PhD Forum Abstract: Degradation-Aware Adaptive Design of Multi-Use Battery Energy Storage under Deep Uncertainty

Behind-the-meter battery energy storage systems (BESS) face a tension between expected-cost efficiency and worst-case reliability, compounded by the nonlinear coupling between dispatch and cell degradation. This dissertation develops a degradation-aware, adaptive distributionally robust optimization (DRO) framework for multi-use BESS co-sizing and scheduling under deep uncertainty in load, prices, and aging. Building on a sequence of prior contributions (deterministic MILP, scenario-based SAA), it culminates in a Wasserstein DRO formulation with a physics-based piecewise-linear (PWL) aging surrogate and an explicit resilience recourse. The central claim, that operational resilience can substitute 10–20% of static capacity redundancy at comparable conditional-value-at-risk (CVaR) reliability and lower expected lifecycle cost, is under validation on 2019–2024 German market data.