The presentation summarizes the main objectives, innovations and results of the ongoing BMSmart project (see Fig.1). These include measures to increase the energy efficiency, cost-effectiveness and lifetime of large-scale battery storage systems by using distributed battery condition monitoring with artificial intelligence, a generic structured model from cell to system level, and model-based, multi-criteria optimizing energy and string management concepts.

The „Large-scale Battery Storage Dresden South“ (12 MWh, 12 MW, LFP battery cells, see Fig.2) serves as a reference application for testing the new concepts. The battery is used in a multi-purpose application with FCR, aFFR and spot market trading. The results of an extensive analysis of high resolution monitoring and measurement data are presented. Furthermore, a generic modeling approach for large-scale battery storage systems in hybrid configurations with n parallel strings is presented, distinguishing homogeneous, size-heterogeneous and technology-heterogeneous configurations. Models for terminal, loss and aging behavior are described and parametrized at cell, module, string and system level (see Fig.3).

The main focus of the presentation is on the new model-based, multi-criteria optimizing energy and string management concepts for maximizing the benefits of large-scale battery storage. For energy management, deterministic and stochastic optimization approaches are discussed and compared for different multi-use scenarios, demonstrating the functionality and benefits (see Fig.4). For string management, static and dynamic control based, optimization based and combined methods are used as power splitting algorithms to increase the efficiency, lifetime, performance and safety of the battery storage system (see Fig.5). Fig.6 shows exemplary results of the implementation and testing of a dynamic control based round-robin string management concept with the aim of SOC equalization. The functional verification of the developed methods is performed for the reference object Dresden South with three strings and a total number of 34580 cells. Furthermore, large-scale battery storage systems with 5 to 10 strings are analyzed for heterogeneous configurations and different multi-use applications.

Finally, the presentation will give a brief overview of the developed simulation framework and the coupling of the generic storage model with the energy and string management blocks as well as the online condition monitoring units.

The BMSmart project is funded by the Federal Ministry of Economic Affairs and Climate Action (BMWK) with the funding code: 03EI4035B.