Artificial neural network based Duty Cycle estimation for maximum Power Point tracking in Photovoltaic systems-Reference-Cited by-同舟云学术

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Artificial neural network based Duty Cycle estimation for maximum Power Point tracking in Photovoltaic systems

Published:2015-04 Issue: Volume: Page:
ISSN:
Container-title:SoutheastCon 2015
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Author:

Anzalchi Arash,Sarwat Arif

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/7124301/7132866/07132988.pdf?arnumber=7132988

Cited by 16 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. PV Panel Model Parameter Estimation by Using Particle Swarm Optimization and Artificial Neural Network;Sensors;2024-05-09

2. Enhanced Voltage Regulation in Solar PV Systems using ANN-based MPPT control for DC-DC Converter;2023 3rd Asian Conference on Innovation in Technology (ASIANCON);2023-08-25

3. Application of Hybrid Techniques for Efficient Photovoltaic Systems-An Overview;2023 International Conference on Control, Communication and Computing (ICCC);2023-05-19

4. An advanced intelligent MPPT control strategy based on the imperialist competitive algorithm and artificial neural networks;Evolutionary Intelligence;2023-02-20

5. Maximum Power Point Tracking Techniques for Photovoltaic Systems—A Comprehensive Review From Real‐Time Implementation Perspective;Smart Grids and Green Energy Systems;2022-09-30

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