IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v367y2024ics0306261924008559.html
   My bibliography  Save this article

Incorporating FFTA based safety assessment of lithium-ion battery energy storage systems in multi-objective optimization for integrated energy systems

Author

Listed:
  • Tan, Jiawei
  • Chen, Xingyu
  • Bu, Yang
  • Wang, Feng
  • Wang, Jialing
  • Huang, Xianan
  • Hu, Zhenda
  • Liu, Lin
  • Lin, Changzhui
  • Meng, Chao
  • Lin, Jian
  • Xie, Shan
  • Xu, Jinmei
  • Jing, Rui
  • Zhao, Yingru

Abstract

Lithium-ion Battery Energy Storage Systems (BESS) have been widely adopted in energy systems due to their many advantages. However, the high energy density and thermal stability issues associated with lithium-ion batteries have led to a rise in BESS-related safety incidents, which often bring about severe casualties and property losses. To accurately evaluate the safety of lithium-ion BESS, this study proposes a probabilistic risk assessment method (PRA) that incorporates fuzzy fault tree analysis (FFTA) with expert knowledge aggregation. This approach takes into account the impact of BESS design variations and provides risk probability estimates for safety incidents in BESS. Based on the risk assessment, an energy system design framework is developed. This framework introduces a quantified risk indicator for BESS and establishes a mixed integer linear programming (MILP) model to examine the implications of BESS design on self-safety, as well as its interactive effects on the economics of integrated energy systems (IES). A case study conducted in an industrial park in Ningde, China, demonstrates that differences in safety requirements from investors can lead to cost variations of up to 6.8%. Furthermore, the study reveals the deep coupling between the safety and economics of BESS, highlighting that a cost-optimal approach which neglects safety can result in a 4.5% increase in the probability of BESS safety incident risk compared to a safety-optimal approach. Overall, this study contributes to the understanding of the interplay between safety and economics in BESS design. By employing a combination of quantitative evaluation and mathematical optimization methods, the present study provides a rational and feasible strategy, as well as a modeling perspective, for the safety design of BESS, paving the way for safer and more efficient integration of BESS in integrated energy systems.

Suggested Citation

  • Tan, Jiawei & Chen, Xingyu & Bu, Yang & Wang, Feng & Wang, Jialing & Huang, Xianan & Hu, Zhenda & Liu, Lin & Lin, Changzhui & Meng, Chao & Lin, Jian & Xie, Shan & Xu, Jinmei & Jing, Rui & Zhao, Yingru, 2024. "Incorporating FFTA based safety assessment of lithium-ion battery energy storage systems in multi-objective optimization for integrated energy systems," Applied Energy, Elsevier, vol. 367(C).
    • Handle: RePEc:eee:appene:v:367:y:2024:i:c:s0306261924008559
    DOI: 10.1016/j.apenergy.2024.123472
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261924008559
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2024.123472?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Maximilian Hoffmann & Leander Kotzur & Detlef Stolten & Martin Robinius, 2020. "A Review on Time Series Aggregation Methods for Energy System Models," Energies, MDPI, vol. 13(3), pages 1-61, February.
    2. Huixing Meng & Qiaoqiao Yang & Enrico Zio & Jinduo Xing, 2023. "An integrated methodology for dynamic risk prediction of thermal runaway in lithium-ion batteries," Post-Print hal-04103786, HAL.
    3. Jing, Rui & Kuriyan, Kamal & Kong, Qingyuan & Zhang, Zhihui & Shah, Nilay & Li, Ning & Zhao, Yingru, 2019. "Exploring the impact space of different technologies using a portfolio constraint based approach for multi-objective optimization of integrated urban energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    4. Wang, Guotao & Zhou, Yifan & Lin, Zhenjia & Zhu, Shibo & Qiu, Rui & Chen, Yuntian & Yan, Jinyue, 2024. "Robust energy management through aggregation of flexible resources in multi-home micro energy hub," Applied Energy, Elsevier, vol. 357(C).
    5. O. Schmidt & A. Hawkes & A. Gambhir & I. Staffell, 2017. "The future cost of electrical energy storage based on experience rates," Nature Energy, Nature, vol. 2(8), pages 1-8, August.
    6. Fang Yan & Kaili Xu & Xiwen Yao & Yang Li, 2016. "Fuzzy Bayesian Network-Bow-Tie Analysis of Gas Leakage during Biomass Gasification," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-21, July.
    7. Kachirayil, Febin & Weinand, Jann Michael & Scheller, Fabian & McKenna, Russell, 2022. "Reviewing local and integrated energy system models: insights into flexibility and robustness challenges," Applied Energy, Elsevier, vol. 324(C).
    8. Zhou, Zhizuan & Li, Maoyu & Zhou, Xiaodong & Ju, Xiaoyu & Yang, Lizhong, 2023. "Investigating thermal runaway characteristics and trigger mechanism of the parallel lithium-ion battery," Applied Energy, Elsevier, vol. 349(C).
    9. A. Stephan & B. Battke & M. D. Beuse & J. H. Clausdeinken & T. S. Schmidt, 2016. "Limiting the public cost of stationary battery deployment by combining applications," Nature Energy, Nature, vol. 1(7), pages 1-9, July.
    10. Hong, Bingyuan & Shao, Bowen & Guo, Jian & Fu, Jianzhong & Li, Cuicui & Zhu, Baikang, 2023. "Dynamic Bayesian network risk probability evolution for third-party damage of natural gas pipelines," Applied Energy, Elsevier, vol. 333(C).
    11. Huang, Zonghou & Liu, Jialong & Zhai, Hongju & Wang, Qingsong, 2021. "Experimental investigation on the characteristics of thermal runaway and its propagation of large-format lithium ion batteries under overcharging and overheating conditions," Energy, Elsevier, vol. 233(C).
    12. Yael Parag & Benjamin K. Sovacool, 2016. "Electricity market design for the prosumer era," Nature Energy, Nature, vol. 1(4), pages 1-6, April.
    13. He, Gang & Lin, Jiang & Sifuentes, Froylan & Liu, Xu & Abhyankar, Nikit & Phadke, Amol, 2020. "Author Correction: Rapid cost decrease of renewables and storage accelerates the decarbonization of China’s power system," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt11x8b9hc, Department of Agricultural & Resource Economics, UC Berkeley.
    14. Jing, Rui & Hua, Weiqi & Lin, Jian & Lin, Jianyi & Zhao, Yingru & Zhou, Yue & Wu, Jianzhong, 2022. "Cost-efficient decarbonization of local energy systems by whole-system based design optimization," Applied Energy, Elsevier, vol. 326(C).
    15. Gang He & Jiang Lin & Froylan Sifuentes & Xu Liu & Nikit Abhyankar & Amol Phadke, 2020. "Rapid cost decrease of renewables and storage accelerates the decarbonization of China’s power system," Nature Communications, Nature, vol. 11(1), pages 1-9, December.
    16. Si, Fangyuan & Wang, Jinkuan & Han, Yinghua & Zhao, Qiang & Han, Peng & Li, Yan, 2018. "Cost-efficient multi-energy management with flexible complementarity strategy for energy internet," Applied Energy, Elsevier, vol. 231(C), pages 803-815.
    17. Said, Ahmed O. & Lee, Christopher & Stoliarov, Stanislav I. & Marshall, André W., 2019. "Comprehensive analysis of dynamics and hazards associated with cascading failure in 18650 lithium ion cell arrays," Applied Energy, Elsevier, vol. 248(C), pages 415-428.
    18. Lei, Zijian & Yu, Hao & Li, Peng & Ji, Haoran & Yan, Jinyue & Song, Guanyu & Wang, Chengshan, 2024. "A compact time horizon compression method for planning community integrated energy systems with long-term energy storage," Applied Energy, Elsevier, vol. 361(C).
    19. Mirshekali, Hamid & Mortensen, Lasse Kappel & Shaker, Hamid Reza, 2024. "Reliability-aware multi-objective approach for predictive asset management: A Danish distribution grid case study," Applied Energy, Elsevier, vol. 358(C).
    20. Gabrielli, Paolo & Fürer, Florian & Mavromatidis, Georgios & Mazzotti, Marco, 2019. "Robust and optimal design of multi-energy systems with seasonal storage through uncertainty analysis," Applied Energy, Elsevier, vol. 238(C), pages 1192-1210.
    21. Yunusov, Timur & Frame, Damien & Holderbaum, William & Potter, Ben, 2016. "The impact of location and type on the performance of low-voltage network connected battery energy storage systems," Applied Energy, Elsevier, vol. 165(C), pages 202-213.
    22. Mallapragada, Dharik S. & Sepulveda, Nestor A. & Jenkins, Jesse D., 2020. "Long-run system value of battery energy storage in future grids with increasing wind and solar generation," Applied Energy, Elsevier, vol. 275(C).
    23. Stephen Comello & Stefan Reichelstein, 2019. "The emergence of cost effective battery storage," Nature Communications, Nature, vol. 10(1), pages 1-9, December.
    24. Gang He & Jiang Lin & Froylan Sifuentes & Xu Liu & Nikit Abhyankar & Amol Phadke, 2020. "Author Correction: Rapid cost decrease of renewables and storage accelerates the decarbonization of China’s power system," Nature Communications, Nature, vol. 11(1), pages 1-1, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lingzhi Wang & Yang Bu & Yichun Wu, 2024. "Multi-Scale Risk-Informed Comprehensive Assessment Methodology for Lithium-Ion Battery Energy Storage System," Sustainability, MDPI, vol. 16(20), pages 1-24, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ma, Huan & Sun, Qinghan & Chen, Lei & Chen, Qun & Zhao, Tian & He, Kelun & Xu, Fei & Min, Yong & Wang, Shunjiang & Zhou, Guiping, 2023. "Cogeneration transition for energy system decarbonization: From basic to flexible and complementary multi-energy sources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 187(C).
    2. Hetong Wang & Kuishuang Feng & Peng Wang & Yuyao Yang & Laixiang Sun & Fan Yang & Wei-Qiang Chen & Yiyi Zhang & Jiashuo Li, 2023. "China’s electric vehicle and climate ambitions jeopardized by surging critical material prices," Nature Communications, Nature, vol. 14(1), pages 1-13, December.
    3. Wang, Yadong & Wang, Delu & Shi, Xunpeng, 2023. "Sustainable development pathways of China's wind power industry under uncertainties: Perspective from economic benefits and technical potential," Energy Policy, Elsevier, vol. 182(C).
    4. Schauf, Magnus & Schwenen, Sebastian, 2023. "System price dynamics for battery storage," Energy Policy, Elsevier, vol. 183(C).
    5. Natalia Gonzalez & Paul Serna-Torre & Pedro A. Sánchez-Pérez & Ryan Davidson & Bryan Murray & Martin Staadecker & Julia Szinai & Rachel Wei & Daniel M. Kammen & Deborah A. Sunter & Patricia Hidalgo-Go, 2024. "Offshore wind and wave energy can reduce total installed capacity required in zero-emissions grids," Nature Communications, Nature, vol. 15(1), pages 1-16, December.
    6. Yu, Zhongjue & Geng, Yong & Calzadilla, Alvaro & Bleischwitz, Raimund, 2022. "China's unconventional carbon emissions trading market: The impact of a rate-based cap in the power generation sector," Energy, Elsevier, vol. 255(C).
    7. Liqun Peng & Denise L. Mauzerall & Yaofeng D. Zhong & Gang He, 2023. "Heterogeneous effects of battery storage deployment strategies on decarbonization of provincial power systems in China," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
    8. Francesca Andreolli & Chiara D'Alpaos & Peter Kort, 2023. "Does P2P Trading Favor Investments in PV-Battery Systems?," Working Papers 2023.02, Fondazione Eni Enrico Mattei.
    9. Sánchez-Pérez, P.A. & Staadecker, Martin & Szinai, Julia & Kurtz, Sarah & Hidalgo-Gonzalez, Patricia, 2022. "Effect of modeled time horizon on quantifying the need for long-duration storage," Applied Energy, Elsevier, vol. 317(C).
    10. Jing, Rui & Li, Yubing & Wang, Meng & Chachuat, Benoit & Lin, Jianyi & Guo, Miao, 2021. "Coupling biogeochemical simulation and mathematical optimisation towards eco-industrial energy systems design," Applied Energy, Elsevier, vol. 290(C).
    11. Zhenyu Zhuo & Ershun Du & Ning Zhang & Chris P. Nielsen & Xi Lu & Jinyu Xiao & Jiawei Wu & Chongqing Kang, 2022. "Cost increase in the electricity supply to achieve carbon neutrality in China," Nature Communications, Nature, vol. 13(1), pages 1-13, December.
    12. Shi, Zhengkun & Yang, Yongbiao & Xu, Qingshan & Wu, Chenyu & Hua, Kui, 2023. "A low-carbon economic dispatch for integrated energy systems with CCUS considering multi-time-scale allocation of carbon allowance," Applied Energy, Elsevier, vol. 351(C).
    13. Kalkbrenner, Bernhard J., 2019. "Residential vs. community battery storage systems – Consumer preferences in Germany," Energy Policy, Elsevier, vol. 129(C), pages 1355-1363.
    14. Parra, David & Mauger, Romain, 2022. "A new dawn for energy storage: An interdisciplinary legal and techno-economic analysis of the new EU legal framework," Energy Policy, Elsevier, vol. 171(C).
    15. Rahman, Arief & Richards, Russell & Dargusch, Paul & Wadley, David, 2023. "Pathways to reduce Indonesia’s dependence on oil and achieve longer-term decarbonization," Renewable Energy, Elsevier, vol. 202(C), pages 1305-1323.
    16. Englberger, Stefan & Abo Gamra, Kareem & Tepe, Benedikt & Schreiber, Michael & Jossen, Andreas & Hesse, Holger, 2021. "Electric vehicle multi-use: Optimizing multiple value streams using mobile storage systems in a vehicle-to-grid context," Applied Energy, Elsevier, vol. 304(C).
    17. Elkadeem, Mohamed R. & Younes, Ali & Mazzeo, Domenico & Jurasz, Jakub & Elia Campana, Pietro & Sharshir, Swellam W. & Alaam, Mohamed A., 2022. "Geospatial-assisted multi-criterion analysis of solar and wind power geographical-technical-economic potential assessment," Applied Energy, Elsevier, vol. 322(C).
    18. Sun, Ya-Fang & Zhang, Yue-Jun & Su, Bin, 2022. "How does global transport sector improve the emissions reduction performance? A demand-side analysis," Applied Energy, Elsevier, vol. 311(C).
    19. Kuang, Zhonghong & Chen, Qi & Yu, Yang, 2022. "Assessing the CO2-emission risk due to wind-energy uncertainty," Applied Energy, Elsevier, vol. 310(C).
    20. Li, Xiao & Liu, Pan & Feng, Maoyuan & Jordaan, Sarah M. & Cheng, Lei & Ming, Bo & Chen, Jie & Xie, Kang & Liu, Weibo, 2024. "Energy transition paradox: Solar and wind growth can hinder decarbonization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:367:y:2024:i:c:s0306261924008559. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.