Neural Networks and Fuzzy Logic Based Maximum Power Point Tracking Control for Wind Energy Conversion System-Reference-Cited by-同舟云学术

Neural Networks and Fuzzy Logic Based Maximum Power Point Tracking Control for Wind Energy Conversion System

Published:2021-03 Issue:2 Volume:6 Page:586-592
ISSN:2415-6698
Container-title:Advances in Science, Technology and Engineering Systems Journal
language:
Short-container-title:Adv. sci. technol. eng. syst. j.

Author:

Aissaoui Hayat El,Ougli Abdelghani El,Tidhaf Belkassem

Publisher

ASTES Journal

Subject

Management of Technology and Innovation,Physics and Astronomy (miscellaneous),Engineering (miscellaneous)

Link

https://www.astesj.com/publications/ASTESJ_060267.pdf

Reference9 articles.

1. A. Choumane, O. Boukhari, "Wind energy in Algeria: potential and achievements," in International conference on renewable energy strategies and its role in achieving sustainable development.

2. M. Zerouali, M. Boutouba, A. El Ougli and B. Tidhaf, " Control of variable speed wind energy conversion systems by fuzzy logic and conventional P&O," in 2019 International Conference on Intelligent Systems and Advanced Computing Sciences (ISACS), 1-5, IEEE, 2019, doi: 10.1109/ISACS48493.2019.9068866.

3. P. Suresh, B.C. Sujatha, "Maximum Power Point Tracking Of A Hybrid Solar-Wind Power Generation System For A Smart Grid Using Fuzzy Logic Control," International Journal of Scientific & Engineering Research, 7(5), 165-170, 2016.

4. S.S. Dheeban, N.B. Muthu Selvan, C. Senthil Kumar, "Design Of Standalone Pv System," International Journal Of Scientific & Technology Research, 8(11), 2019.

5. I. Duka, C. Noble. " High frequency DC/DC boost converter," submitted to the Faculty of the Worcester Polytechnic Institute in partial fulfillment of the requirements for the Degree of Bachelor of Science in Electrical and Computer Engineering , 2011.

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