1. School of Electrical Engineering Wuhan University Wuhan 430072 China; 2. School of Power and Mechanical Engineering Wuhan University Wuhan 430072 China
Abstract：It has been a long sought goal for the field of high voltage engineering to obtain the discharge voltage of air gaps by mathematical calculations instead of experiments. Therefore, a new idea for the discharge voltage prediction of air gaps was proposed in this paper, which is based on the physical thought that the insulation breakdown is due to the out-of-limit of the stored energy. The complicated air discharge process study was moved forward to the study of the energy storage status of the gap structure and its influence factors. The feature set used to characterize the energy storage status of air gap was defined from two aspects, including the electric field distribution and the impulse voltage waveform. The air gap discharge voltage prediction model was established by support vector machine (SVM). By the proposed model, the 50% discharge voltage prediction of rod-plane and rod-rod long air gaps with different gap lengths was successfully achieved, under positive and negative switching impulse voltage with different wavefronts. The mean absolute percentage errors of the predicted results of 4 test sample sets are respectively 3.6%, 3.25%, 3.5% and 3.8%. This method contributes to promoting the digital design of external insulation, and provide reference for establishing the discipline system of computational high voltage engineering.
邱志斌, 阮江军, 唐烈峥, 徐闻婕, 黄从鹏. 空气间隙的储能特征与放电电压预测[J]. 电工技术学报, 2018, 33(1): 185-194.
Qiu Zhibin, Ruan Jiangjun, Tang Liezheng, Xu Wenjie, Huang Congpeng. Energy Storage Features and Discharge Voltage Prediction of Air Gaps. Transactions of China Electrotechnical Society, 2018, 33(1): 185-194.
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2018, Vol. 33 
