A sequential excitation and simplified ant colony optimization based global extreme seeking control method for performance improvement-Reference-Cited by-同舟云学术

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A sequential excitation and simplified ant colony optimization based global extreme seeking control method for performance improvement

Published:2024-04 Issue: Volume:86 Page:101522
ISSN:2210-6502
Container-title:Swarm and Evolutionary Computation
language:en
Short-container-title:Swarm and Evolutionary Computation

Author:

Liu Guangyu^ORCID,Bai Yuwei,Zhu Ling,Wang Qingyun,Zhang Wei

Publisher

Elsevier BV

Reference39 articles.

1. Condition classification and performance of mismatched photovoltaic arrays via a pre-filtered elman neural network decision making tool;Liu;Sol. Energy,2018

2. A novel pso strategy for improving dynamic change partial shading photovoltaic maximum power point tracker;Eltamaly;Energy Sources A,2020

3. A bayesian fusion technique for maximum power point tracking under partial shading condition;Gugulothu;SN Appl. Sci.,2021

4. A novel strategy for optimal pso control parameters determination for pv energy systems;Eltamaly;Sustainability,2021

5. Renewable Energy Devices and Systems with Simulations in MATLAB and ANSYS;Blaabjerg,2017

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