Title :
Artificial neural network enhanced by gap statistic algorithm applied for bad data detection of a power system
Author :
Huang, Shyh-Jier ; Lin, Jeu-Min
Author_Institution :
Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
Abstract :
In this paper, a gap statistic algorithm (GSA) is applied for the bad data analysis. In the method, GSA is employed for the enhancement of neural networks. Because the number of cluster can be determined via GSA more effectively, this integrated approach is beneficial for the localization of the group of bad data. The proposed approach was validated through the data collected from the operation of a power system. Test results pointed to the feasibility of the method for the applications considered.
Keywords :
neural nets; power system analysis computing; power system parameter estimation; statistical analysis; artificial neural network; bad data analysis; bad data detection; bad data localisation; gap statistic algorithm; neural networks enhancement; power system; Application software; Artificial neural networks; Neural networks; Pollution measurement; Power system analysis computing; Power system measurements; Power system reliability; Power systems; State estimation; Statistics;
Conference_Titel :
Transmission and Distribution Conference and Exhibition 2002: Asia Pacific. IEEE/PES
Print_ISBN :
0-7803-7525-4
DOI :
10.1109/TDC.2002.1177571
