This theme cuts across the other four themes addressed by the Project. This theme encompasses monitoring, controlling, optimising and integrating into networks, energy storage technologies including batteries, fuel cells, power-to-gas and virtual storage, to fully realise their value.
ADVANCED HEALTH MONITORING AND ANALYSIS METHODS FOR BATTERY ENERGY STORAGE SYSTEMS
The objective of this sub-theme is to investigate a new framework that integrates dynamic battery state estimation into charging/discharging algorithms to improve the charging efficiency, reliability and cycle life of batteries.
The focus of the research will include:
modelling material properties and chemical processes via combined theoretical- experimental investigations;
developing effective and efficient on-line measurement to assist the estimation of time-varying parameters of the nonlinear battery models;
developing customer-tailored state-of-charge and remaining useful life estimation methods for batteries based on the dynamic models;
building a real-time RTDS-based hardware-in-the-loop test-bed for battery life cycle testing and model validation; and
developing adaptive charging algorithms for optimal scheduling, considering battery degradation and state estimation uncertainties.