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Smartload with series-connected dc electric spring (ES) and noncritical load (NCL) structure can compensate for load voltage and improve the power quality. In this article, a distributed virtual inertial control framework based on model predictive control is proposed for low inertia in the dc microgrid. First, the current prediction model of the ES bidirectional full-bridge dc/dc converter is presented. Based on the virtual inertia control, model predictive control is used to optimize virtual capacitance during the operation. When the system suffers from disturbance, virtual capacitance increases to slow down the change of the dc bus voltage. When disturbance happens, the system can be stabilized quickly by reducing the virtual capacitance. Then, the consensus algorithm based on distributed control is established after defining the NCL voltage deviation rate, which can achieve the balance of NCL voltage deviations, and effectively avoid the more significant voltage deviation in one of NCLs. Furthermore, the small-signal model of the proposed control method is developed, and the influence of the proposed controller on the small-signal stability is described by employing the eigenvalue analysis method. Finally, based on the RT-Lab hardware-in-the-loop simulation system, comparisons and analysis are made to verify the effectiveness of the proposed control method under power step conditions. [ABSTRACT FROM AUTHOR]

Efficient and stable operation (ESO) of the proton exchange membrane fuel cell (PEMFC) system is challenging because the nonlinearity of system not only aggravates the difficulty of performance analysis but also puts forward higher requirements for controller design. In this article, a hierarchical performance enhancement control strategy (HPECS) is proposed, which can deal with optimal trajectory seeking under multiobjective constraints and nonlinear problem of system separately. In upper optimization level, the multiobjective optimization based on dynamic adjustment of weighting factor is proposed to seek optimal trajectory for ESO of PEMFC system considering the harm of oxygen starvation, oxygen saturation to system, and contradiction characteristic between net power and efficiency; in lower control level, a data-driven constraint adaptive predictive control is proposed for optimal trajectory tracking with the nonlinearity of system. The proposed HPECS is implemented and validated on the experimental PEMFC system. The comparative studies show that the proposed HPECS is superior in performance enhancement, disturbance rejection, and tracking ability. The normalized multiobjective optimization function can be basically guaranteed to above 0.9, and a nearly 7.2% enhancement in average can be also observed, which shows that ESO of PEMFC system can be achieved in changeable working conditions under proposed HPECS. [ABSTRACT FROM AUTHOR]

A multiagent-based coordination consensus algorithm was designed to simultaneously meet state-of-charge consensus and DC bus voltage stability requirements. A distributed energy storage system model with four batteries was built in Matlab/Simulink, and local droop control was employed to achieve the proposed algorithm. A multiagent system and agent weak communication network were constructed in the JADE platform, and the effectiveness of the proposed algorithm was verified by Simulink and JADE interactive simulation. The effect of communication delay on the system was also analyzed. [ABSTRACT FROM AUTHOR]