摘要
柔性直流电网中的直流(DC)侧短路故障电流会严重危害电网的运行,而电阻型超导故障限流器(RSFCL)能有效地限制短路故障电流的增长,降低对直流断路器开断容量和开断时间的要求。为了研究用于RSFCL的氧化钇钡铜(YBCO)超导带材在短时直流冲击电流下的电阻特性,根据故障电流特征搭建了高压直流冲击平台,实验测量了在不同电流峰值和不同冲击时间的冲击电流下YBCO带材的电阻变化情况。详细分析了失超电阻越过拐点阻值前后的不同变化趋势并解释了其产生原因。据此,分阶段建立了基于Levenberg-Marquardt(LM)算法的多层前馈神经网络,并利用实验室获得的实验数据对网络进行训练和网络结构的优化。利用训练好的神经网络建立YBCO带材直流冲击特性预测模型。预测结果与实验结果的对比表明,基于LM神经网络的建模方法可以有效地预测直流冲击下YBCO带材失超电阻的变化。所得的预测模型可用于研究RSFCL在柔直电网中的设计与应用。
The direct current(DC)short-circuit fault current endangers the operation of the power gird seriously,while the resistive superconducting fault current limiter(RSFCL)could effectively limit the increase of the short-circuit fault current and reduce the requirements for the breaking capacity and breaking time of the DC breaker.In recent years,with remarkable progress in the preparation technology,yttrium barium copper oxide(YBCO)superconducting tape has become the main material for developing RSFCL at home and abroad.However,it is still difficult to model the resistance characteristics of YBCO tape under short-time DC impact current accurately.Therefore,this paper proposes a modeling method to predict the resistance of YBCO tape under DC current impact based on LM neural network.The study of DC impact characteristics of YBCO tapes and the modeling analysis based on neural network were carried out in this paper.In order to study the resistance characteristics of YBCO tape used in RSFCL under short-time DC impact current,a high-voltage DC impact platform was established according to the fault current characteristics.By adjusting the inductance value,capacitance value,resistance value and capacitor charging voltage,the platform can realize the short-time DC impact process with different current peak values and impact time.The resistance changes of YBCO tape were measured under different impact currents whose current peak at 1000 to 3000 A and impact time at 1.9 to 8 ms.The results would be used in the analysis and establishment of the model.The experimental results showed that when the peak of DC impact current was small,the resistance of YBCO tape increased with the increase of current and decreased to zero with the decrease of current,but when the peak of DC impact current was large,the resistance of YBCO tape did not decrease with the decrease of current,it just kept getting higher.The difference between the two situations was whether or not the resistance curve crosses an inflection point.The inflection point was
作者
高惠娟
张志丰
王浩男
郭凡铖
张国民
肖立业
Gao Huijuan;Zhang Zhifeng;Wang Haonan;Guo Fancheng;Zhang Guomin;Xiao Liye(Applied Superconductitvity Key Lab,Institute of Electrical Engineering,Chinese Academy of Sciences,Beijing 100190,China;Institute of Electrical Engineering,Chinese Academy of Sciences,Beijing 100190,China;University of Chinese Academy of Science,Beijing 100049,China)
出处
《稀有金属》
EI
CAS
CSCD
北大核心
2021年第1期55-61,共7页
Chinese Journal of Rare Metals
基金
国家重点研发计划项目(2018YFB0904400)
国家自然科学基金项目(51577179,51721005)
中国科学院前沿科学重点研究项目(QYZDJ-SSW-JSC025)资助。
关键词
YBCO带材
直流冲击
失超特性
LM神经网络
YBCO tape
direct current impact
resistance characteristic
LM neural network
