Study on inertia based MPPT control using reinforcement learning algorithm for extra power production-Reference-Cited by-同舟云学术

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Study on inertia based MPPT control using reinforcement learning algorithm for extra power production

Published:2023-07-19 Issue: Volume: Page:
ISSN:
Container-title:2023 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME)
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Author:

Jargalsaikhan Nyam¹,Byambaa Sergelen²,Masahiro Furukakoi³,Tomonobu Senjyu⁴

Affiliation:

1. University of the Ryukyus,Grad. School of Engineering and Science,Okinawa,Japan

2. Mongolian University of Science and Technology,Department of Electrical Engineering,Ulaanbaatar,Mongolia

3. Sasebo College,National Institute of Technology,Nagasaki,Japan

4. University of the Ryukyus,Faculty of Engineering,Okinawa,Japan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10252163/10252090/10252813.pdf?arnumber=10252813

Reference13 articles.

1. Neural Network Based Reinforcement Learning for Maximum Power Extraction of Wind Energy

2. MPPT Control of a PMSG Connected to the Wind Turbine based on Deep Q-Network

3. Q-Learning based Maximum Power Extraction for Wind Energy Conversion System With Variable Wind Speed

4. Application of Reinforcement Learning Algorithm to Parameter Identification for MPPT Control of PMSG Wind Energy Conversion Systems

5. Control of PMSG-Based Wind Turbine with Virtual Inertia

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