Optimal market-aware scheduling and control of EV batteries in second-life usage

As the share of renewable energy in power systems increases, the resulting need for additional flexibility can be supported by second-life battery energy storage systems. However, their operation is complicated by the heterogeneity of the constituent battery packs. This paper addresses this challenge by proposing an optimization framework that uses battery packs’ losses as a proxy for battery degradation. The proposed two-stage framework (i) optimizes the participation of multiple second-life battery packs, each connected to its own DC/DC converter, in the Frequency Containment Reserve and day-ahead markets, while enforcing a specific constraint to ensure homogeneous degradation of each pack, and (ii) employs a model predictive control-based convex optimization to track market commitments while equalizing resistive losses among the batteries. The framework is validated in simulation across three scenarios with varying initial conditions, demonstrating effectiveness in balancing performance and degradation among heterogeneous battery packs.