期刊
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
卷 43, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.seta.2020.100958
关键词
I-V curve Analysis; Electrical parameters; Fuzzy logic; Fault identification; Fault classification
Implementing automatic fault diagnostic tools in PV systems can reduce operation and maintenance costs. This paper presents a fuzzy diagnostic algorithm based on electrical parameters classification, aimed at identifying common faults and detecting deviations in measured I-V curves caused by partial shade.
Implementing automatic fault diagnostic tools will contribute to reducing the operations and maintenance costs and duration associated with PV systems. This paper presents a fuzzy diagnostic algorithm relying on the electrical parameters classification which values are extracted from experimental I-V curve measurements of crystalline modules. It is dedicated to the identification of common faults in a power plant, such as uniform dust, partial shade and potential induced degradation using a curve tracer at the system level. The fuzzy processing of the electrical parameters permits recognizing the shape of the characteristic by discerning different signatures of each fault. Also, a novel algorithm is presented to detect the deviation occurred in the measured I-V curve caused by the by-pass activation due to partial shade. It depends on the quadratic and cubic polynomial regression which concavities are highly sensitive to noisy data.
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