Kun Ding
Hohai University
11 Papers
6 Citations
Kun Ding is an academic researcher from Hohai University. The author has contributed to research in topics: Computer science & Fault (power engineering). The author has an hindex of 5, co-authored 11 publications.
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Papers
Fault diagnosis approach for photovoltaic array based on the stacked auto-encoder and clustering with I-V curves
TL;DR: A fault diagnosis method is proposed for photovoltaic array based on stacked auto-encoder and clustering algorithm, which can automatically extract features and use a small number of labeled data samples to mine data sample features for fault diagnosis.
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A fault diagnosis method for photovoltaic arrays based on fault parameters identification
TL;DR: The proposed fault diagnosis method can identify the parameters of up to three concurrent faults, including partial shading, short circuit, and increased series-resistance losses, under good irradiance condition with high accuracy.
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Local outlier factor-based fault detection and evaluation of photovoltaic system
Ding Hanxiang,Kun Ding,Jingwei Zhang,Wang Yue,Gao Lie,Yuanliang Li,Chen Fudong,Zhixiong Shao,Wanbin Lai +8 more
TL;DR: The results of experiments reveal that the modified LOF has good performance in fault detection and fault degree evaluation in different scales of the PV systems.
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A reinforcement learning based approach for on-line adaptive parameter extraction of photovoltaic array models
TL;DR: In this paper, a reinforcement learning (RL) based approach for on-line adaptive parameter extraction of PV array models is proposed, including the ideality factor, series and shunt resistance, and the compensated irradiance for the uncalibrated pyranometer.
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Fault detection of photovoltaic array based on Grubbs criterion and local outlier factor
TL;DR: Experimental results verify that the proposed G-LOF method can sensitively detect above abnormalities, especially can detect the slight performance reduction caused by the partial shading or faults.
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