Title :
Estimation of line flows and bus voltages using decision trees
Author :
Yang, Chien-Chun ; Hsu, Yuan-Yih
Author_Institution :
Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan
fDate :
8/1/1994 12:00:00 AM
Abstract :
A machine learning method called the ID3 (Interative Dichotomizer 3) approach is presented for the estimation of line flows and bus voltages following an outage event. A decision tree which is capable of generating the desired line flows and bus voltages are created using the training patterns which are compiled from the historical operating records of Taiwan power system. The established decision tree contains the knowledge which is essential for line flow and bus voltage prediction. Thus, it can be applied to estimate line flows and bus voltages of a system in an efficient manner. The effectiveness of the proposed ID3 approach is demonstrated by security assessment of Taiwan power system which contains 170 buses and 207 lines
Keywords :
decision theory; learning (artificial intelligence); load flow; neural nets; parameter estimation; power system analysis computing; power system control; power system protection; trees (mathematics); ID3 approach; Interative Dichotomizer 3 approach; Taiwan power system; artificial neural network; bus voltages estimation; decision trees; historical operating records; line flows estimation; machine learning method; outage event; security assessment; training patterns; Artificial neural networks; Decision trees; Expert systems; Learning systems; Machine learning; Power engineering and energy; Power system security; Senior members; Student members; Voltage;
Journal_Title :
Power Systems, IEEE Transactions on
