Lithium-Ion (Li-Ion) batteries are widely used for energy storage applications in microgrids systems. A real time estimation of static and dynamic conditions of the battery pack, such as the remaining capacity or the aging effects, is fundamental for these applications, where it is necessary to ensure stability and reliability in the power supply. Since the internal state of each cell cannot be directly measured, a model-based estimation algorithm has to be implemented to further describe the performance of the whole battery pack. This work proposes a simplified version of the equivalent circuit model capable of describing the behavior of Battery Energy Storage Systems (BESS) for microgrid applications. To create an accurate model based on experimental data, data relating to different Lithium technologies of storage systems located in ENEA Research Centre Casaccia were collected. Each BESS was subjected to discharge cycles operating at variable C-Rate, in order to carry out the same parameters identification process and analyze the behavior of the different technologies. The results demonstrate that the electrical parameters obtained for a specific C-rate and for the same BESS technology can be used for discharges carried out at the same power but on different days, showing a robustness of the proposed model in terms of reduced RMSE between the experimental and the simulated curves.

Lucaferri, V., Valentini, M., De Lia, F., Laudani, A., Presti, R.L., Schioppo, R., et al. (2023). Modeling and optimization method for Battery Energy Storage Systems operating at variable C-rate: A comparative study of Lithium technologies. JOURNAL OF ENERGY STORAGE, 73, 109232 [10.1016/j.est.2023.109232].

Modeling and optimization method for Battery Energy Storage Systems operating at variable C-rate: A comparative study of Lithium technologies

Riganti Fulginei F.
2023-01-01

Abstract

Lithium-Ion (Li-Ion) batteries are widely used for energy storage applications in microgrids systems. A real time estimation of static and dynamic conditions of the battery pack, such as the remaining capacity or the aging effects, is fundamental for these applications, where it is necessary to ensure stability and reliability in the power supply. Since the internal state of each cell cannot be directly measured, a model-based estimation algorithm has to be implemented to further describe the performance of the whole battery pack. This work proposes a simplified version of the equivalent circuit model capable of describing the behavior of Battery Energy Storage Systems (BESS) for microgrid applications. To create an accurate model based on experimental data, data relating to different Lithium technologies of storage systems located in ENEA Research Centre Casaccia were collected. Each BESS was subjected to discharge cycles operating at variable C-Rate, in order to carry out the same parameters identification process and analyze the behavior of the different technologies. The results demonstrate that the electrical parameters obtained for a specific C-rate and for the same BESS technology can be used for discharges carried out at the same power but on different days, showing a robustness of the proposed model in terms of reduced RMSE between the experimental and the simulated curves.
2023
Lucaferri, V., Valentini, M., De Lia, F., Laudani, A., Presti, R.L., Schioppo, R., et al. (2023). Modeling and optimization method for Battery Energy Storage Systems operating at variable C-rate: A comparative study of Lithium technologies. JOURNAL OF ENERGY STORAGE, 73, 109232 [10.1016/j.est.2023.109232].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11590/456287
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