低压配电系统选择性保护短路电流峰值早期预测的算法研究

在短路故障早期诊断基础上,提出一种基于最小二乘法的低压配电系统短路电流峰值预测计算方法.该方法利用少量电流数据与故障电压初相角进行曲线拟合,可预测出短路电流发展趋势及峰值,使得通过实时在线预测短路电流峰值实现低压配电系统全局选择性保护成为可能.通过C语言编程与Matlab短路故障模型仿真,结果表明,峰值预测方法具有有效性,其精度高、程序运行速度快,且容易在硬件系统上实时实现.最后,给出利用峰值预测实现全局选择性保护方案,为开发具有短路故障早期诊断与选择性保护功能的智能断路器提供参考.

Current Peak Value Prediction of Short-circuit Fault with Selectivity Protection in Low-voltage Distribution System

Short fault diagnosis in low-voltage distribution has great significance and global selectivity protection can further ensure the reliability and continuity of the supply line. A method of short fault current peak value prediction based on least squares theory, which use a small amount of current data and fault initial phase of voltage to predict the current trends and peaks by curve fitting is presented in this paper. It makes global selectivity protection of low voltage distribution systems possible. Through the C programming and MATLAB short circuit fault model simulation, large amounts of data results show that the method is valid. It has high accuracy and easy to implement in real-time hardware system. At the end of this paper, a solution of selectivity protection by current peak value prediction is also proposed. Accordingly, it provides a reference for the development of intelligent breaker with early short fault diagnosis and selectivity protection.