By Topic

A combined artificial neural network-fuzzy dynamic programming approach to reactive power/voltage control in a distribution substation

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 ; Feng-Chang Lu

Reactive power/voltage control in a distribution substation is investigated in this work. The purpose is to determine proper capacitor on/off status and suitable load tap changer (LTC) positions for the 24 hours in the next day. To reach this goal, an artificial neural network (ANN) is designed to reach a preliminary dispatch schedule for the capacitor and LTC. The inputs to the ANN are main transformer real power and reactive power and primary and secondary bus voltages and the outputs are the desired capacitor on/off status and LTC tap positions. The preliminary dispatch schedule is further refined by fuzzy dynamic programming in order to reach the final schedule. To demonstrate the effectiveness of the proposed method, reactive power/voltage control is performed on a distribution substation in Taipei, Taiwan. Results from the example show that a proper dispatch schedule for capacitor and LTC can be reached by the proposed method in a very short period

Published in:

Power Systems, IEEE Transactions on  (Volume:13 ,  Issue: 4 )