The use of high penetration converter-interfaced renewable energy (RE) based microgrids (MGs), due to the absence of rotational masses from conventional synchronous generators (SGs), may lead to a lack of inertia, which may lead the steeper frequency and voltage fluctuations that may in turn cause instability issues and challenges the normal operation of sensitive loads. To suppress these fluctuations and enhance the MGs stability, a novel model predictive control (MPC)-controlled virtual synchronous generator (VSG) for an energy storage system (ESS) is introduced. The proposed method can provide inertia support during transient states and enhance the dynamic characteristics of system voltage and frequency. By establishing the prediction model of VSG and designing the cost function for frequency and power, the increments of the needed active and reactive power are calculated then superposed on the power reference of VSG. The results show that the suppression performance of the voltage and frequency variations under loading transition with the proposed method is better than those of other techniques. Simulation and hardware-in-the-loop (HIL) results further demonstrate the effectiveness of the proposed method.

Electrical energy storage (EES) with a virtual synchronous generator (VSG) method is used widely for power fluctuation compensation in renewable energy microgrid systems. In the traditional VSG method, the inertia moment and damping coefficients usually remain constant. When dealing with large load variations, this method may cause obvious system frequency deviations and exceed the standard limit (e.g., IEEE Std 1547-2018). This paper proposes a novel control method combining fuzzy control with a model predictive controller (MPC) to solve this problem. The new method was applied to VSG. The virtual inertia and damping coefficient of VSG are on-line adjusted by a fuzzy controller, so that the regulation capability of the swing equation can be substantially utilized. The optimal rated power of VSG was modified using the MPC method, which further strengthens the EES support for power needs. The system frequency performance can be enhanced effectively under joint control. The simulation and experimental results further demonstrated the effectiveness of the proposed method.

Aging and temperature changes in the passive components of an LCL -filter grid connected converter system (GCCs) may lead to parameter uncertainties, which can in turn influence its modeling accuracy for finite-control-set model predictive control (FCS-MPC). The presence of model errors will change the resonance point and deteriorate the power quality of the grid current, in turn degrading the active damping performance. In this situation, there is a serious possibility that the GCCs may malfunction and automatically disconnect from the grid, causing great challenges to the system stability. To solve this problem, first, prediction error analysis in FCS-MPC due to the model parameter errors is presented. Second, to achieve high accuracy and fast filter parameter estimation in utility, an adaptive online parameter identification method based on gradient descent optimization (GDO) has been proposed. Finally, to further reduce the searching time needed by the optimal iteration step, a variable iteration step searching method based on the root-mean-square-prop (RMSprop) GDO method is proposed. Experimental studies of an LCL -GCCs prototype in the laboratory have been conducted to validate the effectiveness of the proposed method.

Sliding-mode control (SMC) has been widely used in grid-connected converter system (GCC) systems because of its robustness to parameter variations and external disturbances. However, chattering in SMC may deteriorate the tracking accuracy and can easily excite high-frequency unmodeled dynamics. To solve this problem, this article presents a fuzzy-fractional-order nonsingular terminal sliding-mode controller (Fuzzy-FONTSMC) for the grid current control of LCL–GCCs. First, the system modeling, design of the integer-order NTSMC controller, and state estimation based on the Kalman filter to minimize the sampling sensors are described. Second, the Fuzzy-FONTSMC controller is introduced for optimal fraction-order selection and chattering mitigation, this controller exhibits fast convergence with high tracking accuracy and strong robustness. Finally, the Lyapunov theorem is used to analyze the system stability. Experimental comparisons on a 10-kVA laboratory prototype validate the superior performance and effectiveness of the proposed method under many scenarios.

The inertia of a power system decreases with the increasing penetration of renewable energy, and the stability of power systems is facing great challenges. A virtual synchronous generator (VSG) has become one of the effective schemes for the high permeability of distributed generation, due to its similar characteristics to a synchronous generator. However, the coupling of the VSG in the power transmission from the actual power output point to the grid-connected point may lead to a steady-state error and dynamic oscillations, which limits the power output capability of the grid-connected converter and the grid support ability. To solve this problem, first, the power coupling mechanism of VSG is studied. Second, a virtual-inductor and virtual-capacitor control strategy is proposed for power decoupling, which eliminates the power coupling and improves their capability in suppressing the reactive power fluctuation. Finally, simulation and laboratory experimental results verify the effectiveness of the proposed decoupling strategy.

Power batteries play a vital role in electric vehicle (EV) industry. To evaluate their charging and discharging performance and achieve energy recovery, a power accumulator battery testing system (PABTS) based DC-microgrid (DC-MG) is proposed. However, during battery testing, frequent charging and discharging current test may endanger the stability of the PABTS DC-MG. Although, the traditional virtual inertia control (VIC) approach can stabilize the DC-bus voltage, its anti-interference ability is still limited. To solve this problem, an active disturbance rejection control (ADRC) based VIC control scheme is proposed, wherein the VIC approach provides virtual inertia for the system, and the ADRC is derived and modeled using the first-order virtual inertia equation. The external and uncertain internal disturbances in the system are considered for the total disturbance estimation. This disturbance is suppressed by feedback compensation, thereby greatly improving the system robustness. Finally, the effectiveness of the proposed ADRC-VIC method is further verified by experimental results on the laboratory hardware prototype under different scenarios.