To overcome the real-time problem of maximum power point tracking (MPPT) for partially shaded photovoltaic (PV) systems, a novel nature-inspired MPPT controller with fast convergence and high accuracy is proposed in this paper. The proposed MPPT controller is achieved by combining salp swarm algorithm (SSA) with grey wolf optimizer (GWO) (namely, SSA-GWO). The leader structure of the GWO algorithm is introduced into the basic SSA algorithm to enhance the global search capability. Numerical simulation on 13 benchmark functions was done to evaluate the proposed SSA-GWO algorithm. Finally, the MPPT performance on PV system with the proposed SSA-GWO algorithm under static and dynamic partial shading conditions was investigated and compared with conventional MPPT algorithms. The quantitative and simulation results validated the effectiveness and superiority of the proposed method.

Multi-inverter systems have been widely used for grid-connected large-scale centralized photovoltaic (LSCPV) plants. However, the problem of how time delays affect the stability of digitally controlled grid-connected LSCPV plants with multi-inverter systems has not been investigated sufficiently. This paper models a grid-connected LSCPV system as a cascade system and conducts a systematic study of the relationship between the time delay and the stability of a grid-connected LSCPV system. The analysis intuitively reveals the influence of the time delay on the stability of the grid-connected LSCPV system. The impact of the time delay on the stability range of the number of grid-connected inverters in LSCPV plants is discussed for the first time, and the stability range for a specific time delay is obtained from the root locus. In addition, considering the damping performance is negatively affected by the time delay, an improved capacitor-current-feedback active damping method is proposed to reduce the effects of the delay on the damping region and the robustness against variations in the grid impedance. Simulations and experimental results are presented to validate the theoretical analysis and the effectiveness of the proposed delay compensation method.

According to studies on active damping and the stability margin, grid impedance variation does not make active damping ineffective; instead, it attenuates the stability margin. The harmonic resonance mechanism of grid‐tied inverters has been revealed by researching the influence of stability margin reduction on harmonic current amplification coefficients around the cut‐off and phase crossover frequencies. With the stability margin decreasing, amplification to harmonics around relevant frequencies is strengthened. The harmonic resonance around the cut‐off frequency is triggered as the stability margin decreases to zero. An online phase margin (PM) compensation strategy is proposed in this study to improve system robustness to grid impedance variation. The strategy is implemented by the lead network to enhance the phase and the proportional component to regulate the cut‐off frequency according to the grid impedance measured online. Hence, the system can be maintained with a sufficient PM to mitigate the harmonic resonance caused by grid impedance. Simulation and experimental results validate the theoretical analysis presented in this study. Comparisons show that the proposed strategy is superior to the zero compensation strategy in suppressing the harmonic resonance.

As the grid inductor increases the phase difference between the inverter admittance and the grid admittance increases at their intersection frequency showing that the harmonic amplification coefficient is enhanced. When the phase difference exceeds 180° the admittance ratio cannot satisfy Nyquist criterion and the system becomes unstable. To address this problem a phase‐reshaping strategy aiming to revise the phase of the inverter admittance in a wide frequency region without using any real‐time information referring to the grid impedance or the resonant frequency is proposed. The strategy is realised by the combination of the feedforward of the voltage at the point of common coupling (PCC) and the harmonic compensators. In the feedforward, a phase lag network is employed to modify the admittance phase in a wide frequency region. The harmonic compensator in parallel to the current controller is used to offset the magnitude rise brought in by the PCC voltage feedforward. After adopting the proposed strategy, the upper limit of the phase difference is constrained at 150° and the magnitude of the inverter admittance is lower than that of the original one at low‐order odd‐harmonic frequency. The validity of the proposed strategy is verified by the experimental results.

To improve the robustness of grid-connected inverter against grid impedance in a weak grid an integrated design method of LCL-filter parameters and controller parameters is proposed. In the method the inherent relation of LCL-filter parameters and controller parameters is taken into consideration to realize their optimized match. A parameter normalization scheme is also developed to facilitate the system stability and robustness analysis. Based on the method all normalization parameters can be designed succinctly according to the required stability and robustness. Additionally, the LCL parameter and controller parameter can be achieved immediately by restoring normalization parameters. The proposed design method can guarantee the inverter stability and robustness simultaneously without needing any compensation network, additional hardware, or the complicated iterative computations which cannot be avoided for the conventional inverter design method. Simulation and experiment results have validated the superiority of the proposed inverter design method.

Voltage sag is the most serious power quality problem in the three-phase symmetrical power system. The influence of multiple factors on the voltage sag level and low computational efficiency also pose challenges to the prediction of residual voltage amplitude of voltage sag. This paper proposes a voltage sag amplitude prediction method based on data fusion. First, the multi-dimensional factors that influence voltage sag residual voltage are analyzed. Second, these factors are used as input, and a model for predicting voltage sag residual voltage based on data fusion is constructed. Last, the model is trained and debugged to enable it to predict the voltage sag residual voltage. The accuracy and feasibility of the method are verified by using the actual power grid data from East China.