A Review of Modeling, Management, and Applications of Grid-Connected Li-Ion Battery Storage Systems

Rouholamini, Mahdi; Wang, Caisheng; Nehrir, Hashem; Hu, Xiaosong; Hu, Zechun; Aki, Hirohisa; Bo, Zhao; Miao, Zhixin; Strunz, Kai

doi:10.1109/tsg.2022.3188598

Cited by 68 publications

(15 citation statements)

References 173 publications

(265 reference statements)

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“…Here, a pulse waveform perturbation V ac,r is added to the voltage reference V dc,r of an interface converter, i.e., buck-boost converter, which results in perturbations appearing on the battery voltage and current. By applying a fast Fourier transform (FFT) analysis, the broadband impedance can be estimated using (2). Based on [207], the same authors further presented a multi-frequency step perturbation scheme [217], which implementation is similar to that in [207].…”

Section: ) Implementation Of Bim Based On Interface Converters A) Bas...mentioning

confidence: 99%

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Power Electronics-Based Safety Enhancement Technologies for Lithium-Ion Batteries: An Overview From Battery Management Perspective

Zhao

et al. 2023

IEEE Trans. Power Electron.

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Safety enhancement for lithium-ion batteries (LIBs) has received a lot of attention from academic and industrial fields. However, there is a lack of overview from the perspective of the application power electronics (PEs) in the systems. This article gives an overview of PE-based safety enhancement technologies for LIBs, mainly focusing on battery management. It introduces the latest advances in battery protection, balancing, monitoring, and lifetime improvement, all based on PE technologies. Detailed discussion and future research opportunities are given. This article aims to provide a reference for PE researchers who want to make some efforts in LIB safety.

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Section: ) Implementation Of Bim Based On Interface Converters A) Bas...mentioning

confidence: 99%

“…ITHIUM-ION batteries (LIBs) have been widely used for energy storage in various applications, such as consumer electronics, electric vehicles (EVs), and energy storage power stations (ESPSs) [1], [2]. However, LIB is sensitive to thermal and electrical stresses.…”

Section: Introductionmentioning

confidence: 99%

Power Electronics-Based Safety Enhancement Technologies for Lithium-Ion Batteries: An Overview From Battery Management Perspective

Zhao

et al. 2023

IEEE Trans. Power Electron.

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“…The intrinsic parameters of the lithium battery energy storage will change. Therefore, it is worthwhile to quantitatively investigate the degradation effect of lithium BESS on the optimal operation of the microgrid [16].…”

Section: A Literature Reviewmentioning

confidence: 99%

Bi-Level Optimizing Model for Microgrids With Fast Lithium Battery Energy Storage Considering Degradation Effect

Wang

et al. 2023

IEEE Access

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The nonlinear degradation effect of the fast lithium battery energy storage system (FLBESS) and the time-scale variability of peak shaving and frequency regulation both make the optimal operation of the microgrid more challenging. Therefore, this paper presents a bi-level optimization model to balance the degradation cost of lithium battery and the benefit of peak shaving and frequency regulation and improve the utilization of FLBESS while dealing with the multiple time scales optimization problems. The upper-level model mainly optimizes the day-ahead hourly power to minimize the power purchase cost and wind and solar power curtailment cost while calculating the internal parameters of the FLBESS to supply the lower-level model for the solution. The lower model optimizes the intra-hour economic cost and coordinates the frequency regulation benefit and lithium battery degradation cost. Finally, case studies are conducted using a regional microgrid to verify that the model solution satisfies the requirements for optimal system operation. In contrast, the model has the advantages of lower economic cost, more significant life extension effect, and higher energy storage utilization rate. The results show that the annual costs were reduced by 14.9%, and the battery life was increased by 19.0% than without considering degradation.INDEX TERMS Fast lithium battery energy storage system, bi-level optimization, nonlinear degradation effect, frequency regulation, multiple time scales. NOMENCLATURE A. ACRONYMS

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“…[1,2] Lithium-ion batteries are widely used as energy supply devices because of their high energy density, high electric potential, and long cycle life. [3][4][5] A battery management system (BMS) can guarantee the safety of lithium-ion batteries in the use process and prolong the service life. [6] Accurate state of charge (SOC) estimation is essential for the charge/discharge control and thermal management of BMS.…”

Section: Introductionmentioning

confidence: 99%

State of Charge Estimation for Lithium‑Ion Batteries Based on Extended Kalman Particle Filter and Orthogonal Optimized Battery Model

Shi,

Zhang,

et al. 2024

Advcd Theory and Sims

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State of charge (SOC) is a key state variable in lithium‑ion battery management system. The battery model and estimation algorithm are important factors that affect the accuracy of SOC estimation. In this paper, the optimization battery model is created by optimizing the hybrid power pulse characteristic (HPPC) parameter combination through orthogonal analysis. The simulation results demonstrate that optimizing the HPPC parameter combinations can improve battery modeling accuracy. Then, an extended Kalman particle filter (EKPF) algorithm is proposed by using the extended Kalman filter (EKF) algorithm as the density function of the particle filter (PF) algorithm. The EKPF algorithm is verified under the dynamic stress test and Beijing bus dynamic stress test conditions, the root mean absolute errors and root mean square errors in all cases are less than 1.5%. The experimental results show that the EKPF algorithm can combine the advantages of EKF and PF to estimate lithium‐ion battery SOC accurately.

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A Review of Modeling, Management, and Applications of Grid-Connected Li-Ion Battery Storage Systems

Cited by 68 publications

References 173 publications

Power Electronics-Based Safety Enhancement Technologies for Lithium-Ion Batteries: An Overview From Battery Management Perspective

Power Electronics-Based Safety Enhancement Technologies for Lithium-Ion Batteries: An Overview From Battery Management Perspective

Bi-Level Optimizing Model for Microgrids With Fast Lithium Battery Energy Storage Considering Degradation Effect

State of Charge Estimation for Lithium‑Ion Batteries Based on Extended Kalman Particle Filter and Orthogonal Optimized Battery Model

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