H
Huafeng Xiao
Researcher at Nanjing University
Publications - 23
Citations - 367
Huafeng Xiao is an academic researcher from Nanjing University. The author has contributed to research in topics: Computer science & Multiplicity (mathematics). The author has an hindex of 1, co-authored 1 publications receiving 311 citations.
Papers
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Journal ArticleDOI
Leakage Current Analytical Model and Application in Single-Phase Transformerless Photovoltaic Grid-Connected Inverter
Huafeng Xiao,Shaojun Xie +1 more
TL;DR: In this article, the leakage current suppressing method, in which all common-mode paths are considered, has been proposed, and the existing full-bridge and half-bridge type converters have been analyzed by using the developed model and rules, and then, a new fullbridge-type converter structure and a compensation strategy for half-branched inverter have been presented finally.
Journal ArticleDOI
A Highly Reliable Three-Level Neutral-Point-Clamped Inverter With Anti-Shoot-Through Capability
TL;DR: In this paper , a split-induction hybrid inverter with anti-shoot-through capability is proposed to suppress the short-circuited current in neutral-point-clamped inverters.
Journal ArticleDOI
Infinitely many solutions for the discrete Schrödinger equations with a nonlocal term
Qilin Xie,Huafeng Xiao +1 more
TL;DR: In this paper , the Schrödinger equations were considered in the context of discrete Schröding equations, where the potentials of the potential are two positive constants, i.e., a positive constant and a negative constant.
An Equivalent Differential Method for Active Damping of LCL Type Grid-Connected Inverters With Grid-Side Inductor Voltage Feedback
TL;DR: In this paper , a band-pass filter in series with a lead compensation unit was proposed to replace the ideal differential around the resonance frequency band, which features lower gain at low and high frequency bands.
Proceedings ArticleDOI
Research on Edge Diagnosis Method of UHVDC Commutation Failure Based on LSTM Neural Network
TL;DR: Wang et al. as discussed by the authors proposed a commutation failure diagnosis method based on wavelet energy entropy and long short-term memory (LSTM) neural network to diagnose and trace fault recording data at UHVDC station.