| 摘要: |
| 短路电流峰值预测对低压系统选择性保护的实现至关重要，目前仍缺乏深入研究。利用短路故障早期检测技术，建立了低压系统单相短路故障仿真模型。获取全相角范围短路故障电流波形，并分析不同相角下短路电流峰值的特点。通过短路故障电流历史数据，构建基于条件云发生器的预测规则，从而建立基于二维云的短路电流峰值预测模型。实验结果表明，基于二维云模型的短路电流预测方法能够准确预测出短路故障电流峰值，为低压选择性保护技术的实现奠定基础。 |
| 关键词: 低压配电系统 短路电流峰值预测 早期检测 二维云模型 不确定推理 |
| DOI：10.7667/PSPC171748 |
| 投稿时间：2017-11-30修订日期：2018-01-22 |
| 基金项目:国家自然科学基金项目资助(51377023) |
|
| Short circuit current peak prediction based on two-dimensional cloud model |
| CHEN Junjie,MIAO Xiren |
| (School of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350116, China) |
| Abstract: |
| The peak prediction of short circuit current is very important for the realization of selective protection of low voltage system, and it is still lack of in-depth study. By using the early detection technology of short circuit fault, a simulation model of single phase short circuit fault for low voltage system is established. The phase angle of short-circuit fault current is obtained, and the characteristics of short circuit current peak under different phase angles are analyzed. Through the historical data of short circuit fault current, the prediction rule based on conditional cloud generator is constructed, and the peak prediction model of short circuit current based on two-dimensional cloud is established. The experimental results show that the prediction method of short circuit current two-dimensional cloud model can accurately predict the fault current, which can lay the foundation for the realization of low voltage selective protection technology. This work is supported by National Natural Science Foundation of China (No. 51377023). |
| Key words: low-voltage distribution system short-circuit current peak forecasting early fault detection two-dimensional cloud model uncertainty reasoning |
