An Optimal Predictive Control for Maximum Utilization of Heterogeneous Battery Energy Storage System Interfaced Cascaded Multilevel Inverters

This paper proposes a control scheme for optimal selection of switching sequences in cascaded multi-level inverters (CMI) interfaced heterogeneous battery energy storage systems. To ensure energy availability for critical loads and voltage and frequency stability of the futuristic power electronics dominated grids (PEDG)., significant battery energy storage system (BESS) will be required. The exponential increase in the number of electric vehicles (EVs) represents an opportunity to utilize the second-used batteries from EVs for power grid applications. The challenge is the sparse-life of these battery cells and consequently different state of the charge (SOCs) in a string which limits their utilization. This paper leverages the characteristics of CMIs to mitigate the impact of the sparse-life of these battery cells via an optimal predictive control scheme for balancing the power drawn from CMI cells by taking into consideration the SOCs of battery cells. The provided case studies in this paper demonstrate significant improvement in utilization of heterogeneous BESS comparing to state-of-the-art control schemes.