H
Hui Li
Researcher at Florida State University
Publications - 219
Citations - 8797
Hui Li is an academic researcher from Florida State University. The author has contributed to research in topics: Inverter & Ćuk converter. The author has an hindex of 42, co-authored 192 publications receiving 7561 citations. Previous affiliations of Hui Li include Pusan National University & Oak Ridge Institute for Science and Education.
Papers
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Journal ArticleDOI
A new ZVS bidirectional DC-DC converter for fuel cell and battery application
TL;DR: In this paper, a new zero-voltage-switching (ZVS) bidirectional dc-dc converter is proposed for medium and high power applications especially for auxiliary power supply in fuel cell vehicles and power generation where the high power density, low cost, lightweight and high reliability power converters are required.
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Coordinated Control of Distributed Energy Storage System With Tap Changer Transformers for Voltage Rise Mitigation Under High Photovoltaic Penetration
TL;DR: The proposed coordinated control of distributed energy storage system with traditional voltage regulators including the on-load tap changer transformers and step voltage regulators to solve the voltage rise problem caused by the high photovoltaic penetration in the low-voltage distribution network.
Journal ArticleDOI
Sizing Strategy of Distributed Battery Storage System With High Penetration of Photovoltaic for Voltage Regulation and Peak Load Shaving
TL;DR: The cost-benefit analysis presented in this paper considers factors of BESS influence on the work stress of voltage regulation devices, load shifting and peaking power generation, as well as individual BESS cost with its lifetime estimation, and determines the cost- benefit size.
Journal ArticleDOI
High-Frequency Transformer Isolated Bidirectional DC–DC Converter Modules With High Efficiency Over Wide Load Range for 20 kVA Solid-State Transformer
Haifeng Fan,Hui Li +1 more
TL;DR: In this paper, a high-frequency transformer isolated bidirectional dc-dc converter modules connected in input-series-output-parallel (ISOP) for 20kVA-solid-state transformer is presented.
Proceedings ArticleDOI
Neural network based sensorless maximum wind energy capture with compensated power coefficient
Hui Li,K.L. Shi,P. G. McLaren +2 more
TL;DR: In this paper, a small wind generation system where neural network principles are applied for wind speed estimation and robust maximum wind power extraction control against potential drift of wind turbine power coefficient curve is described.