Title :
Enhancement of anomalous data mining in power system predicting-aided state estimation
Author :
Huang, Shyh-Jier ; Lin, Jeu-Min
Author_Institution :
Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
Abstract :
An approach for predicting-aided state estimation including bad data mining in a power system is proposed in this paper. In the method, the sliding surface-enhanced fuzzy control and optimal cluster numbers estimation techniques are both employed for the enhancement of state estimation. This proposed approach has been applied to test systems. Test results reveal the feasibility of the method for the applications considered.
Keywords :
data mining; fuzzy control; power system control; power system state estimation; anomalous data mining; optimal cluster number estimation techniques; power system predicting-aided state estimation; sliding surface-enhanced fuzzy control; Data mining; Economic forecasting; Filtering; Fuzzy control; Load management; Neural networks; Power system dynamics; Power system modeling; Power systems; State estimation;
Journal_Title :
Power Systems, IEEE Transactions on
DOI :
10.1109/TPWRS.2003.818726
