Adaptive Droop based Control Strategy for DC Microgrid Including Multiple Batteries Energy Storage Systems

In a microgrid architecture that includes energy storage systems based on parallel batteries, the inequalities in the batteries’ state of charge may cause inconsistency in the residual capacity of each battery. As a consequence, the battery cells may be degraded owing to overcharging or deep discharging. This paper presents an optimized load-sharing approach-based droop control strategy for parallel batteries operating in a DC microgrid. The main aim of the proposed control approach is to include the real battery capacity, which may be affected during its lifecycle, in the control algorithm in order to prevent non-matching conditions. As a result, proportional power-sharing will be allowed according to the actual capacity. In addition, all the SoCs will be equalized and the parallel batteries, present in the system, will operate equally in terms of SoC when delivering or absorbing power. Hence, the batteries lifecycle will be extended while power-sharing is performed in the best way. To this end, the identification of the actual battery capacity has been carried out using a metaheuristic optimization algorithm called Salp Swarm Algorithm (SSA). Each battery output is controlled by bidirectional DC/DC converters that ensure the charging and discharging process. The control approach has been evaluated under different scenarios such as similar and different capacities and a sudden disconnection of a battery. The obtained results prove the ability of the proposed control strategy to ensure proportional power-sharing while handling the inconsistency of residual energy between battery cells and improve the battery state of health.