Recent Advances of Wind-Solar Hybrid Renewable Energy Systems for Power Generation: A Review-Reference-Cited by-同舟云学术

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Recent Advances of Wind-Solar Hybrid Renewable Energy Systems for Power Generation: A Review

Published:2022 Issue: Volume:3 Page:81-104
ISSN:2644-1284
Container-title:IEEE Open Journal of the Industrial Electronics Society
language:
Short-container-title:IEEE Open J. Ind. Electron. Soc.

Author:

Roy Pranoy¹^ORCID,He JiangBiao¹^ORCID,Zhao Tiefu²^ORCID,Singh Yash Veer³

Affiliation:

1. Department of Electrical and Computer Engineering, University of Kentucky, Lexington, KY, USA

2. Department of Electrical and Computer Engineering, University of North Carolina at Charlotte, Charlotte, NC, USA

3. Eaton Research Lab, Southfield, MI 48076, USA

Funder

University of Kentucky

L. Stanley Pigman faculty fellowship endowment

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering,Control and Systems Engineering

Link

http://xplorestaging.ieee.org/ielx7/8782706/9667159/09684974.pdf?arnumber=9684974

Reference147 articles.

1. Power Enhancement of an Actively Controlled Battery/Ultracapacitor Hybrid

2. Real-Time Simulation of a Wind Turbine Generator Coupled With a Battery Supercapacitor Energy Storage System

3. Development of hybrid battery–supercapacitor energy storage for remote area renewable energy systems

4. Battery–ultracapacitor hybrids for pulsed current loads: A review

5. Photovoltaic-Wind and Hybrid Energy Storage Integrated Multisource Converter Configuration-Based Grid-Interactive Microgrid

Cited by 109 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. Enhancing energy quality and grid stability with improved adaptive controller for renewable energy conversion systems under weak grid conditions;Electric Power Systems Research;2024-12

2. Adaptive Control for Undisturbed Functioning and Smooth Mode Transition in Utility-Interactive Wind–Solar Based AC/DC Microgrid;IEEE Transactions on Power Electronics;2024-11

3. Analyzing energy transition for industry 4.0-driven hybrid energy system selection with advanced neural network-used multi-criteria decision-making technique;Renewable Energy;2024-10

4. Enhancing the load ramp-up capability of the subcritical CFB power unit by considering the evolution of internal stored energy;Energy;2024-10

5. Deep reinforcement learning based energy management of a hybrid electricity-heat-hydrogen energy system with demand response;Energy;2024-10

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