Discharge Voltage Of Air Gap Research Articles

Discharge Characteristics and Numerical Simulation of the Oil–Gas Surface under DC Voltage

Low insulation strength at the oil–gas surface due to oil leakage and partial discharge of oil-immersed power equipment is a major threat to the safe and reliable operation of power systems. This paper investigates the initiation and development of the oil–gas surface discharge. The oil–gas surface discharge test platform was established, and discharge tests were carried out at different gap distances (1–2.5 mm). By coupling the electric field and flow field, the multi-layer dielectric discharge streamer model was built, and the characteristics of charge and electric field distribution at different gap distances were studied. The test results show that the liquid surface between the electrodes rises during the discharge process. Furthermore, the surface discharge voltage exceeds the air gap discharge voltage. With the simulation analysis, the oil–gas surface discharge is a typical streamer development process. Under 50 kV applied voltage and 2.5 mm gap distance, the average development speed of the streamer is 12.5 km/s. The larger the gap distance is, the greater the average streamer development speed is. The recording and numerical simulation of the discharge process are of great significance for exploring the mechanism of oil–gas surface discharge, optimizing the discharge process, and diagnosing partial discharges.

Influence of protrusions on the positive switching impulse breakdown voltage of sphere‐plane air gaps in high‐altitude areas

The construction of ultra-high-voltage direct-current power transmission projects in high-altitude areas calls for the research into the discharge characteristics of the air gaps in the valve hall of a power converter station in such areas. Tests on the switching impulse discharge characteristics of the sphere-plane air gap were conducted at Yangbajing test base (Tibet, China) at an altitude of 4300 m on conditions that there were burrs on the 1.3 m diameter shield balls. The discharge characteristics, under the influences of burrs with different lengths and locations, were obtained and compared with test data from low-altitude areas. The results indicate that the arrangements of burrs with different lengths and locations can significantly reduce the switching impulse discharge voltage of sphere-plane air gaps, while the voltage sag gradually decreased down with increasing burr length. Moreover, the larger the sphere-plane air gap is, the smaller the influence of such burrs have. High altitude also substantially decreased the switching impulse discharge voltage of the air gap. When the surface of shield balls was smooth, the U50 saturation of the air gap was more significant than at low altitude; however, if there were burrs on the shield balls, the saturation effect was less significant.

Modelling for switching impulse breakdown of live working gaps between equipotential worker and transmission towers

Air gap discharge voltage is the key parameter to determine the minimum approach distance for live working. In this study, a mathematical–physical model for predicting 50% discharge voltage of the transmission line air gaps considering the effect of live line worker is developed based on the continuous leader inception criterion. Also, the tower structure coefficient S T is proposed to represent the influence of various tower structures and S T is calculated by finite element method. Finally, the switching impulse discharge tests of the equipotential worker-tower structure gaps are carried out on 750 kV transmission lines to verify the proposed model. The research results show that the errors between the calculation and experimental data are within ±4.03% which demonstrates the feasibility of discharge voltage prediction for complicated live working gaps. This model offers a possible way to determine the safety air gap distance for live working by analytical and numerical calculation rather than costly and time-consuming experiments.

Application of a SVR model to predict lightning impulse flashover voltages of parallel gaps for insulator strings

Discharge voltage prediction of engineering gap configurations is a great challenge for external insulation design in high‐voltage engineering. This paper presents an air gap discharge voltage prediction model based on the support vector regression (SVR). A series of features are defined on the shortest interelectrode path of an air gap, and they are extracted from the electric field calculation results using the finite element method. These electric field features are considered as the input parameters of the SVR‐based model, and the output is the air gap discharge voltage. The genetic algorithm is used for parameter optimization of the SVR model. Trained by a few experimental data of the Institute of Electrical and Electronics Engineers standard rod–rod gaps, this model is applied to predict the standard lightning impulse flashover voltages of parallel gaps for insulator strings under different gap configurations. The prediction results coincide well with the experimental data collected from previous publications. The mean absolute percentage error of the eight test samples is within 4.07%, which is acceptable for engineering applications. The SVR‐based model may be helpful to guide the structure design and insulation coordination of parallel gaps and insulator strings, thus reducing the required full‐scale tests. © 2019 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

Analysis of the Effect of Atmosphere Condition on Discharge Characteristic of Air Gap and the Application of Neural Network

The discharge voltage of air gap is an important factor to determine the level of external insulation. In this paper, in order to study the influence of atmosphere condition on the discharge voltage, an automatic discharge device has been developed to monitor the discharging experiment of sphere- sphere electrodes and record the atmosphere condition and the discharge voltage. This paper discusses the application of back-propogation neural network (BPNN) in the prediction of discharge voltage. The result indicates that it is feasible and the average relative error is 1.8%. When the BPNN based on data of one monitoring sites is used to predict the discharge voltage of other regions, the average relative error will be greater but the error is still under acceptable limits.

Feature extraction of electric field distribution and its application in discharge voltage prediction of large sphere-plane air gaps

The electric field calculations cannot effectively guide the insulation design of high voltage equipment since the insulation strengths of dielectrics cannot be predicted according to the electromagnetic analysis. In this paper, some features related to the electric field distribution such as the electric field strength, electric field gradient, path length, and the electric field integral are defined and extracted from finite element calculations of air gaps. The electric field features are taken as the input parameters of a grey correlative model established by support vector machine (SVM), so as to establish the multi-dimensional nonlinear relationships between these features and the discharge voltage of an air gap. The grid search (GS) method was used to search the optimal parameters of the SVM. This model was applied to predict the 50% discharge voltages of large sphere-plane air gaps in UHVDC valve halls. The predicted results were obtained after multiple iterative calculations, using the golden section search method. Compared to experimental data, the relative errors of the predicted results are within an acceptable range in view of engineering applications, which indicates the validity of the proposed method. This paper achieves the discharge voltage of air gaps by numerical computations instead of costly experiments.

Research on Prediction Model of Discharge Voltage under High-Altitude Condition Based on BP ANN

To obtain a mathematical model capable of predicting the 50% discharge voltage of air-gap under high-altitude conditions, we used the test results of air-gap in high altitude areas to establish the 50% discharge voltage BP neural network model of air-gap under high-altitude conditions. We used the model to forecast the 50% discharge voltage of air-gap under high-altitude conditions. The result shows that the maximum error between forecast voltage and test voltage is 1.42%, which certificates the possibility of using the neural network to build the multidimensional and nonlinear relationship between the environmental factors and discharge voltage. At the same time, we can simulate and analyze the effect of environmental factors on discharge voltage of air-gap with the help of model that we established, analysis showed that there was a positive correlation between the environmental factors, such as temperature, humidity and atmosphere pressure, and discharge voltage of air-gap.

DC positive discharge performance of rod-plane short air gap under rain conditions

To study the discharge performance of air gap under rain conditions and provide reference to the selection of clearance distance of external insulation in strong rain, this paper explored the influence of different environment conditions, rain intensity, rain conductivity, and ambient temperature on the dc positive breakdown voltage of rodplane air gap in the artificial climate chamber and at Xuefeng Mountain Natural Site. It is shown that the discharge voltage of rod-plane short air gap in wet condition is slightly higher than that in the dry condition; light rain has little influence on the positive dc discharge voltage of rod-plane short air gap. The relative discharge voltage of air gap decreases with an increase of rain intensity and rain conductivity with 2.2% to 0.2% / (mm/min), 1.4% to 0.1% / (100 μS/cm), respetively; and it is associated with the increase of ambient temperature with 0.3% to 0.1% / °C. In addition, several computations were carried out with different droplet sizes in rod-plane air gap. It can be indicated that the maximum electric field in the air gap increases with the increase of the radius and number of droplets.