Fault detection and diagnosis methods for photovoltaic systems: A review

Mellit, A.; Tina, Giuseppe Marco; Kalogirou, Soteris A.

doi:10.1016/j.rser.2018.03.062

Cited by 404 publications

(208 citation statements)

References 95 publications

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“…There are two main types of fault diagnosis strategies for DC side in PV plant [4,5]. The first type methods rely on the test equipment for PV modules/arrays.…”

Section: Introductionmentioning

confidence: 99%

A Photovoltaic Array Fault Diagnosis Method Considering the Photovoltaic Output Deviation Characteristics

Zhao¹,

Sun²,

Zhou³

et al. 2020

International Journal of Photoenergy

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There are a large number of photovoltaic (PV) arrays in large-scale PV power plants or regional distributed PV power plants, and the output of different arrays fluctuates with the external conditions. The deviation and evolution information of the array output are easily covered by the random fluctuations of the PV output, which makes the fault diagnosis of PV arrays difficult. In this paper, a fault diagnosis method based on the deviation characteristics of the PV array output is proposed. Based on the current of the PV array on the DC (direct current) side, the deviation characteristics of the PV array output under different arrays and time series are analyzed. Then, the deviation function is constructed to evaluate the output deviation of the PV array. Finally, the fault diagnosis of a PV array is realized by using the probabilistic neural network (PNN), and the effectiveness of the proposed method is verified. The main contributions of this paper are to propose the deviation function that can extract the fault characteristics of PV array and the fault diagnosis method just using the array current which can be easily applied in the PV plant.

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“…There are two main types of fault diagnosis strategies for DC side in PV plant [4,5]. The first type methods rely on the test equipment for PV modules/arrays.…”

Section: Introductionmentioning

confidence: 99%

A Photovoltaic Array Fault Diagnosis Method Considering the Photovoltaic Output Deviation Characteristics

Zhao¹,

Sun²,

Zhou³

et al. 2020

International Journal of Photoenergy

View full text Add to dashboard Cite

show abstract

“…In PV systems it is extremely important to identify situations where the operating conditions change. These cases are called "faults", they are either system-based or environmental factors based [2,3]. Because these types of conditions, which can be called as bad working conditions, can seriously affect the produced energy yield, system efficiency, as well as the security and reliability of the entire system in case of them not being detected and corrected [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, many studies have been proposed for the fault diagnosis of PV systems. These studies generally differ in terms of main features such as rapid fault detection, required input data, and the separability of different faults [3]. Faults can be mainly grouped into two categories as to be visual and thermal methods, and electrical methods [7].…”

Section: Introductionmentioning

confidence: 99%

Photovoltaic Fault Detection and Classification Using Common Vector Approach Based on I-V Curve

Turhal

Onal

2020

Acta Phys. Pol. A

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Photovoltaic systems are subject to various faults. These faults result in significant degradation in photovoltaic system performances. These degradations result in a significant reduction in system efficiency as a result of increase in operating costs and times of exclusion of the photovoltaic system. Therefore, health monitoring and high accuracy error detection are extremely important for a photovoltaic system. In this study, fault detection and classification in photovoltaic systems are performed by using common vector approach which is first proposed in the literature for speech recognition and then is applied for face recognition. The faulty conditions discussed in the study are partial shading and series resistance degradation. In both fault detection situations, the common vector approach method is used to determine the type of fault using simulation data obtained under healthy operation and faulty operation conditions and very high fault detection rates are obtained. In order to evaluate the accuracy of the proposed method, the data obtained are also evaluated with the principal component analysis method, which is previously presented for photovoltaic system fault detection in the literature. According to the results obtained, principal component analysis method completely fails in case of serial resistance degradation fault. However, by using common vector approach method proposed in this study, a very high fault detection rate such as 97.5% can be obtained in serial resistance degradation fault. Likewise, in the case of partial shading, higher fault detection rate is achieved in common vector approach method (99.6%) compared to principal component analysis method (95.4%).

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“…Faults in PV plant components (i.e., modules, converters, connection lines), in addition to downtime correlated penalties, could result in an acceleration of system aging and as a consequence in a reduction of power plant reliability [4]. Typically, faults severity depends on various factors.…”

Section: Introductionmentioning

confidence: 99%

Complex Network Analysis of Photovoltaic Plant Operations and Failure Modes

Bonacina

Corsini

Cardillo³

et al. 2019

Energies

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This paper presents a novel data-driven approach, based on sensor network analysis in Photovoltaic (PV) power plants, to unveil hidden precursors in failure modes. The method is based on the analysis of signals from PV plant monitoring, and advocates the use of graph modeling techniques to reconstruct and investigate the connectivity among PV field sensors, as is customary for Complex Network Analysis (CNA) approaches. Five month operation data are used in the present study. The results showed that the proposed methodology is able to discover specific hidden dynamics, also referred to as emerging properties in a Complexity Science perspective, which are not visible in the observation of individual sensor signal but are closely linked to the relationships occurring at the system level. The application of exploratory data analysis techniques on those properties demonstrated, for the specific plant under scrutiny, potential for early fault detection.

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Fault detection and diagnosis methods for photovoltaic systems: A review

Cited by 404 publications

References 95 publications

A Photovoltaic Array Fault Diagnosis Method Considering the Photovoltaic Output Deviation Characteristics

A Photovoltaic Array Fault Diagnosis Method Considering the Photovoltaic Output Deviation Characteristics

Photovoltaic Fault Detection and Classification Using Common Vector Approach Based on I-V Curve

Complex Network Analysis of Photovoltaic Plant Operations and Failure Modes

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