This paper presents an aging-aware controller for photovoltaic (PV) battery systems aimed at mitigating battery degradation to enhance the operational lifespan and economic viability of energy storage systems. The study involves a one-year simulation of an optimization-based home energy management system (HEMS) utilizing the DESO optimization algorithm, grounded in Stochastic Dynamic Programming (SDP). The HEMS balances power flow among PV systems, hybrid energy storage systems (HESS), consumers, and the grid.
The research incorporates a well-established empirical battery aging model for nickel manganese cobalt (NMC) batteries, allowing for the evaluation of aging effects on performance optimization. By comparing a reference case without aging consideration to the aging-aware approach, the results show significant improvements.
Key findings include an increase in State of Health (SOH) from 95% to 98% after one year, indicating extended battery lifespan. Furthermore, the aging-aware algorithm reduces total cost accounting for aging and annual electricity expense by 45%, based on a battery replacement cost of 500€/kWh and a 70% SOH at end of life. The study underscores the value of aging dynamics in optimizing energy management for residential systems, contributing to sustainability and resilience.