The traditional phase-locked loops (PLLs) in a VSC-HVDC system such as a synchronous reference frame PLL (SRF-PLL) and a dual second-order generalized integrator PLL (DSOGI-PLL) cannot accurately track the positive-sequence voltage phase of grid fundamental wave under non-ideal power grid, which will cause different degrees of phase-locked error, affect the control performance of VSC and reduce the system stability. To solve this problem, an improved DSOGI-PLL scheme is proposed. First, the attenuation characteristics of SOGI-QSG at different frequencies are analyzed according to the Bode diagram, and the limitations of DSOGI-PLL applications are obtained. Then, based on the voltage of harmonic grid, the internal model of repetitive control is introduced on the basis of DSOGI to realize the real-time tracking and regulation of harmonic signals, thus suppressing the harmonic voltage interference. At the same time, considering the DC bias and voltage frequency fluctuation of power grid, a method of DC bias elimination and frequency adaptation is proposed to realize the adaptive phase tracking of power grid. Finally, the superiority of the proposed strategy was verified through a comparison between the simulation and experimental results.

In a certain environment where regional wind farms distribute irregularly, the traditional convolutional neural network prediction method cannot reflect the distribution states or influence relationship of regional wind farms, and it is difficult to accurately predict the wind speed. First, to solve this problem, the technology of graph convolutional networks is used for feature modeling, and the connected graph and weight matrix are established according to the topology of multiple wind farms and the cross-correlation coefficient of wind speed in each region. Second, depending on the time dynamic characteristics of wind speed at wind farms, an improved parallel convolution structure is used to obtain the correlation between wind speed series in multiple time periods at the same wind farm. Third, based on the spatial correlation and delay effect of wind speed at wind farms, the spatio-temporal characteristics of wind speed in different regions are aggregated by using a second-order aggregation method. Finally, the verification of data from one regional wind farm shows that the proposed method can extract the spatio-temporal characteristics and improve the performance of ultra short-term wind speed prediction for multiple wind farms on 0-4 h prediction scale.

Based on the two-stage (AC/DC and DC/DC) structure of a DC charging pile for electric vehicles(EVs) and through the analysis of the functional requirements of the two-stage circuit structure, a MATLAB/Simulink simulation model is built with a main circuit which consists of a Vienna circuit as the front-stage AC/DC rectifier and a Buck-Boost circuit as the rear-stage DC/DC voltage conversion circuit. Simulations are performed with load set as a pure resistive load and the PNGV model of a battery, respectively. Simulation results meet the requirement of parameters such as output voltage stability accuracy, output voltage ripple and input current harmonics, which proves that the model can be used to analyze the power grid loaded by EVs and promote the study on the impact of EVs on power grid.

The grid-forming(GFM) converter is one of the main components of high-permeability power electronic equipment, and its fault ride-through(FRT) capability is an important basis for ensuring the stable operation of a power system with a high degree of power electronics. On this basis, an FRT strategy for GFM converter is proposed, which not only considers the hardware constraints(i.e., current constraints) of the converter, but also can keep it running in protected mode under symmetric and asymmetric faults. First, the FRT-related problem of the GFM converter is analyzed in detail. Then, an appropriate FRT model and the corresponding control method are established. Finally, the effectiveness of the proposed method was verified by power-hardware-in-the-loop simulation and experiment. Results show that compared with a grid-following converter, the proposed control method can guarantee the instantaneous injection of reactive current when the GFM converter fails to prevent the overcurrent problem, and the GFM converter can still operate fault-tolerant under serious fault conditions.

To solve the instability problem caused by time-varying communication delay and uncertain faults in an isolated island AC microgrid, a novel robust hierarchical control method is proposed, which includes cascade current loop, voltage loop, virtual impedance and droop control loop. First, a robust controller based on adaptive backward integral non-singular fast terminal sliding mode control is designed in the current loop to adjust and track the current reference value under unknown bounded uncertainties and external disturbances. Second, the hybrid H2/H∞ control is used in the voltage loop, and the state feedback control law is used to generate the inner loop reference value to increase the robustness of the controller to disturbances, and sufficient conditions are given based on the linear matrix inequalities. Considering the unstable effects of time-varying delay (TVD), a distributed protocol based on consistency is adopted in the second control layer to improve the robustness of the controller against TVD. Third, droop control and virtual impedance loop are used to improve the system's power distribution accuracy. Finally, the performance of the proposed control method was evaluated by hardware-in-the-loop simulation, and its effectiveness was verified. Simulation results show that compared with the existing methods, the proposedmethod has advantages in transient response, steady-state performance and fault crossing capability under large and small signal disturbances.

In the traditional power system, the synchronous generator independently forms the internal voltage amplitude/frequency, which is connected to grid to establish the system voltage. However, the establishment of grid voltage at present is increasingly dependent on renewable energy equipment. Under the phase-locked synchronization, the grid-connected converter needs to detect the grid voltage to form the internal voltage, which seems to be different from the synchronous machine that independently forms the internal voltage and further establishes the system voltage. On this basis, the mechanism of internal voltage amplitude/frequency formed by the current control of the phase-locked synchronous converter is studied, and it is explicitly stated that the internal voltage amplitude/frequency is uniquely determined by current, which is essentially the same as the synchronous generator independently forming the internal voltage to establish the system voltage. In this paper, based on the control structure and the nature of forming the AC instantaneous value, it is explained that the converter output is essentially the internal voltage amplitude/frequency. Then, starting from the closed-loop dynamic process of equipment and network, the redundant relationship between terminal voltage and current is clarified. After the input current is determined, the internal voltage amplitude/frequency can be uniquely determined accordingly. Finally, combined with the simulation analysis, the correctness of uniquely determining the internal voltage amplitude/frequency by input current is demonstrated.

Under certain parameters, a permanent magnet synchronous motor (PMSM) will exhibit nonlinear chaotic behavior, which is mainly manifested in torque and speed oscillation, resulting in unstable system performance. Under this background, a sliding mode control (SMC) experiment was carried out on an actual motor platform. After a reasonable process of data, the corresponding system phase diagram was drawn, and it was compared with that without SMC, thereby verifying the chaotic phenomenon from another point of view. Based on the analysis model of chaotic motion of PMSM, the chaotic dynamic behavior of PMSM was studied theoretically by using the stability theory and equilibrium point properties. It was found that the experimental results were consistent with the numerical simulation, which verifies the existence of chaos and the correctness of theoretical analysis and shows that SMC has a better inhibitory effect on the chaotic phenomenon.

Simulation substation batteries often work under discontinuous operation conditions, which will result in capacity regeneration of batteries during their performance degradation. The degradation of batteries shows nonstationary and random characteristics, leading to a low prediction accuracy for the remaining useful life(RUL). Aimed at the problem of RUL prediction of batteries with capacity regeneration, a prediction method is proposed based on variational mode decomposition(VMD) and bat optimized kernel extreme learning machine(Bat-KELM). First, VMD is employed to decompose the battery state-of-health(SOH) time series into overall degradation components and capacity regeneration components. Then, Bat-KELM is used to construct prediction models of each component, so that the prediction accuracy of component trend is improved. At last, the prediction results of all components are blended together to yield the accurate battery SOH prediction results as well as the RUL results. The proposed method is applied to the analysis of battery degradation instance data, and results show its superiority in terms of prediction accuracy compared with the KELM and VMD-KELM models.

The state-of-charge(SOC) of lithium-ion battery is an important parameter for the operation and maintenance of a battery management system(BMS), and its accurate estimation is related to the real-time monitoring and safety control of lithium-ion battery. The traditional unscented Kalman filter(UKF) algorithm has the risk of making the covariance matrix negative when estimating the SOC of lithium battery, and the estimation accuracy is not optimal. To solve the shortcomings of this algorithm, a ternary lithium-ion battery is taken as the research object, and a second-order RC equivalent circuit model is established to describe the working characteristics of the battery. Based on the traditional UKF algorithm, a square-root double unscented Kalman filter(SR-DUKF) algorithm with double unscented transformation is proposed, and it is verified under multiple working conditions. Experimental results show that the improved SR-DUKF algorithm can better estimate the SOC of lithium-ion battery based on the second-order RC equivalent circuit. The average errors under HPPC and BBDST conditions are 0.59% and 0.52%, respectively, and the convergence times are 60 s and 110s, respectively, which verifies that the improved SR-DUKF algorithm has a higher estimation accuracy, better convergence and better robustness.

The traditional linear control method for a Boost converter has a poor dynamic performance and weak robustness to load disturbance. To solve this problem, a fixed-frequency sliding mode current control method based on power balance is proposed. First, the observed value of load current is used to calculate the input power, which is required to maintain the stability of output voltage. Then, the input power of the converter is adjusted by controlling the inductor current, so that the system's state trajectory is restrained on the sliding mode surface that possesses invariance to load disturbance, thus ensuring the system's large signal stability and improving its dynamic performance. Finally, based on the equivalent control principle, the equivalent sliding mode control is achieved through the PWM technique to avoid problems of chattering and unstable switch frequency. Simulations of the Boost converter under the condition of step load change are carried out in Simulink, and the proposed method is compared with the traditional linear control method. Results show that when using the proposed method, the system's dynamic performance is better and its large signal stability under large load disturbances is guaranteed.