Energy storage features and a predictive model for switching impulse flashover voltages of long air gaps

It has been a long sought goal to determine the critical flashover voltages of long air gaps by mathematical calculations instead of experiments. In this paper, a predictive model is proposed for 50% discharge voltage (U50) prediction of long air gaps subjected to switching impulses. This model is developed on the basis of the physical thought that air breakdown can be viewed as out-of-limit of the capacitive energy stored in the electric field. Two groups of features are defined to characterize the energy storage status of an air gap, from the perspective of electric field distribution and impulse voltage waveform, respectively representing the space distribution and time accumulation of the energy. The predictive model is established by support vector machine (SVM), and the input data are the energy storage features. Giving an estimated applied voltage range, the predicted result of the critical flashover voltage is searched by the golden section method. Trained by 6 known experimental data, this model is used to predict the U50of rod-plane, rod-rod and rod-conductor long air gaps subjected to negative switching impulse voltages. The mean absolute percentage errors of 5 groups of test samples are respectively 6.0%, 5.8%, 6.3%, 3.2% and 1.7%, which are in an acceptable range in the view of engineering applications. The proposed method might be useful to predict the U50 of long air gaps with various geometries and under different voltage waveshapes, therefore reducing the required test work for insulation design of high voltage equipments.