$V_{\text{cp}}$-Decomposition-Based Adaptive Search for Optimal Power Extraction in Photovoltaic Systems-Reference-Cited by-同舟云学术

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$V_{\text{cp}}$-Decomposition-Based Adaptive Search for Optimal Power Extraction in Photovoltaic Systems

Published:2024-10 Issue:10 Volume:39 Page:12794-12802
ISSN:0885-8993
Container-title:IEEE Transactions on Power Electronics
language:
Short-container-title:IEEE Trans. Power Electron.

Author:

Ma Jieming¹^ORCID,Wang Kangshi¹^ORCID,Huang Ming¹^ORCID,Chen Xiaoyang¹^ORCID,Li Xingshuo²^ORCID,Hughes Danny³

Affiliation:

1. School of Advanced Technology, AI University Research Center, Xi'an Jiaotong-Liverpool University, Suzhou, China

2. School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing, China

3. Department of Computer Science, EU Leuven, Leuven, Belgium

Funder

Suzhou Science and Technology Project-Key Industrial Technology Innovation

XJTLU Postgraduate Research Scholarship

XJTLU AI University Research Centre

Jiangsu Province Engineering Research Centre of Data Science and Cognitive Computation at XJTLU

SIP AI innovation platform

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/63/10659244/10586791.pdf?arnumber=10586791

Reference22 articles.

1. A study on the feasibility of using solar radiation energy and ocean thermal energy conversion to supply electricity for offshore oil and gas fields in the Caspian Sea

2. Improved drift-free P&O MPPT method to enhance energy harvesting capability for dynamic operating conditions of fuel cells

3. A Reinforcement Learning-Based Maximum Power Point Tracking Method for Photovoltaic Array

4. Self-Tuning MPPT Scheme Based on Reinforcement Learning and Beta Parameter in Photovoltaic Power Systems

5. A High-Performance Global Maximum Power Point Tracker of PV System for Rapidly Changing Partial Shading Conditions

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