Fault detection of photovoltaic array based on Grubbs criterion and local outlier factor
| Autor: | Yuanliang Li, Kun Ding, Chen Fudong, Ding Hanxiang, Liu Yongjie, Jingwei Zhang |
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| Rok vydání: | 2020 |
| Předmět: |
Local outlier factor
Renewable Energy Sustainability and the Environment Computer science 020209 energy 020208 electrical & electronic engineering Photovoltaic system String (computer science) 02 engineering and technology Fault (power engineering) Fault detection and isolation Reduction (complexity) Reachability 0202 electrical engineering electronic engineering information engineering False alarm Algorithm |
| Zdroj: | IET Renewable Power Generation. 14:551-559 |
| ISSN: | 1752-1424 1752-1416 |
| DOI: | 10.1049/iet-rpg.2019.0957 |
| Popis: | Aiming at improving the effectiveness and real-time performance of the fault detection of the photovoltaic (PV) array under different outdoor conditions, a novel method based on Grubbs criterion and local outlier factor (G-LOF) method is proposed in this study. The simulation model of the PV array is built to obtain the reference current of each PV string. The local outlier factor (LOF) is a ratio of the average local reachability density of sample neighbourhoods relative to its local reachability density. In this study, the LOF is used to quantify the abnormality by comparing the measured current and the simulated reference current. To reduce the false alarm probability of LOF, the Grubbs criterion is utilised as the test criterion to detect the abnormality of PV strings and it is merged with the LOF to derivate the G-LOF. The experiments of partial shading, open-circuit fault and short-circuit fault of PV modules are implemented in sunny and cloudy days. 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. |
| Databáze: | OpenAIRE |
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