DC microgrids encounter the challenges of constant power loads (CPLs) and pulsed power loads (PPLs), which impose the requirements of fast dynamics, large stability margin, high robustness that cannot be easily addressed by conventional linear control methods. This necessitates the implementation of advanced control technologies in order to significantly improve the robustness, dynamic performance, stability and flexibility of the system. This paper presents an overview of advanced control technologies for bidirectional dc/dc converters in DC microgrids. First, the stability issue caused by CPLs and the power balance issue caused by PPLs are discussed, which motivate the utilization of advanced control technologies for addressing these issues. Next, typical advanced control technologies including model predictive control, backstepping control, sliding mode control, passivity-based control, disturbance estimation techniques, intelligent control and nonlinear modeling approaches are reviewed. Then the applications of advanced control technologies in bidirectional DC/DC converters are presented for the stabilization of CPLs and accommodation of PPLs. Finally, advanced control techniques are explored in other high gain non-isolated (e.g., interleaved, multilevel, cascaded) and isolated converters (e.g., dual active bridge) for high power applications.

This letter investigates the fuzzy model predictive control synthesis of networked controlled power buffer for dynamic stabilization of a dc microgrid (MG). The proposed is based on Takagi-Sugeno fuzzy model and model predictive scheme to mitigate the network-induced delays from the sensor-to-controller and controller-to-actuator links. By employing the so-called time-stamp technique and network delay compensator (NDC), the delays are computed and compensated, which improves the effectiveness and robustness of the proposed controller. Due to the usage of two NDCs, the presented approach is robust against the network delays and results in small computational burden. Therefore, it can widely be employed on large distributed power systems. To show the merits of the proposed approach, it is applied to a dc MG that feeds one constant power load. Results show the simplicity of designing the controller and better robustness against the network's delays compared to the state-of-the-art methods. Additionally, hardware-in-the-loop simulations are presented to prove the practical applicability of the proposed controller.

More electric aircrafts (MEAs) comprise a vast amount of power electronic loads, which usually behave as constant power loads (CPLs). The incremental negative impedance of CPLs threatens system stability. To ensure an effective control of power flow in MEAs, eliminating the undesired behavior of CPLs is a necessity. This aim requires spontaneous power estimation of the time-varying uncertain loads. In this paper, an adaptive backstepping controller, which is interconnected to a 3rd degree cubature Kalman filter (CKF), is developed for a DC MG feeding non-ideal CPLs. At first, the load power is considered as an artificial state and augmented into the system states, which enables estimation of not only the DC MG states but also the unknown value of the load power. The estimated load power is then forwarded to a backstepping controller. The systematic approach of this controller allows obtaining the control signal, which is the duty ratio of the switch, to not only system stabilizing but also tracking a desired voltage of the DC bus under the load power variations. The proposed adaptive controller is tested on a DC MG that has one CPL. The conducted experimental results verify the effectiveness of the proposed adaptive controller.

This paper proposes a novel controller for the secondary load frequency control of a shipboard microgrid. The suggested controller is based on the linear matrix inequality technique and the Lyapunov stability theory. In the controller design procedure, the effects of the sensor-to-controller and controller-to-actuator delay communication links are considered, and a robust controller against the delay is proposed by utilizing a Lyapunov–Krasovskii functional. In addition, due to the practical space limitation of a ship, low-space, high-efficient renewable energy sources (RESs), and energy storage systems are considered. Furthermore, a diesel generator and a proton exchange membrane fuel cell are employed to effectively mitigate the frequency oscillations arise by the loads and RES power variations. Finally, to show the merits of the proposed method, several hardware-in-the-loop real-time simulations are performed. Comparison results illustrate the effectiveness of the proposed approach to the state-of-the-art methods.

This paper investigates the injecting power stabilization of nonlinear dc microgrids (MGs) with constant power loads (CPLs). By considering a centralized controller scheme, the limitations of the communication utilities are considered. Therefore, limited information is transferred through the nonideal noisy communication network. Consequently, a cubature Kalman filter (CKF) with a third degree is proposed to mitigate the effect of the noisy measurement and the noisy network on the system's information. Moreover, an estimation-based robust feedback controller is developed to design an optimal value for the injecting power. The considered CKF algorithm is robust against the system uncertainty and noisy environments and has a low computational time for high-order dc MGs with a high number of sources and CPLs. In addition, a systematic procedure to compute the feedback gain of the controller is presented, which can be numerically solved by linear matrix inequality techniques. Hardware-in-the-loop real-time simulation results verify the simplicity of the controller implementation, enhanced performance for the case of limited information, and better robustness against the noisy measurements compared to the state-of-the-art methods.