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Long-term degradation based analysis for lithium-ion batteries in off-grid wind-battery renewable energy systems

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  • Ghorbanzadeh, Milad
  • Astaneh, Majid
  • Golzar, Farzin

Abstract

This work presents a mathematical framework for calculating Li-ion batteries useful life by coupling electrochemical and thermal aging models. The model takes into account the impact of operating conditions of real wind-battery power stations including charge/discharge profiles and control strategies to predict battery degradation over time. The model estimates battery end of discharge capacity with a RRSME of 1.1% in comparison with experimental data. In addition, the maximum relative error to predict battery voltage in the plateau region of charge/discharge curves is 1.3%. Results show a remarkable impact of operating conditions on battery bank lifetime. Analyzing different case studies predicts a wide range of 4.6–11.6 years for battery longevity. Moreover, the model shows that controlling the maximum allowed battery state of charge set point improves battery bank lifetime up to 63%. Hence, the proposed model is a powerful decision support tool to evaluate the impact of off-grid wind-battery systems operating conditions on the battery lifetime.

Suggested Citation

  • Ghorbanzadeh, Milad & Astaneh, Majid & Golzar, Farzin, 2019. "Long-term degradation based analysis for lithium-ion batteries in off-grid wind-battery renewable energy systems," Energy, Elsevier, vol. 166(C), pages 1194-1206.
    • Handle: RePEc:eee:energy:v:166:y:2019:i:c:p:1194-1206
    DOI: 10.1016/j.energy.2018.10.120
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    as
    1. San Martín, Idoia & Berrueta, Alberto & Sanchis, Pablo & Ursúa, Alfredo, 2018. "Methodology for sizing stand-alone hybrid systems: A case study of a traffic control system," Energy, Elsevier, vol. 153(C), pages 870-881.
    2. Jaiswal, Abhishek, 2017. "Lithium-ion battery based renewable energy solution for off-grid electricity: A techno-economic analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 922-934.
    3. Dufo-López, Rodolfo & Cristóbal-Monreal, Iván R. & Yusta, José M., 2016. "Optimisation of PV-wind-diesel-battery stand-alone systems to minimise cost and maximise human development index and job creation," Renewable Energy, Elsevier, vol. 94(C), pages 280-293.
    4. Diouf, Boucar & Pode, Ramchandra, 2015. "Potential of lithium-ion batteries in renewable energy," Renewable Energy, Elsevier, vol. 76(C), pages 375-380.
    5. Ning, Bo & Cao, Binggang & Wang, Bin & Zou, Zhongyue, 2018. "Adaptive sliding mode observers for lithium-ion battery state estimation based on parameters identified online," Energy, Elsevier, vol. 153(C), pages 732-742.
    6. Cai, Yishan & Yang, Lin & Deng, Zhongwei & Zhao, Xiaowei & Deng, Hao, 2018. "Online identification of lithium-ion battery state-of-health based on fast wavelet transform and cross D-Markov machine," Energy, Elsevier, vol. 147(C), pages 621-635.
    7. Lujano-Rojas, Juan M. & Monteiro, Cláudio & Dufo-López, Rodolfo & Bernal-Agustín, José L., 2012. "Optimum load management strategy for wind/diesel/battery hybrid power systems," Renewable Energy, Elsevier, vol. 44(C), pages 288-295.
    8. Berrueta, Alberto & Urtasun, Andoni & Ursúa, Alfredo & Sanchis, Pablo, 2018. "A comprehensive model for lithium-ion batteries: From the physical principles to an electrical model," Energy, Elsevier, vol. 144(C), pages 286-300.
    9. Lau, K.Y. & Yousof, M.F.M. & Arshad, S.N.M. & Anwari, M. & Yatim, A.H.M., 2010. "Performance analysis of hybrid photovoltaic/diesel energy system under Malaysian conditions," Energy, Elsevier, vol. 35(8), pages 3245-3255.
    10. Zheng, Linfeng & Zhu, Jianguo & Lu, Dylan Dah-Chuan & Wang, Guoxiu & He, Tingting, 2018. "Incremental capacity analysis and differential voltage analysis based state of charge and capacity estimation for lithium-ion batteries," Energy, Elsevier, vol. 150(C), pages 759-769.
    11. Uddin, Kotub & Gough, Rebecca & Radcliffe, Jonathan & Marco, James & Jennings, Paul, 2017. "Techno-economic analysis of the viability of residential photovoltaic systems using lithium-ion batteries for energy storage in the United Kingdom," Applied Energy, Elsevier, vol. 206(C), pages 12-21.
    12. Holger C. Hesse & Rodrigo Martins & Petr Musilek & Maik Naumann & Cong Nam Truong & Andreas Jossen, 2017. "Economic Optimization of Component Sizing for Residential Battery Storage Systems," Energies, MDPI, vol. 10(7), pages 1-19, June.
    13. Deng, Zhongwei & Deng, Hao & Yang, Lin & Cai, Yishan & Zhao, Xiaowei, 2017. "Implementation of reduced-order physics-based model and multi-parameters identification strategy for lithium-ion battery," Energy, Elsevier, vol. 138(C), pages 509-519.
    14. Dufo-López, Rodolfo & Cristóbal-Monreal, Iván R. & Yusta, José M., 2016. "Stochastic-heuristic methodology for the optimisation of components and control variables of PV-wind-diesel-battery stand-alone systems," Renewable Energy, Elsevier, vol. 99(C), pages 919-935.
    15. Holger C. Hesse & Michael Schimpe & Daniel Kucevic & Andreas Jossen, 2017. "Lithium-Ion Battery Storage for the Grid—A Review of Stationary Battery Storage System Design Tailored for Applications in Modern Power Grids," Energies, MDPI, vol. 10(12), pages 1-42, December.
    16. Saevarsdottir, Gudrun & Tao, Pai-chun & Stefansson, Hlynur & Harvey, William, 2014. "Potential use of geothermal energy sources for the production of lithium-ion batteries," Renewable Energy, Elsevier, vol. 61(C), pages 17-22.
    17. Dali, Mehdi & Belhadj, Jamel & Roboam, Xavier, 2010. "Hybrid solar–wind system with battery storage operating in grid-connected and standalone mode: Control and energy management – Experimental investigation," Energy, Elsevier, vol. 35(6), pages 2587-2595.
    18. Uddin, Kotub & Jackson, Tim & Widanage, Widanalage D. & Chouchelamane, Gael & Jennings, Paul A. & Marco, James, 2017. "On the possibility of extending the lifetime of lithium-ion batteries through optimal V2G facilitated by an integrated vehicle and smart-grid system," Energy, Elsevier, vol. 133(C), pages 710-722.
    19. Krieger, Elena M. & Cannarella, John & Arnold, Craig B., 2013. "A comparison of lead-acid and lithium-based battery behavior and capacity fade in off-grid renewable charging applications," Energy, Elsevier, vol. 60(C), pages 492-500.
    20. Dufo-López, Rodolfo & Lujano-Rojas, Juan M. & Bernal-Agustín, José L., 2014. "Comparison of different lead–acid battery lifetime prediction models for use in simulation of stand-alone photovoltaic systems," Applied Energy, Elsevier, vol. 115(C), pages 242-253.
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