A multi-year stochastic optimization model for battery system design and operation: addressing uncertainties alongside degradation effects

Distributed PV-battery systems offer a promising solution to enhance energy self-consumption and demand self-sufficiency. However, uncertainties in techno-economic parameters battery degradation, and computational inefficiencies in existing models affect their design and operation. Therefore, this study proposes a two-stage stochastic optimization framework that integrates a multiyear financial model with battery degredation model to optimize the sizing and operation of PV-battery systems.

The framework incorporates uncertainties through Monte Carlo simulation and scenario reduction techniques. The stochastic solution increases the optimal battery capacity by 12.4% compared to the deterministic approach, ensuring more reliable system performance.