Diagnostic method for photovoltaic systems based on light I–V measurements

Spataru, Sergiu; Séra, Dezső; Kerekes, Tamás; Teodorescu, Remus

doi:10.1016/j.solener.2015.06.020

Cited by 107 publications

(48 citation statements)

References 38 publications

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“…In another study diagnostic parameters and fuzzy logic rules are developed based on system currentvoltage characteristics. These were used to detect different fault types, such as shading problems, losses in series resistance and degradation potentials [33]. The advantages of fuzzy logic are no required accurate description of the system to be controlled and no need to compensate for wide parameter variations which is unlike the standard regulators.…”

Section: Hybrid Computational Techniquesmentioning

confidence: 99%

Review on Methods of Fault Diagnosis in Photovoltaic System Applications

Syafaruddin¹,

Zinger²

2019

JESTR

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Recently, detection and identification of faults in photovoltaic (PV) system applications have been attracting researchers worldwide. Some of them have investigated the causes of potential faults, have worked on how to monitor and identify the faults through fault diagnosis, and have elaborated on how to develop problem-solving methods for the early detection of faults in PV system operations. This paper attempts to provide information comprehensively from the previous research. It summarizes types of faults, methods used in early fault identification and monitoring, and PV fault prevention and protection systems. The paper also investigates future trends in PV system fault diagnosis which include real-time implementation. The paper is expected to bring new perspective about the literature associate with fault studies in PV systems. This survey will be beneficial for the future discussion on how to provide comprehensive solutions for PV system fault problems. It will help avoid research repetition on similar topics and focus on the improvement and performance development of PV fault diagnosis methods.

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Section: Hybrid Computational Techniquesmentioning

confidence: 99%

Review on Methods of Fault Diagnosis in Photovoltaic System Applications

Syafaruddin¹,

Zinger²

2019

JESTR

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“…The fill factor (FF) is a generic diagnostic indicator which is sensitive to power losses due to shading and faulty conditions occurring in PV systems [27]. FF is sufficiently robust to the irradiance change and the temperature levels.…”

Section: Fill Factor (Ff)mentioning

confidence: 99%

Seven indicators variations for multiple PV array configurations under partial shading and faulty PV conditions

et al. 2017

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The goal of this paper is to model, compare and analyze the performance of multiple photovoltaic (PV) array configurations under various partial shading and faulty PV conditions. For this purpose, a multiple PV array configurations including series (S), parallel (P), series-parallel (SP), total-cross-tied (TCT) and bridge-linked (BL) are carried out under several partial shading conditions such as, increase or decrease in the partial shading on a row of PV modules and increase or decrease in the partial shading on a column of PV modules. Additionally, in order to test the performance of each PV configuration under faulty PV conditions, from 1 to 6 Faulty PV modules have been disconnected in each PV array configuration. Several indicators such as short circuit current (I sc ), current at maximum power point (I mpp ), open circuit voltage (V oc ), voltage at maximum power point (V mpp ), series resistance (R s ), fill factor (FF) and thermal voltage (V te ) have been used to compare the obtained results from each partial shading and PV faulty condition applied to the PV system. MATLAB/Simulink software is used to perform the simulation and the analysis for each examined PV array configuration.

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“…The methods presented in [6,14] are simple and can detect shading faults, but they are not able to identify and classify the type of shading patterns. The shading faults can also be detected with artificial neural network (ANN) and fuzzy classifier system as described in [15,16]. The main disadvantage of these techniques is that the rules must be designed for each system.…”

Section: Introductionmentioning

confidence: 99%

Data-driven approach for isolated PV shading fault diagnosis based on experimental I-V curves analysis

Fadhel

Migan²,

Delpha

et al. 2018

2018 IEEE International Conference on Industrial Technology (ICIT)

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This paper deals with a data-driven fault diagnosis method for photovoltaic (PV) system. The proposed method is based on the Principal Component Analysis (PCA) to detect and identify different shading types. The PCA uses the current-voltage (I-V) curves that are experimentally determined for a monocrystalline PV module of 250Wc. The experimental tests were carried out for several shading patterns covering the PV cells. For the diagnosis process, three features (current, voltage and power of PV module) are extracted for each test to build the database which is then analyzed through the PCA algorithm. Simulation results using the experimental data, prove the efficiency of the proposed method in terms of discrimination. The healthy data are clearly separated from the faulty ones despite sudden irradiation variations.

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Diagnostic method for photovoltaic systems based on light I–V measurements

Cited by 107 publications

References 38 publications

Review on Methods of Fault Diagnosis in Photovoltaic System Applications

Review on Methods of Fault Diagnosis in Photovoltaic System Applications

Seven indicators variations for multiple PV array configurations under partial shading and faulty PV conditions

Data-driven approach for isolated PV shading fault diagnosis based on experimental I-V curves analysis

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