After a fault disturbance, there is a risk of temporary overvoltage in areas where renewable energy is aggregated, which can lead to the disconnection of renewable energy and threaten the safe and stable operation of the power grid. The capacity of input access to a multi-input system affects the temporary overvoltage level. Therefore, there exists a maximum access capacity that prevents the renewable energy from disconnecting from the grid in the event of a fault disturbance. To solve for the maximum access capacity, this paper first analyzes the reasons for the temporary overvoltage in the renewable energy AC transmission system caused by the fault disturbance, according to the renewable energy low voltage ride through (LVRT) control strategy. Then, a mathematical model for solving the temporary overvoltage maximum value in such a system with multiple inputs is presented. On top of that, an optimization model for the maximum access capacity of renewable energy, which is subject to the constraint of overvoltage safety, is established. The optimization model is solved using the tracking center trajectory interior point method to obtain the maximum access capacity of the multiple-input system and the optimal output distribution of each renewable energy source. Further, the cosine similarity is used to evaluate which output distribution is better for the same access capacity. Finally, the effectiveness of the proposed method for quantifying the maximum access capacity of multi-feeder systems is verified in a practical engineering example.

Increase in permeability of renewable energy sources (RESs) leads to the prominent problem of voltage stability in power system, so it is urgent to have a system strength evaluation method with both accuracy and practicability to control its access scale within a reasonable range. Therefore, a hybrid intelligence enhancement method is proposed by combining the advantages of mechanism method and data driven method. First, calculation of critical short circuit ratio (CSCR) is set as the direction of intelligent enhancement by taking the multiple renewable energy station short circuit ratio as the quantitative indicator. Then, the construction process of CSCR dataset is proposed, and a batch simulation program of samples is developed accordingly, which provides a data basis for subsequent research. Finally, a multi-task learning model based on progressive layered extraction is used to simultaneously predict CSCR of each RESs connection point, which significantly reduces evaluation error caused by weak links. Predictive performance and anti-noise performance of the proposed method are verified on the CEPRI-FS-102 bus system, which provides strong technical support for real-time monitoring of system strength.

AC fault disturbance can cause commutation failure (CF) in LCC-HVDC, potentially threatening the secure and stabile operation of sending and receiving AC systems. Previous studies have focused on commutation failures in inverters resulting from receiving-end AC system faults. Different from previous studies, this paper comprehensively analyzes the commutation failure mechanism of the inverter caused by a three-phase symmetrical grounding fault at different HVDC sending terminals. First, based on actual HVDC transmission system parameters, a simulation model is established in the electromagnetic transient simulation platform Hypersim, and the phenomenon of inverter commutation failure due to a sending-end fault is simulated and verified. Second, unlike the qualitative analysis used in the past to explain reasons for CF, the quantitative analysis investigates dominant factors that lead to inverter CF under different control modes. In control mode 1, the main reason for CF is that the inverter commutation voltage drops beyond the critical value. In control mode 2, the decrease in the inverter advance angle increases the risk of inverter CF. At the same time, through analysis of the relevant electrical quantities before CF, excessive DC current in the system recovery stage is the root cause of the above phenomenon. On these bases, a control strategy is proposed to suppress commutation failures caused by the fault at the sending end by adjusting the rectifier's trigger angle. Electromagnetic transient simulation results show that the proposed control strategy can effectively inhibit CF.

The power system is experiencing a higher penetration of renewable energy generations (REGs). The short circuit ratio (SCR) and the grid impedance ratio (GIR) are two indices to quantify the system strength of the power system with REGs. In this paper, the critical short circuit ratio (CSCR) is defined as the corresponding SCR when the system voltage is in the critical stable state. Through static voltage stability analysis, the mathematical expression of the CSCR considering the impact of GIR is derived. The maximum value of CSCR is adopted as the critical value to distinguish the weak power system. Based on the static equivalent circuit analysis, it is proved that the CSCR is still effective to evaluate critical system strength considering the interactive impact among REGs. Finally, we find that the GIR can be neglected and the SCR can be used individually to evaluate the system strength when SCR>2 or GIR>5. The correctness and rationality of the CSCR and its critical value are validated on ADPSS.

The mode-based damping torque analysis (M-DTA) method for studying the effect of an external controller on power system low-frequency oscillations is proposed in this paper. First, based on the interconnection model between the system and the controller in the frequency domain, the oscillation loop corresponding to the electromechanical oscillation mode is built, and then the mode-based damping torque of the controller can be calculated. Then, the application of the M-DTA method in the power system is illustrated. The derivation shows that in the single-machine infinite-bus power system, the M-DTA method is completely equivalent to the classical damping torque analysis (C-DTA) method. In the multi-machine power system, the mode-based damping torque directily reflects the effect of the controller on the oscillation mode, overcoming the shortcomings of the C-DTA method in which there is no direct correspondence between the damping torque and the oscillation mode. By deriving the relationship with the residue index, the M-DTA method shows higher accuracy than the residue method in applications, such as controller parameter adjustment. Finally, two example power systems are presented to demonstrate the application of the proposed M-DTA method.