By Topic

Analysis of torsional oscillations using an artificial neural network

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Hsu, Yuan-Yih ; Dept. of Electr. Eng., Nat. Taiwan Univ., Taipei, Taiwan ; Lin-Her Jeng

A novel approach using an artificial neural network (ANN) is proposed for the analysis of torsional oscillations in a power system. In the ANN those system variables, such as generator loadings and the capacitor compensation ratio, which have major impact on the damping characteristics of torsional oscillation modes were used as the inputs. The outputs of the neural net provided the desired eigenvalues for torsional modes. Once the connection weights of the neural network have been learned using a set of training data derived offline, the neural network can be applied to torsional analysis in real-time situations. To demonstrate the effectiveness of the proposed neural net, torsional analysis was performed on the IEEE First Benchmark Model. It is concluded from the test results that accurate assessment of the torsional mode eigenvalues can be achieved by the neural network in a very efficient manner

Published in:

Energy Conversion, IEEE Transactions on  (Volume:7 ,  Issue: 4 )