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作 者:邱志斌 宋雨 吴子建 陈文豪 QIU Zhibin;SONG Yu;WU Zijian;CHEN Wenhao(Department of Energy and Electrical Engineering,Nanchang University,Nanchang 330031,China)
机构地区:[1]南昌大学能源与电气工程系,江西南昌330031
出 处:《绝缘材料》2024年第9期106-113,共8页Insulating Materials
基 金:国家自然科学基金资助项目(52167001);江西省研究生创新专项资金项目(YC2021-S055、YC2022-s021)。
摘 要:空气放电源于电场与大气环境的相互作用,空气间隙放电电压受到极间电场分布与大气参数的共同影响。为实现高海拔环境下棒-板长空气间隙的操作冲击放电电压计算,本文以气压、温度、绝对湿度、海拔以及电场特征量作为特征集,构建了一种基于k近邻(k-nearest neighbor,KNN)算法的绝缘预测模型。采用55~4 300 m海拔范围内的试验数据对KNN算法进行训练,建立气隙特征与其绝缘强度的映射关系,实现了5 000 m高海拔环境不同间隙距离的棒-板空气间隙放电电压预测,最大相对误差和平均绝对百分比误差分别为8.58%和3.78%,验证了所提方法的有效性。将模型外推至平原不同大气参数下的棒-板空气间隙时,放电电压预测值与试验值同样具有较好的一致性。研究结果可为不同大气环境下的空气间隙绝缘强度计算提供参考。Air discharge results from the interaction between electric field and atmospheric environment,therefore the air gap switching impulse discharge voltage is affected by the interelectrode electric field distribution and the atmospheric parameters.In order to calculate the discharge voltage of rod-plane long air gaps at high altitude areas,we construct an insulation prediction model based on k-nearest neighbor(KNN) algorithm with air pressure,temperature,humidity,altitude,and electric field characteristic parameters as feature set.The KNN algorithm was trained by the test data in the altitude range of 55-4 300 m to establish the mapping relationship between air gap features and the insulation strength,and then discharge voltage prediction of rod-plane air gaps at the high altitude of 5 000 m with different gap distances was realized.The maximum relative error and the mean absolute percentage error are 8.58% and 3.78%,respectively,which verifies the effectiveness of the proposed method.When the model was extrapolated to the rod-plane air gaps in plain area under different atmospheric parameters,the predicted discharge voltages also had good agreement with the experimental values.This study results can provide references for the calculation of air gap insulation strength in different atmospheric environment.
分 类 号:TM85[电气工程—高电压与绝缘技术]
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