By Topic

Power System Stabilizer Design Using an Online Adaptive Neurofuzzy Controller With Adaptive Input Link Weights

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)
Ramirez-Gonzalez, M. ; Dept. of Electr. & Comput. Eng., Univ. of Calgary, Calgary, AB ; Malik, O.P.

A neurofuzzy controller (NFC) with adaptive input link weights (ILWs) and working as an adaptive power system stabilizer is presented. The control structure of the proposed adaptive neurofuzzy power system stabilizers (ANFPSSs) consists of a neuroidentifier to track the dynamic behavior of the plant and an NFC to damp the low-frequency power system oscillations. Usually, the input membership functions (IMFs) and consequent parameters (CPs) are adapted in order to enhance the performance of the NFC. However, the adjustment of IMFs can be realized indirectly by the tuning of ILWs introduced here, which is simpler due to the small number of parameters involved. Therefore, in this paper, ILWs and CPs are updated online by the gradient descent method. Simulation studies over a range of operating conditions and disturbances in a single machine-infinite bus system and a multimachine power system demonstrate the improvement in the dynamic performance of the system with the proposed ANFPSS.

Published in:

Energy Conversion, IEEE Transactions on  (Volume:23 ,  Issue: 3 )