Energy management of stationary hybrid battery energy storage systems using the example of a real-world 5 MW hybrid battery storage project in Germany

Abstract

Utility-scale Battery Energy Storage Systems (BESS) are becoming increasingly important for the transition to large shares of renewable energy sources in the electricity grid. Hybrid battery storage systems are an interesting option to increase the profitability of BESS by combining low-cost battery technologies with more expensive, but also more efficient and robust ones. In theory, such a hybrid system can be cheaper than a single-technology system by leveraging synergy effects while still satisfying the requirements of a given application. An energy management system, which allocates the setpoint power of the BESS to the individual battery technologies, is crucial for taking advantage of the hybrid system layout. This paper details an analysis of different energy management algorithms for hybrid BESS using the example of a real-world project called M5BAT and compares the latter to alternative BESS layouts. Besides two heuristic algorithms, a non-predictive optimization and a predictive optimization are developed. Models comprising the electrical, thermal and aging behavior of the considered BESS components are introduced. Simulations of the operation of the BESS providing frequency containment reserve are conducted for determining the operating costs. The performance of the algorithms is evaluated based on the simulation results. Comparing the results shows significant differences in the operating costs between the algorithms, especially when optimized to reduce operating costs. The economic advantage of hybrid BESS is validated by additional simulations of a virtual hybrid BESS and a virtual single-technology BESS. Although the layout has not been optimized in terms of individual sizing of the different battery technologies, the hybrid BESS show a considerable advantage over the single-technology BESS.Highlights-Comparative study of energy management algorithms for power allocation in hybrid battery energy storage systems.-Development of heuristic power allocation algorithms and optimization approaches for cost-optimal operation.-Modeling of all relevant components and effects that contribute to the operating costs.-Simulations based on frequency-containment reserve operation of a real-world system.-Evaluation of the advantage of hybrid over mono-technology battery energy storage.