An adaptive droop control for distributed battery energy storage systems in microgrids with DAB converters

With the progress of renewable energy technologies, distributed energy system (DES) has become attractive due to its flexibility and interaction with power systems. Battery energy storage system (BESS) is an indispensable part of DESs, the control strategies of which have a great influence on system performance. In this paper, we present a novel adaptive droop control (ADC) for energy storage batteries. The state and model parameters of energy storage batteries are estimated simultaneously online by dual extended Kalman filter (DEKF) algorithm. Then the droop controller is designed based on the battery parameters by the ?virtual battery? algorithm, benefit from which power can be distributed among battery packs adaptively for their power characteristics, meanwhile SOC balancing can be achieved automatically. The proposed control strategy is validated in MATLAB/Simulink environment with a direct-current (DC) microgrid model where battery packs are connected to the DC bus through dual active bridge (DAB) converters. Compared with conventional droop controls, the proposed ADC method considers the battery characteristics and battery aging, and it is more suitable for DES with multiple sets of batteries.

Automated summary

The study introduces a novel adaptive droop control strategy for energy storage batteries, which estimates battery parameters online and designs a droop controller based on the "virtual battery" algorithm for adaptive power distribution and SOC balancing. This method takes into account battery characteristics and aging, making it more suitable for DES with multiple sets of batteries.