By Topic

Identification of optimal operating point of PV modules using neural network for real time maximum power tracking control

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
$33 $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

3 Author(s)
T. Hiyama ; Dept. of Electr. Eng. & Comput. Sci., Kumamoto Univ., Japan ; S. Kouzuma ; T. Imakubo

This paper presents an application of a neural network for the identification of the optimal operating point of PV modules for the real time maximum power tracking control. The output power from the modules depends on the environmental factors such as insolation, cell temperature, and so on. Therefore, accurate identification of optimal operating point and real time continuous control are required to achieve the maximum output efficiency. The proposed neural network has a quite simple structure and provides a highly accurate identification of the optimal operating point and also a highly accurate estimation of the maximum power from the PV modules

Published in:

IEEE Transactions on Energy Conversion  (Volume:10 ,  Issue: 2 )