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With ever increasing grow of inverter-based generation, energy storage systems that can support the grid during load and generation disturbances become vital for stable and resilient operation of the grid. Battery energy storage systems (BESS) are one of the promising candidates to provide grid support during disturbances. Using secondhand batteries which are retired from electric vehicles can alleviate the cost of BESS requirements for grid applications. However, this high number of secondhand batteries have diverse state of the charges (SOCs), which should stay in a predefined range to avoid failure or malfunction of BESS. This article proposes a control scheme for BESS interfaced to a cascaded H-bridge inverter for grid-integration. The proposed scheme is based on a model predictive control (MPC) embedded with coordinated battery cell selection which determines the contribution of each battery to the overall power injection to the grid according to its SOC. The process starts with classification of batteries into subsets according to their SOCs, then sequence matrices are constructed based on the subsets to optimize the power drawn from each cell to comply with battery&#x0027;s SOC. The proposed MPC scheme determines the optimal switching array according to the coordinated battery cells sequence selection. Several experimental case studies are provided that validate the proposed scheme&#x0027;s impact and theoretical expectations. Furthermore, the computational burden and the performance of the proposed scheme are compared with the other algorithms to show the merits of the proposed method.

Optimal Utilization of Battery Sources in Cascaded H-Bridge Inverter by Coordinated Sequence Selection