Grouping consistency control strategy based on DMPC and energy storage unit constraints. (June 2023) - Zhang, Jing; Long, Benjin; He, Yu; Chen, Rong; Fan, Luqin; Li, Bowen; Gu, Tingyun; Fu, Xiaofan; Li, Hongqian
Highlights: This paper proposes a weighted consistency algorithm based on DMPC and state constraints, which takes into account the power constraints of each BESU and can quickly realize the adaptive power allocation of multiple energy storage units with less communication times. Based on the proposed consistency algorithm, this paper designs a grouping coordination control strategy for energy storage units, which can reduce the charge/discharge conversion times of BESU, and prolong the life of energy storage system and improve the energy conversion efficiency without double capacity configuration and without reducing the rated power of BESS. Based on the proposed consistency algorithm, this paper designs a method to reduce the low-power (low-efficiency) operation ratio of BESU, so as to improve the operation efficiency of the energy storage system. Abstract: This paper proposes a distributed packet consistency control strategy to solve the distributed coordinated control problem among multiple battery storage units. In order to ensure that the distributed power allocation results meet the power constraints of each energy storage unit and reduce the communication requirements of distributed control, this paper proposes a weighted consistency algorithm based on distributed model predictive control and state constraints. A grouping control strategy of energy storage units is proposed. The weight of energy storage unit is set according to SOC information to improve consistency of SOC of energy storage unit. Meanwhile, based on the proposed consistency algorithm, an inter-group coordination control strategy and an efficiency improvement strategy of energy storage units are developed to improve the regulation ability of energy storage system, extend the life of energy storage system and improve the energy conversion efficiency. Finally, the proposed algorithm and control strategy are simulated and analyzed by building a microgrid system with eight battery storage units in Matlab. The simulation results show that the proposed algorithm and control strategy have certain advantages in improving convergence speed, optimizing control effect, prolong energy storage life and improve the operation efficiency of the energy storage system.