scale applications of lithium-ion batteries. Especially, thermal runaway is the key scientific problem in battery safety research. Therefore, in this study, we performed a numerical analysis on the thermal runaway phenomenon of NCM111, NCM523 and NCM622 batteries using a two-dimensional analysis model. The results show that the two-dimensional simulation results are generally matched with three-dimensional simulation. Also, In the case of NCM111 with a low Ni content in the temperature range used in this study, thermal runaway phenomenon does occurred very slowly, but as the Ni content is increased, the thermal runaway phenomenon occurs rapidly and the thermal stability tends to be decreased. And, in NCM523 and NCM622 batteries, chain reactions occur almost simultaneously, but in the case of NCM111 battery, it is found that after the SEI(Solid Electrolyte Interface) layer decomposition reaction, the cathode-electrolyte reaction is appeared sequentially. After that, the anodic decomposition reaction is increased and leads to the thermal runaway reaction.

Design and development of less than 1Kw Lithium rechargeable battery pack

  • Kim, Sang-Bum;Lee, Sang-Hyun
    • International Journal of Internet, Broadcasting and Communication
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    • 제10권3호
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    • pp.104-108
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    • 2018
  • Lithium-ion batteries have been used in energy storage systems (ESS), electric vehicles (EVs), etc. due to their high safety, fast charging and long lifecycle. This paper aims to improve the convenience of users by changing the wired battery stack used in the battery pack, wirelessly using RFID, reducing the internal volume of the battery pack, reducing the size of the battery pack. In this paper, we propose a battery management system which can provide the flexibility of battery pack expansion and maintenance by using lithium ion battery, battery management system (BMS) and wireless communication for light weight of 1Kw small battery pack. Also, by flexibly arranging the cell layout inside the battery pack and designing to reduce the size of the outer shape of the battery pack.

리튬이온 배터리 수명추정을 위한 용량예측 머신러닝 모델의 성능 비교 (Comparison of the Machine Learning Models Predicting Lithium-ion Battery Capacity for Remaining Useful Life Estimation)

  • 유상우;신용범;신동일
    • 한국가스학회지
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    • 제24권6호
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    • pp.91-97
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    • 2020
  • 리튬이온 배터리(LIB)는 다른 배터리에 비해 수명이 길고, 에너지 밀도가 높으며, 자체 방전율이 낮아, 에너지 저장장치(ESS)로 선호되고 있다. 하지만, 2017~2019년 기간 동안 국내에서만도 28건의 화재사고가 발생하였으며, LIB의 운영 중 안전성 및 신뢰성을 보장하기 위해 LIB의 정확한 용량추정은 필수요소이다. 본 연구에서는 LIB의 충방전 cycle에 따른 용량변화를 예측하는 기계학습 기반 모델의 설계에 있어 중요한 요소인 최적 머신러닝 모델의 선정을 위해, Decision Tree, 앙상블학습법, Support Vector Regression, Gaussian Process Regression (GPR) 각각을 이용한 예측모델을 구현하고 성능비교를 실시하였다. 학습을 위해 NASA에서 제공하는 시험데이터를 사용하였으며, GPR이 가장 좋은 예측성능을 보였다. 이를 바탕으로 추가 시험데이터 학습을 통해 개선된 LIB 용량예측과 잔여 수명추정 모델을 개발하여, 운영 중 이상 감지 및 모니터링 성능을 높여, 보다 안전하고 안정된 ESS 운용에 활용하고자 한다.