Online Evolutionary Maximum Power Point Tracking for Photovoltaic Grid-connected System-Reference-Cited by-同舟云学术

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Online Evolutionary Maximum Power Point Tracking for Photovoltaic Grid-connected System

Published:2023-05-12 Issue: Volume: Page:
ISSN:
Container-title:2023 IEEE 6th International Electrical and Energy Conference (CIEEC)
language:
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Author:

Tian Luyu¹,Dong Chaoyu²,Xiong Bingyu³,Li Xiangke⁴,Mu Yunfei¹,Jia Hongjie¹

Affiliation:

1. School of Electrical and Information Engineering, Tianjin University,Tianjin,China,300072

2. Nanyang Technological University,Agency for Science, Technology and Research,Singapore,639798

3. School of Automation, Wuhan University of Technology,Wuhan,China,430072

4. The Hong Kong Polytechnic University,Department of Electrical Engineering,Hong Kong,China

Funder

NSFC

EPSRC

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10165685/10164836/10166548.pdf?arnumber=10166548

Reference14 articles.

1. Fuzzy cognitive network-based maximum power point tracking using a self-tuned adaptive gain scheduled fuzzy proportional integral derivative controller and improved artificial neural network-based particle swarm optimization

2. Perturbation observer based fractional-order PID control of photovoltaics inverters for solar energy harvesting via Yin-Yang-Pair optimization

3. Perturbation observer based fractional-order sliding-mode controller for MPPT of grid-connected PV inverters: Design and real-time implementation

4. Passive Fractional-order Proportional-Integral-Derivative control design of a Grid-connected Photovoltaic inverter for Maximum Power Point Tracking

5. Energy reshaping based passive fractional-order PID control design and implementation of a grid-connected PV inverter for MPPT using grouped grey wolf optimizer

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