Global maximum power point tracking for solar power systems using the hybrid artificial fish swarm algorithm-Reference-Cited by-同舟云学术

Global maximum power point tracking for solar power systems using the hybrid artificial fish swarm algorithm

Published:2019-08 Issue:4 Volume:2 Page:351-360
ISSN:2096-5117
Container-title:Global Energy Interconnection
language:en
Short-container-title:Global Energy Interconnection

Author:

Li Jianpo,Dong Pengwei

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology,Automotive Engineering,Renewable Energy, Sustainability and the Environment,Control and Systems Engineering

Reference16 articles.

1. Geothermal-solar combined organic rankine cycle power generation technology research;Hu;Journal of Northeast Dianli University,2015

2. Maximum power point tracking (MPPT) techniques: Recapitulation in solar photovoltaic systems;Verma;Renewable & Sustainable Energy Reviews,2016

3. Efficient photovoltaic system maximum power point tracking using a new technique;Seyedmahmoudian;Energies,2016

4. Open- and Short- Circuit fault identification for a boost dc/dc converter in PV MPPT systems;Trejo;Energies,2018

5. Optimization of perturb and observe maximum power point tracking method;Femia;IEEE Transactions on Power Electronics,2005

Cited by 9 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. Multi Peak MPPT Algorithm Based on Improving Cuckoo Search;2023 IEEE 18th Conference on Industrial Electronics and Applications (ICIEA);2023-08-18

2. Maximum power point tracking of photovoltaic power generation based on improved fuzzy control and conductance increment method;Clean Energy;2022-10-01

3. Two fast metaheuristic-based MPPT techniques for partially shaded photovoltaic system;International Journal of Electrical Power & Energy Systems;2022-05

4. Study on Intelligent Optimization Model of Porous Hydraulic Buffer;International Journal of Fluid Power;2022-03-16

5. Design of Automated Deep Learning-Based Fusion Model for Copy-Move Image Forgery Detection;Computational Intelligence and Neuroscience;2022-01-31