复杂智能电网畸变信号故障检测与恢复仿真研究

Simulation of Fault Detection and Restoration for Distortion Signal in Complex Smart Grid

以解决当前电网畸变信号故障检测与恢复方法中存在的检测率和恢复系数低问题为目的,提出基于瞬时频率的复杂智能电网畸变信号故障检测与恢复方法。利用深度优先搜索法对电网中开关层畸变信号故障进行检测,采用Petri模型对电网中馈线层畸变信号故障进行检测。通过粗糙集理论对电网中变电站层畸变信号故障进行检测。基于检测出的电网总畸变信号,分析故障信号瞬时频率和原信号频率之间的关系,得到信号重采样的时间间隔,据此设定一个整数值,将瞬时频率转换为恒定值,并利用三次样条函数插值方式完成畸变信号重采样,获取恢复之后的电网信号。实验结果表明,所提方法电网畸变故障恢复系数平均为0. 93,故障检测率较高。上述方法具有很强的检测性能,实用性优于当前方法。

In order to solve low detection rate and low restitution coefficient in current fault detection and recovery method for power grid distortion signal,a method to detect and recover fault of complex smart grid distortion signal based on instantaneous frequency was proposed.At first,the depth-first search method was used to detect the fault of distortion signal at the switch layer of power grid.Then,the Petri model was adopted to detect the distortion signal fault at the feeder line layer of power grid.Moreover,the rough set theory was used to detect the distortion signal fault at the substation layer of power grid.Based on the detected total distortion signal of power grid,the relationship between the instantaneous frequency of.fault signal and the frequency of original signal was analyzed and the time interval for signal resample was obtained.Finally,an integer value was set to change the instantaneous frequency into the constant value,and the cubic spline function interpolation method was used to complete distortion signal resampie.Thus,the grid signal after recovery was obtained.Simulation results s.how that,through the proposed method, the average restitution coefficient of power grid distortion fault is 0.93,and the fault detection rate is high.Meanwhile,this method has strong detection performance.The practicality is better than that of current method.