Article
Energy & Fuels
Ariana Ramos, Markku Tuovinen, Mia Ala-Juusela
Summary: Battery Energy Storage Systems (BESS) can serve as a service for final customers, microgrids, and external actors like DSOs and TSOs. Ownership of BESS can vary between the final consumer or a third party, and the key enablers for the service model are regulatory framework that allows stacked revenues and technological interoperability.
JOURNAL OF ENERGY STORAGE
(2021)
Article
Energy & Fuels
Xiwen Liu, Jia Li, Zhuohong Yao, Zhongyan Wang, Ruicai Si, Yunpeng Diao
Summary: The life characteristics of lithium-ion battery were analyzed based on experimental data, with a mathematical model established for predicting the battery's state of health (SOH). The performance parameters of the battery were studied in relation to its life, and the accuracy of the estimation methods was verified.
Article
Energy & Fuels
Davide Fioriti, Claudio Scarpelli, Luigi Pellegrino, Giovanni Lutzemberger, Enrica Micolano, Sara Salamone
Summary: The adoption of electric vehicles is expected to widespread to cope with energy transition needs, but concerns about battery lifetime arise. Based on experimental data, this paper proposes a holistic battery degradation model to accurately account for major determinants of capacity loss. The results show that the expected lifetime of electric vehicles is comparable to that of traditional cars, and the proposed temperature-dependent battery modeling reduces estimation errors up to 27%.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Energy & Fuels
Ruomei Zhou, Rong Zhu, Cheng-Geng Huang, Weiwen Peng
Summary: A novel State of Health (SOH) estimation method for fast-charging batteries is proposed in this study, using incremental capacity (IC) analysis and Gaussian process regression (GPR). The study discusses the aging of batteries under fast-charging conditions, introduces a new feature extracted from IC curves for SOH estimation, and establishes a GPR model trained with extracted features. The proposed method achieves over 90% reduction in mean absolute percentage error on two fast-charging batteries datasets.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Energy & Fuels
Pawan Saini, Lata Gidwani
Summary: In this study, a comprehensive assessment and optimization of battery energy storage system technology is conducted in radial distribution networks using Photovoltaics (PV) output. The goal is to reduce energy losses, dispatch peak power, and control voltage variations. Comparison between PV and PV-BESS is performed for different load models, demonstrating the importance of battery energy storage systems in distribution networks.
JOURNAL OF ENERGY STORAGE
(2022)
Review
Green & Sustainable Science & Technology
Chunyang Zhao, Peter Bach Andersen, Chresten Traeholt, Seyedmostafa Hashemi
Summary: Battery energy storage system (BESS) is widely used in grid services, but a lack of insights into BESS applications and low data transparency limit the understanding of battery usage. This work reviews recent advancements in BESS grid services, describing use cases, hardware features, and proposing a quantitative framework to assess long-term BESS usage patterns. It emphasizes the cross-cutting integration with other components and evaluates the state of charge, state of health, and technical and economic research through a survey of BESS grid applications in the past 10 years. The comprehensive review and analysis provide insights for optimizing battery usage and future application-oriented battery research.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2023)
Article
Energy & Fuels
Mattia Secchi, Grazia Barchi, David Macii, David Moser, Dario Petri
Summary: This paper investigates a bi-objective strategy for optimizing the capacity of Battery Energy Storage Systems (BESSs) for REC prosumers with PV generators, using the Non-dominated Sorting Genetic Algorithm-II (NSGA-II). The strategy aims to maximize self-sufficiency from the main grid while minimizing BESS capacity. Results show that a P2P energy sharing policy slightly outperforms P2G in reducing CO2 emissions, and returns on investment are generally higher with increasing electricity demand.
Article
Energy & Fuels
Sarmad Hanif, M. J. E. Alam, Kini Roshan, Bilal A. Bhatti, Juan C. Bedoya
Summary: This paper presents a multiple grid service procurement and operation approach for battery energy storage systems (BESS), addressing the nonlinearity of BESS services and uncertainty in market forecasts. The proposed framework considers an optimal multi-temporal dimension and has been tested with utility-scale BESS, showing its effectiveness in systematic BESS planning and operation.
Article
Engineering, Electrical & Electronic
Pawan Saini, Lata Gidwani
Summary: This paper presents a multi-objective methodology for BESS allocation in distribution networks, which optimizes BESS investment by combining various benefits. By utilizing a new node voltage sensitivity analysis strategy, the search space for genetic algorithm is reduced, leading to reduction in energy losses, environmental emissions, and improvement in system parameters.
INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
(2021)
Article
Engineering, Electrical & Electronic
Yi Dong, Zhen Dong, Tianqiao Zhao, Zhengtao Ding
Summary: The study formulates the BESS bidding problem as a Markov Decision Process to maximize profit, introducing function approximation technology to handle massive bidding scales and avoid dimension curse. Several case studies demonstrate the effectiveness of the proposed algorithm.
ELECTRIC POWER SYSTEMS RESEARCH
(2021)
Article
Automation & Control Systems
Zhongkai Zhou, Bin Duan, Yongzhe Kang, Yunlong Shang, Qi Zhang, Chenghui Zhang
Summary: In this article, a practical SoH estimation method for LiFePO4 batteries based on Gaussian mixture regression (GMR) and incremental capacity (IC) analysis is proposed. The method achieves high accuracy, high adaptability, and low complexity in estimating the SoH of the batteries.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Chemistry, Multidisciplinary
Chen-Han Wu, Jia-Zhang Jhan, Chih-Han Ko, Cheng-Chien Kuo
Summary: The capacity aging of lithium-ion energy storage systems is inevitable under long-term use, depending on battery usage and the current aging state. Simulation results showed that using higher C-rates and lower SOC levels can lead to higher net profits, and the SOC level of the BESS has a significant impact on the system's lifespan and net income.
APPLIED SCIENCES-BASEL
(2022)
Article
Computer Science, Information Systems
Mohammadreza Gholami, Soad Abokhamis Mousavi, S. M. Muyeen
Summary: This study aims to improve the reliability of microgrids by finding the optimal size and type of battery energy storage systems (BESSs). Various factors of the BESS, such as rated power, power cost, discharge time, efficiency, and life cycle, as well as power exchange limitations with the main grid, are considered. The results show that utilizing BESS can significantly improve the expected energy not supplied (EENS) of both islanded and grid-connected microgrids with power exchange limitations.
Article
Energy & Fuels
Charles C. Okaeme, Chuanbo Yang, Aron Saxon, Jason A. Lustbader, Darek Villeneuve, Chihao Mac, Thomas Reed
Summary: This paper presents a systematic thermal management analysis for a new lithium-titanate-oxide battery pack installed in a hybrid truck. By conducting thermal and electrical characterization tests and developing computational models, the authors achieve a final battery pack design that ensures sufficient cooling and temperature uniformity. They also develop a reduced-order electrothermal model for predicting battery performance and temperature control.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Automation & Control Systems
Tianmu Chen, Guohong Zeng, Long Jing, Sirui Wang, Weige Zhang
Summary: This article proposes a current ripple mitigation strategy for MDC battery energy storage system, based on harmonic model analysis using Fourier series. By simultaneously varying duties and phase-shifted angles, multiple current harmonics are eliminated. The feasibility and effectiveness of the proposed modulation method are verified through experimental results on a four-unit MDC.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Computer Science, Information Systems
Matthieu Dubarry, George Baure
Article
Energy & Fuels
George Baure, Matthieu Dubarry
Article
Chemistry, Physical
D. Ansean, G. Baure, M. Gonzalez, I Camean, A. B. Garcia, M. Dubarry
JOURNAL OF POWER SOURCES
(2020)
Article
Energy & Fuels
George Baure, Matthieu Dubarry
JOURNAL OF ENERGY STORAGE
(2020)
Article
Energy & Fuels
Matthieu Dubarry, David Beck
Summary: This study introduces improved datasets for three major battery chemistries, which can be utilized for statistical or deep learning methods, along with a detailed statistical analysis. By incorporating the combined information of three learnable parameters, accurate diagnosis and early prognosis comparable to state of the art, while providing physical interpretability, were demonstrated.
Review
Energy & Fuels
David Beck, Philipp Dechent, Mark Junker, Dirk Uwe Sauer, Matthieu Dubarry
Summary: Battery degradation is a major concern in battery research, with challenges in maintaining performance and safety during usage. Variations and inhomogeneities between cells can have significant impacts on electrochemical performance, and various methods are used to characterize and track these effects.
Review
Electrochemistry
Peter M. Attia, Alexander Bills, Ferran Brosa Planella, Philipp Dechent, Goncalo dos Reis, Matthieu Dubarry, Paul Gasper, Richard Gilchrist, Samuel Greenbank, David Howey, Ouyang Liu, Edwin Khoo, Yuliya Preger, Abhishek Soni, Shashank Sripad, Anna G. Stefanopoulou, Valentin Sulzer
Summary: This article reviews the phenomenon of "knees" in the aging trajectories of lithium-ion batteries and discusses their pathways, key design and usage sensitivities, as well as the challenges and opportunities for knee modeling and prediction.
JOURNAL OF THE ELECTROCHEMICAL SOCIETY
(2022)
Article
Energy & Fuels
N. Costa, L. Sanchez, D. Ansean, M. Dubarry
Summary: This study proposes a new method for battery degradation diagnosis based on the representation of battery data as images. Experimental results show that this method outperforms current methodologies in accuracy and is adaptable to different types of batteries.
JOURNAL OF ENERGY STORAGE
(2022)
Article
Chemistry, Physical
Matthieu Dubarry, David Howey, Billy Wu
Summary: Digital twins are cyber-physical systems that integrate real-time sensor data and models for accurate predictions and optimal decisions in specific assets. In the case of batteries, this concept has been applied at different scales. However, a comprehensive approach is needed for battery digital twins to achieve their full potential in industrial settings. Standardized and transparent data sharing, as well as principled methods to quantify and propagate uncertainty, are essential. Physical modeling and sensing approaches for battery manufacturing and thermal runaway also need improvement.
Article
Electrochemistry
Matthieu Dubarry, Vishal Agrawal, Martin Hueske, Matthias Kuipers
Summary: In the past fifteen years, multiple mechanistic model frameworks have been developed to quantify the loss of lithium inventory and active materials. These frameworks usually involve capacity/state of charge or lithiation-based matching for the electrodes. However, this study reveals that when applied to materials that are not fully delithiated, these approaches are not equivalent due to their different treatment of inaccessible lithium. This article explains the discrepancies and proposes new equations to enhance both types of frameworks.
JOURNAL OF THE ELECTROCHEMICAL SOCIETY
(2023)
Article
Multidisciplinary Sciences
Matthieu Dubarry, Nahuel Costa, Dax Matthews
Summary: To address the challenge of diagnosing photovoltaics-connected Li-ion batteries, the authors propose a diagnostic methodology that utilizes machine learning algorithms trained on data from the photovoltaic charging process. This approach effectively reduces the diagnostic error by directly utilizing the data from the charging process.
NATURE COMMUNICATIONS
(2023)
Article
Electrochemistry
Matthieu Dubarry, Fahim Yasir, Nahuel Costa, Dax Matthews
Summary: This work presents a new methodology for diagnosing PV-connected batteries without the need for maintenance cycles. It uses a 1-dimensional convolutional neural network trained on clear sky irradiance model output and validated on observed irradiances for synthetic battery data. The analysis covers sky conditions, degradation composition, and degradation extent. Results show that diagnosis with an average RMSE of 1.75% is achievable for days with over 50% clear sky or average irradiance over 650 W/m(2), regardless of degradation composition and extent.
Article
Chemistry, Multidisciplinary
Matthieu Dubarry, David Beck
Summary: The mechanistic modeling approach has gained significant traction in the field of lithium-ion battery diagnosis and prognosis in the past decade. It relies on assembling digital twins to replicate the degradation modes and enables material-based diagnosis and prognosis without the need for complex models. This approach has proven to be versatile and effective in studying degradation mechanisms and predicting battery performance.
ACCOUNTS OF MATERIALS RESEARCH
(2022)