Power flow in heterogeneous battery systems. (October 2019)

• Record Type: Journal Article
• Authors: Bauer, Michaela; Muehlbauer, Markus; Bohlen, Oliver; Danzer, Michael A.; Lygeros, John
• Is Part Of: Journal of energy storage. Volume 25(2019)
• Publication Date: 2019-10
• Subjects: Power flow -- Power distribution -- Heterogeneous systems -- Battery storage systems -- Model predictive control -- Optimisation; Energy storage -- Periodicals; Energy storage -- Research -- Periodicals; 621.3126
• DOI: 10.1016/j.est.2019.100816
• Languages: English
• ISSNs: 2352-152X

Abstract

Highlights: Control framework of microgrids can be used for power flow control. Power flow control can be achieved with static, dynamic or optimisation based methods. System performance, efficiency and service life are essential optimisation objetives. Optimisation based methods provide flexibility to the operator. Abstract: Control methods are important for stationary energy systems, especially for those based on so called second life batteries, due to asymmetrical system design and a mix of batteries from different capacities and aging levels. This study provides a theoretical analysis and simulation results of power flow and control methods in stationary energy storage systems. The theoretical part of this work develops a hierarchical control scheme comprising several levels and methods for computing the target variables of the control strategy based on optimisation. The simulation study focuses on the implementation of a stationary energy storage system, comprising four BMW i3 battery units connected to four DC/DC converters, and three DC/AC inverters. For this system four control strategies are developed in detail and compared. Three algorithms are based on feedback through a finite state machine, while the fourth uses linear programming and model predictive control techniques developed in this work. All methods are tested on two application profiles (artificial rectangle profile, frequency regulation profile) and the control schemes are compared in terms of performance, efficiency, and service life. The results suggest that optimisation based methods provide the flexibility to design a control strategy that weighs the three control objectives.