Search

Abstract The trip mechanism is a weakness in circuit breakers. Traditional fault identification based on the coil current is difficult to report early mechanical defects such as coil‐plunger jam. Here, the vibration signal during the trip process was extracted. Based on the coil current signal and vibration signal, the characteristics of the trip mechanism are analyzed. The phase space reconstruction (PSR) method is used to extract features from the vibration signal. Combined with the features from the coil current waveform, the feature set representing the health condition of the trip mechanism is proposed. The fault simulation tests are carried out and the variation of current vibration characteristics under fault conditions is studied. The fault identification model based on a support vector machine (SVM) is proposed and compared with the identification results when features are extracted from a single signal. When the power supply voltage is dispersed, the prediction accuracy of fault identification is 83.3% considering only the features of the current waveform or vibration signal. And the identification accuracy rises to 96.7% while using the feature set of current and vibration signals. On basis of the current signal, the method further combines the vibration signal so that the robustness of defect identification improves.

The hybrid high-voltage direct current (HVDC) breaker combines mechanical and power electronics switching that enables it to interrupt power flows within a few milliseconds. Mechanical switch is a key component of hybrid HVDC breaker and has a number of serially connected interrupter units which ideally would divide the voltage equally. The static voltage distribution characteristics and voltage sharing design of a multi-break mechanical switch were discussed in this study. A finite-element model was developed to study the static voltage distribution characteristics and capacitance parameters of multi-break mechanical switch (which actually consists of resistance and capacitance parameters under direct current) as a preliminary study. Comparisons were made under the simulation of vertical and U-shaped arrangement forms. The results indicate that the static voltage distribution of the high-voltage terminal is at least more than 65%, whereas the severe non-uniform voltage distribution can be well improved by means of the method proposed in this study.

The transmission corridors can be effectively saved using 750 kV four-circuit transmission line on the same tower. In order to reduce the corona level, structure optimisation of fittings plays an important role in the transmission line design. In this study, the electric field distribution of 750 kV transmission line on six cross-arms tower was calculated based on finite element method, and the influences of pipe diameter, ring diameter and installation position of the grading ring were analysed. The results show that the increase of pipe diameter can reduce the electric field strength of grading ring while the increase of installation position and decrease of ring diameter are important to protect the end fitting of composite insulator. When using grading ring with the pipe diameter of 100 mm, the ring diameter of 700–900 mm and the installation position of 150–250 mm, the electric field strength can be controlled in a reasonable range. These results can provide references for the grading ring design of 750 kV four-circuit transmission line on the same tower.

Full-scale discharge tests of transmission line–tower air gaps are costly and time-consuming, and they cannot exhaustively simulate all the gap configurations in practical engineering. In this paper, a machine learning model established by support vector machine is introduced to predict the switching impulse discharge voltages of the ultra-high-voltage (UHV) AC transmission line–tower air gaps. The three-dimensional finite element models of a UHV cup-type tower and a UHV compact transmission line were established for electric field calculation, and some features were extracted from the hypothetic discharge channel and the shortest path between the bundled conductor and the tower. These features under a given voltage were normalised and input to the SVM model, while the output is two binary values, respectively, representing gap withstanding or breakdown. Trained by experimental data of one type of the UHV transmission line–tower gaps, the SVM model is able to predict the discharge voltages of another gap type. The mean absolute percentage errors of the two engineering gap types, under different gap distances, are 8.31 and 4.86%, respectively, which are acceptable for engineering applications. The results provide a possible way to obtain the discharge voltages of complicated engineering gaps by mathematical calculations.