In this paper, the basic structure and design parameters of an oil-immersed air core coupling reactor were given according to the interruption requirement of the 160 kV mechanical direct current circuit breaker, and a field-circuit coupled finite element model was established based on the ANSOFT simulation platform. The prototype test results verified the correctness of the simulation calculation method. The coupling reactor design was optimized to minimize the total volume, taking equal height and heat flux design parameters as the optimization object, and the influence of the insulation distance between the oil tank and encapsulations on the secondary current of the coupling reactor were analyzed. Meanwhile, a combined optimization method about the reactor body and oil tank was proposed, and the optimization contour surface was plotted, which described the relationship between the total volume of the coupling reactor and structure parameters of the reactor body and oil tank. According to the optimization design results, the total volume was only 89% compared with the initial design parameters, and the correctness was verified by the simulation results.

Distribution network data may encounter random missing data caused by abnormal conditions and continuous missing data caused by natural disasters during gathering, transmission, and conversion. To address these problems, this paper proposes a missing data imputation method based on the Temporal Generative Adversarial Network with Gradient Penalty (TGAN-GP), which takes the Wasserstein Generative Adversarial Network with Gradient Penalty (WGAN-GP) as its basic framework, replaces traditional fully connected layers with a Temporal Convolutional Network (TCN) in the generator’s core, leverages causal dilated convolution to efficiently capture the long-range temporal dependencies and periodicity of measurement data, and integrates residual connections to mitigate gradient vanishing and network degradation during deep training. For the discriminator, the method adopts a Long Short-Term Memory (LSTM) network, which enhances the evaluation of the temporal rationality of generated data and thereby further improves imputation accuracy. Finally, simulations were conducted on the IEEE 33-bus distribution network test system. Results show that under the random missing scenario (10% missing rate), the Root Mean Squared Error (RMSE) and Mean Absolute Error (MAE) of node voltage magnitude imputation are as low as 0.00062 and 0.00051, those of node injected active power imputation are 0.00081 and 0.00065, and those of node injected reactive power imputation are 0.00082 and 0.00076. Under the continuous missing scenario, the RMSE and MAE of node voltage magnitude imputation are 0.00147 and 0.00122, those of node injected active power imputation are 0.00373 and 0.00268, and those of node injected reactive power imputation are 0.00314 and 0.00226. The imputation errors of all three data types are significantly lower than the comparison methods’.

With the development of extra-high voltage and ultra-high voltage transmission line in China, the reradiation interference generated by induced current on the surface of transmission steel tower becomes more serious to the radio station in the vicinity. In this paper, the calculation method for reradiation interference of transmission steel tower based on method of moment is analyzed. And in order to reduce the impedance matrix storage data in the memory space and the number of iterations in the calculation, the preprocessing of matrix sparse and diagonal norm precondition is presented to improve the performance of the conjugate gradient algorithm for the reradiation interference calculation. The reradiation interference of a standard 500 kV transmission steel tower is calculated using the improved conjugate gradient algorithm. And the results show that the algorithm enhances the convergence and stability after preprocessing and is suitable to calculate the reradiation interference of super-large metal truss structure target.

A statistical energy analysis model for predicting the noise of commercial vehicles was established in this paper. The modal density and loss factor of each subsystem were obtained by combining the calculation and test. The vibration excitation and sound excitation under various working conditions were measured. Then these basic parameters and excitation were put into the model for simulation and calculation, and the sound pressure level of driver's head sound cavity was obtained. By comparing the experimental results, the maximum error does not exceed 2dB (A), which indicates the accuracy of the SEA model for predicting noise. The energy transfer path analysis was carried out to find out the subsystems with the largest contribution of noise. Two kinds of optimized schemes were proposed and the results showed that the interior noise sound pressure can decrease by about 1.5dB (A).

Insulators in wind-sand flows distort the electric field along their surfaces due to the wind-sand electric field, threatening the safe operation of transmission lines. This paper models the impact of wind and sand flow on electric field distribution along transmission line insulators by integrating an Eulerian two-fluid field with an electrostatic field, incorporating the electrification process of sand particles. The study investigates how different wind speeds, dust concentration, and sand particle sizes affect the electric field distribution on insulators. The results show that the electric field along the insulator’s surface decreases in steps, while the electric field forms a “U”-shape with high ends and a low center. In contrast to the clean environment, wind and sand flow generally increases the electric field. Under the influence of wind-sand flows, each 2 m/s wind speed rise reduces the electric field by about 2–3%. As sand concentration and particle size grow, the electric field decreases near the high-voltage end and increases near the grounded end. Higher concentrations or larger particles significantly boost the maximum electric field intensity, worsening distortion and increasing long-term insulation risks.