Neural Network Application to the Bad Data Detection Using Autoregressive filter in Power System

AR 필터에 의한 전력계통의 불량데이타검출에서 신경회로망의 응용

In the power system state estimation, the J(x)-index test and normalized residuals $r_N$ have been used to detect the presence of bad measurements and identify their location. But, these methods require the complete re-estimation of system states whenever bad data is identified. This paper presents back-propagation neural network model using autoregressive filter for identification of bad measurements. The performances of neural network method are compared with those of conventional methods and simulation results show the good performance in the bad data identification based on the neural network under sample power system.