Dynamic global power extraction from partially shaded photovoltaic using deep recurrent neural network and improved PSO techniques-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Dynamic global power extraction from partially shaded photovoltaic using deep recurrent neural network and improved PSO techniques

Published:2019-06-17 Issue:9 Volume:29 Page:
ISSN:2050-7038
Container-title:International Transactions on Electrical Energy Systems
language:en
Short-container-title:Int Trans Electr Energ Syst

Author:

Farh Hassan M.H.¹²^ORCID,Eltamaly Ali M.³⁴^ORCID,Ibrahim Ahmed B.⁵,Othman Mohd F.²,Al‐Saud Mamdooh S.¹⁶

Affiliation:

1. Electrical Engineering Department, College of EngineeringKing Saud University Riyadh 11421 Saudi Arabia

2. Malaysia‐Japan International Institute of TechnologyUniversiti Teknologi Malaysia Kuala Lumpur Malaysia

3. Sustainable Energy Technologies CenterKing Saud University Riyadh 11421 Saudi Arabia

4. Electrical Engineering DepartmentMansoura University Mansoura Egypt

5. KACST‐TIC in Radio Frequency and Photonics for the e‐Society (RFTONICS)King Saud University Riyadh 11421 Saudi Arabia

6. Saudi Electricity Company Chair in Power System Reliability and SecurityKing Saud University Riyadh 11421 Saudi Arabia

Funder

Deanship of Scientific Research, King Saud University

Publisher

Hindawi Limited

Subject

Electrical and Electronic Engineering,Energy Engineering and Power Technology,Modeling and Simulation

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/2050-7038.12061

Reference45 articles.

1. Maximum Power Extraction from a Partially Shaded PV System Using an Interleaved Boost Converter

2. A novel evaluation index for the photovoltaic maximum power point tracker techniques

3. An overview of high voltage conversion ratio DC-DC converter configurations used in DC micro-grid architectures

4. Modified Particle Swarm Optimization technique based Maximum Power Point Tracking for uniform and under partial shading condition

5. Efficient solution of the DC-link hard switching inverter of the PV system

Cited by 27 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. Recurrent neural network based design of fractional order power system stabilizer for effective damping of power oscillations in multimachine system;Engineering Applications of Artificial Intelligence;2023-11

2. New Hybrid MPPT Technique Including Artificial Intelligence and Traditional Techniques for Extracting the Global Maximum Power from Partially Shaded PV Systems;Sustainability;2023-07-11

3. A novel constraint‐based improved equilibrium optimization for global peak tracking of photovoltaic system under complex shading conditions;International Journal of Circuit Theory and Applications;2023-01-26

4. Power quality improvement for microgrid-connected PV-based converters under partial shading conditions using mixed optimisation algorithms;International Journal of Bio-Inspired Computation;2023

5. Maximum power extraction and DC-Bus voltage regulation in grid-connected PV/BES system using modified incremental inductance with a novel inverter control;Scientific Reports;2022-11-19

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3