Algorithms to optimize the state of charge to enhance battery lifespan while maintaining grid reliability and stability

Abstract

With the widespread use of renewable energy, battery energy storage systems (BESS) are playing an increasingly important role in smart grids. However, frequent cycling accelerates capacity decay and internal resistance growth, directly reduces battery remaining useful life (RUL) and system efficiency. This thesis focuses on the battery management systems and aims to investigate the battery characteristics by using electrochemical aging and thermal models. Besides, this thesis aims to develop an optimized battery management strategy that enhances both battery lifespan and grid stability, and it formulated multi-objective optimization functions considering battery degradation, grid reliability and operational costs. The proposed algorithm incorporates critical grid stability parameters, particularly grid frequency regulation, to establish a robust battery management framework. The methodology demonstrates improved sustainability in energy storage operations while providing a technical foundation for efficient management in the future smart grid implementations.