Faults often occur in photovoltaic arrays which work in the natural environment. Locating and classifying the faults timely is of great significance to improve the operating level of photovoltaic power stations. Aiming at several common faults (short circuit, open circuit and partial occlusion) of photovoltaic array, a new method of photovoltaic array fault diagnosis using operation data and combining fuzzy C-means (FCM) algorithm and fuzzy membership (FM) algorithm is proposed in this paper. Firstly, the occurrence mechanism of typical faults of PV array is carried out, and the fault feature parameters are extracted. Then, the FCM algorithm is used to classify the fault samples of PV array and the clustering centers of various faults are obtained. Finally, the FM algorithm is used to calculate the membership degree of the fault data about the clustering centers and determine the fault types. The simulation and experimental tests are both adopted to verify effectiveness of the methods. The results show that the proposed fault diagnosis method can effectively identify the typical faults of PV array and the diagnostic results are accurate and reliable.
WEI Zi-jie
,
LI Ai-wu
,
SHAO Shuai
,
HU Yang
,
ZHU Hong-lu
. Fault Diagnosis of PV Array Based on FCM-FM Algorithm[J]. Advances in New and Renewable Energy, 2018
, 6(4)
: 297
-303
.
DOI: 10.3969/j.issn.2095-560X.2018.04.007
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