Planning Future Microgrids with Second-Life Batteries: A Degradation-Aware Iterative Optimization Framework

Abstract

The growing availability of second-life batteries (SLBs) from electric vehicles is reshaping future microgrid design, requiring planning frameworks that explicitly account for reduced capacity and efficiency over time. However, traditional microgrid planning models often neglect degradation effects or rely on highly simplified formulations, leading to unreliable sizing decisions and increased long-term costs. This paper proposes a degradation-aware iterative optimization framework for long-term microgrid planning that incorporates photovoltaic efficiency fading, battery capacity and efficiency degradation, and SLB characteristics. A cumulative multi-year optimization model is first solved to obtain an initial investment and operational strategy under simplified degradation assumptions, ensuring computational tractability. Subsequently, a yearly validation model evaluates degradation impacts on photovoltaic and battery assets, updating efficiencies and available capacity to assess reliability. An iterative refinement process then adjusts resource allocation to eliminate load shedding while minimizing total system cost. Sensitivity analyses on photovoltaic degradation rates, SLB capital costs, and grid tariffs are conducted to evaluate robustness under varying technical and economic conditions. Results demonstrate that neglecting degradation can compromise reliability and increase blackout risk, while SLBs offer meaningful cost-saving opportunities. The proposed framework provides a scalable and practical tool for planning future microgrids in degradation-constrained environments.