Optimal Hierarchical Management of Shipboard Multibattery Energy Storage System Using a Data-Driven Degradation Model

The lifetime of shipboard energy storage systems (ESSs) has great impacts on the operating cost of all-electric ships (AESs) since their high investment costs. Additionally, those ESSs are designed to have multiple battery packs with high capacity redundancy to cope with various navigation scenarios and distributed in different electric zones onboard to avoid operating risks. To extend the battery lifetime while fully addressing the redundant capacity and distributed locations, an optimal hierarchical management model for shipboard multibattery ESS is proposed, which consists of three levels. In the first level, a practical quadratic degradation cost model is reformulated from a nonlinear data-driven model, which considers both the depth of discharge (DoD) and mean state of charge (MSOC). Then, in the second level, the obtained quadratic model is implemented into the shipboard generation scheduling that views the multibattery ESS as a "single battery pack. "In the third level, a multibattery management strategy is implemented to split the "single battery pack's" power to each battery group by iteratively limiting their MSOCs. To bring the proposed energy management method into practical usage, a real-time simulation experiment is designed to test its validity. The case study shows that the proposed method is suitable for real-time usage and reveals that iteratively regulating the MSOC of batteries will greatly facilitate their lifetime. As a result, the operating cost of AESs can be reduced due to battery lifetime extension.