It is increasingly important to effectively predict the failure of HVDC transmission lines caused by wildfire disasters. On the basis of comprehensively considering the distribution of fire points, the characteristics of wildfire propagation, and the failure factors of the transmission line, a method for calculating the probability of failure in HVDC transmission lines during wildfire disasters is proposed to quantify the risk of HVDC transmission line failures caused by wildfire disasters. Using the ArcGIS 10.7. platform, the study examined the quantity of fire points within the buffer zone of each HVDC transmission line from 2001 to 2022. The results indicate significant variations in the number of fire incidents in the buffer zones of various transmission lines. Notably, there has been a noticeable increase in the number of fire incidents along several HVDC transmission lines, including Xizhe, Baihetan-Jiangsu, Baihetan-Zhejiang, and Fufeng, in recent years. Based on the number of fire points in the buffer zone obtained through ArcGIS processing and the proposed failure probability calculation model, six HVDC hydropower transmission channels in the Sichuan Province were analyzed. At the same time, the proposed probability calculation model was simplified, and a corresponding linear evaluation index was introduced. The regression analysis results indicate that the proposed index can effectively assess the failure risk of HVDC transmission lines during wildfire disasters.

To improve the stability margin of the power grid under unconventional conditions and enhance the fault emergency support capability of AC/DC grids, this paper investigates multi-resource and multi-objective collaboration damping control strategy method based on a multi-input multi-output (MIMO) system model, which considers the multiple control impacts. Based on the analysis of system oscillation characteristics, appropriate feedback signals and controller installation locations are selected based on the modal ratio index. to realize the control effect, the HVDC and energy storage devices are used. Finally, the coupled robust controllers based on robust mechanism are designed out. Simulation results in PSCAD software show that, compared to traditional damping controllers, the controller designed is more suitable for system conditions with large perturbations and uncertainties.

Decentralized control offers a more effective way to avoid the complexities and coordination challenges encountered in centralized control. In the decentralized design of additional controllers for multi-infeed DC transmission systems, it is crucial to focus on the interactions among the controllers. To solve this problem, this paper primarily discusses an enhanced damping characteristic method for hybrid AC-DC systems based on an improved Effective Relative Gain Array (ERGA) index. Initially, feedback signals with better control effects on existing oscillation modes are pre-screened. Subsequently, the ERGA-based interaction index is utilized to pair these feedback signals with control locations, aiming to identify the optimal pairing scheme with the minimum index value, indicating the least interaction effect. This approach minimizes the mutual influence between loops and reduces adverse interactions among controllers. Simulations of multi-DC additional damping controllers designed using the multi-stage Linear Quadratic Regulator (LQR) method in a multi-DC system demonstrate that the optimal pairing scheme significantly outperforms both uncontrolled and poorly paired schemes in controlling low-frequency oscillations, thereby validating the optimality of the proposed method. Furthermore, various disturbances are introduced to verify the effectiveness and robustness of the proposed control strategy against low-frequency oscillations.

With the large-scale integration of renewable energy and the increasing use of power electronics, the issue of wide-band oscillations in power grids has become increasingly prominent. The scarcity and uneven distribution of oscillation samples pose significant challenges for training data-driven models, and traditional generative models struggle to ensure fidelity in both time and frequency domains. To address this, this paper proposes a Time–Frequency Fusion Generative Adversarial Network (TFF-GAN) for generating power grid oscillation risk scenarios. The method constructs a dual-path generation and discrimination framework, where the generator decomposes the signal using Short-Time Fourier Transform (STFT), with time-domain features extracted by a convolutional neural network (CNN) and frequency-domain features extracted from the STFT representation by a dedicated spectral network. These features are then fused using a U-Net structure. The discriminator simultaneously evaluates the authenticity of both the time-domain waveform and the frequency-domain spectrum. A composite loss function, incorporating time-domain loss, frequency-domain loss, and adversarial loss, is used for joint optimization. Experimental results demonstrate that the proposed method generates oscillation scenarios with high fidelity in both time-domain waveforms and frequency-domain spectra, effectively supporting power grid oscillation risk assessment and control strategy validation.

The large-scale integration of inverter-interfaced renewable generation has made the steady-state short-circuit current of renewable energy stations increasingly important for setting protections, planning, and fault analysis. Traditional single-unit multiplication methods are computationally efficient but often ignore the effects of internal electrical distance and active power output dispersion among generation units, which can lead to non-negligible errors at the station level. To address this issue, this paper proposes an improved single-unit multiplication method and a corresponding dimension-reduction framework for centralized renewable energy stations considering short-circuit current fitting characteristics. A unified three-segment positive-sequence current control model is first adopted to represent the low-voltage ride-through behavior of photovoltaic (PV), direct-drive wind turbine, and battery energy storage system (BESS) stations. The upper and lower voltage breakpoints are selected as 0.9 p.u. and 0.2 p.u., respectively, and the linear support coefficient was determined as 1.5 according to Chinese national standards. On this basis, the effects of electrical distance and active power output dispersion on the calculation error of the traditional single-unit multiplication method are analyzed. A grouping criterion based on the average access-point voltage and critical active power is then established, and the resulting two-group equivalent method is used to estimate the total short-circuit current of renewable energy stations. Electromagnetic transient simulations in PSCAD are conducted for PV, direct-drive wind, and BESS stations. The results show that, compared with the traditional single-unit multiplication method, the proposed method more accurately captures the steady-state short-circuit current characteristics under different voltage dips and output-dispersion conditions while retaining high engineering practicality.