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A Multi-objective Co-Design Optimization Framework for Grid-Connected Hybrid Battery Energy Storage Systems: Optimal Sizing and Selection of Technology

Abstract : This paper develops a multi-objective co-design optimization framework for the optimal sizing and selection of battery and power electronics in hybrid battery energy storage systems (HBESSs) connected to the grid. The co-design optimization approach is crucial for such a complex system with coupled sub-components. To this end, a non-sorting genetic algorithm (NSGA-II) is used for optimal sizing and selection of technologies in the design of the HBESS, considering design parameters such as cost, efficiency and lifetime. The interoperable framework is applied considering four first- and second-life battery cells technology for forming two independent battery packs as hybrid battery unit and considers two power conversion architectures for interfacing the hybrid battery unit to the grid with different stages and levels of modularity. Finally, the optimized system obtained as output of the framework enables a lifetime improvement of xx% and Total Cost of Ownership (TCO) reduction of xx% compared to the baseline system.
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https://hal-cea.archives-ouvertes.fr/cea-03760400
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Submitted on : Thursday, August 25, 2022 - 11:19:23 AM
Last modification on : Saturday, August 27, 2022 - 3:51:32 AM

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Mahamudul Hasan, Boris Berseneff, Tim Meulenbroeks, Igor Cantero, Sajib Chakraborti, et al.. A Multi-objective Co-Design Optimization Framework for Grid-Connected Hybrid Battery Energy Storage Systems: Optimal Sizing and Selection of Technology. Energies, MDPI, 2022, 2022 (15), pp.5355. ⟨10.3390/en15155355⟩. ⟨cea-03760400⟩

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