This article proposes an improved distributed cooperative control strategy for the energy storage system (ESS) in islanded dc microgrid. To meet the requirements of state of charge (SoC) balance, accurate current sharing, and voltage regulation, a hierarchical control structure is established. In the primary control layer, the droop coefficient is adaptively adjusted through the SoC dynamic changes in each energy storage unit (ESU) to achieve SoC balance, and two balance adjustment factors are introduced to improve SoC convergence speed and accuracy. In the secondary control layer, an information state factor $\zeta $ is designed to eliminate the influence of the inconsistent line resistance on the SoC balance and realize the dc bus voltage recovery. In the communication layer, each ESU only exchanges information with neighboring nodes through a sparse communication network, in which a dynamic consensus algorithm is used to achieve stable convergence of global average information. Finally, a dc microgrid simulation model and StarSim HIL experimental platform are built. The results show that the proposed control strategy can achieve SoC balance and accurate load current sharing under a variety of complex operating conditions and have excellent plug-and-play performance.

The control performance of traditional model predictive control (MPC) usually deteriorates dramatically with the permanent magnet synchronous motor (PMSM) parameter changes in operation, leading to current harmonics and torque ripple. This paper proposes a robust model predictive current control (MPCC) method based on a nonlinear extended state observer (NESO) to resolve this problem. The NESO is used to observe the current disturbance part to avoid the influence of motor parameters on the current model. Because this method is not sensitive to changes in motor parameters, the system is robust and has a low current harmonic. Second, the ESO designed in this paper based on the nonlinear function has a lower observation error. In addition, this paper uses the fixed coefficient method to simplify the design process. A more accurate parameter design method is proposed based on the bounded analysis of observation error. At the same time, the root locus diagram proves that NESO contributes to the stability of the current loop. Finally, hardware and simulation experiments proved that the robust MPCC based on NESO has lower harmonic content and better dynamic performance.

This paper presents a novel hierarchical cooperative control strategy to solve the problems of unbalanced State of Charge (SoC), unreasonable load current sharing, and unstable bus voltage for battery storage system (BSS) in islanded DC microgrid. In the communication layer, a neighbor-to-neighbor communication network architecture is constructed in which each battery storage unit (BSU) only communicates information with neighboring nodes, and a multi-agent consensus algorithm is used to iteratively estimate the relevant average global variables. In the main control layer, the droop coefficient is dynamically adjusted by constructing a fast SoC convergence function to ensure that the load current is reasonably distributed based on the rated capacity of each BSU. In the secondary control layer, a virtual voltage drop equalization controller and an average bus voltage compensation controller are designed to eliminate the impact of line impedance mismatch and compensate the average bus voltage. Furthermore, an optimized factor is designed to accelerate the later stage of SoC convergence. Finally, a DC microgrid experimental platform based on StarSim HIL is built, and the results demonstrate that the proposed strategy can achieve the control objectives of fast SoC balance, proportional load current sharing, and bus voltage stability.

In this article, an improved distributed secondary control strategy is proposed to achieve state of charge (SoC) balance, accurate load current sharing, and bus voltage recovery for battery storage system in dc shipboard microgrid. First, each battery storage unit (BSU) is regarded as a multiagent, and a neighbor-to-neighbor communication network is constructed to reduce the system communication burden. Each BSU is based on distributed consensus protocol, and global consensus can be achieved only by communication between adjacent BSUs. On this basis, a novel consensus-based SoC balancing algorithm is proposed to achieve accurate load current sharing, and a dc bus voltage controller is designed to achieve secondary regulation of the bus voltage. Furthermore, the SoC convergence characteristics, systems stability analysis, global dynamic model, and steady-state analysis of the proposed control strategy are studied. Finally, the simulation and StarSim HIL experimental results show that the proposed control strategy can achieve SoC dynamic balance, accurate load current sharing, and average bus voltage recovery under various complex conditions, and has a faster SoC convergence speed than advanced methods.

In this article, a novel distributed cooperative control framework is proposed to solve the problems of unbalanced load current sharing and bus voltage deviation in seaport DC microgrid. This framework without droop control, and a novel droop-free cooperative controller is constructed to achieve current sharing and voltage regulation goals. Each distributed generator (DG) transmits information based on a sparse communication network, and uses a discrete dynamic consensus algorithm (DCA) to complete the accurate estimation of a virtual average state variable containing voltage and current information. In addition, a current limiting function adapted to DCA is designed to avoid control failure and prevent the converter output currents from exceeding the rated value. Finally, the influence of boundary weight, communication delays, and calculation delays on the system stability is analyzed, and a seaport DC microgrid simulation model and StarSim HIL experimental platform are built. The results show that the proposed control scheme can achieve average bus voltage restoration and proportional load current sharing within the allowable range of communication delays and calculation delays, and has prominent plug-and-play capabilities.