PV array fault DiagnosticTechnique for BIPV systems

Hachana, Oussama; Tina, Giuseppe Marco; Hemsas, Kamel Eddine

doi:10.1016/j.enbuild.2016.05.031

Cited by 62 publications

(37 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Under practical conditions, faults are unavoidable in PV systems, particularly on the direct current (DC) side where open circuit faults, short circuits faults, hotspot faults, and total and partial shading faults are possible (Chouder and Silvestre, 2010;Hachana et al, 2016;Silvestre et al, 2015;Yahyaoui and Segatto, 2017). Faults on the DC side of PV systems can result in energy loss, system shutdown and even in serious safety breaches (Brooks, 2011;Alam et al, 2015).…”

Section: The State Of the Artmentioning

confidence: 99%

Statistical fault detection in photovoltaic systems

et al. 2017

View full text Add to dashboard Cite

Faults in photovoltaic (PV) systems, which can result in energy loss, system shutdown or even serious safety breaches, are often difficult to avoid. Fault detection in such systems is imperative to improve their reliability, productivity, safety and efficiency. Here, an innovative model-based fault-detection approach for early detection of shading of PV modules and faults on the direct current (DC) side of PV systems is proposed. This approach combines the flexibility, and simplicity of a one-diode model with the extended capacity of an exponentially weighted moving average (EWMA) control chart to detect incipient changes in a PV system. The one-diode model, which is easily calibrated due to its limited calibration parameters, is used to predict the healthy PV array’s maximum power coordinates of current, voltage and power using measured temperatures and irradiances. Residuals, which capture the difference between the measurements and the predictions of the one-diode model, are generated and used as fault indicators. Then, the EWMA monitoring chart is applied on the uncorrelated residuals obtained from the one-diode model to detect and identify the type of fault. Actual data from the grid-connected PV system installed at the Renewable Energy Development Center, Algeria, are used to assess the performance of the proposed approach. Results show that the proposed approach successfully monitors the DC side of PV systems and detects temporary shading.Peer ReviewedPostprint (author's final draft

show abstract

Section: The State Of the Artmentioning

confidence: 99%

Statistical fault detection in photovoltaic systems

et al. 2017

View full text Add to dashboard Cite

show abstract

“…Thermal stress as well as mechanical stresses such as shear and normal stress are potential causes of faults that need to be studied to provide a theoretical basis for PV module reliability [9]. Because PV rooftop installations have limited access for inspection and maintenance, a fault diagnostic method for these systems is compulsory in order to avoid potential faults in every section of the installation [10]. Fires in rooftop building integrated PV systems have occurred because of undetected ground faults found in fuse-based protection systems [11].…”

Section: Introductionmentioning

confidence: 99%

Review on Methods of Fault Diagnosis in Photovoltaic System Applications

Syafaruddin¹,

Zinger²

2019

JESTR

View full text Add to dashboard Cite

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.

show abstract

“…In comparison with the three aforementioned fault detection methods, electrical methods based on statistical signal and processing approaches [6][7][8], power losses analysis [9][10][11], I-V characteristic analysis [12][13][14], and voltage-current measurements [15][16][17][18][19][20] are found to be more advantageous and promising [4]. These electrical methods can be used to investigate numerous faults in PV systems such as short-circuit faults, open-circuit faults, shading conditions, degradation faults, the line to line faults, bypass diode faults, DC arc faults, bridging faults, MPPT errors, and others.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Photovoltaic String Failure and Health Monitoring with Module Fault Identification

et al. 2019

View full text Add to dashboard Cite

In this paper, photovoltaic (PV) string failure analysis and health monitoring of PV modules based on a low-cost self-powered wireless sensor network (WSN) are presented. Simple and effective fault detection and diagnosis method based on the real-time operating voltage of PV modules is proposed. The proposed method is verified using the developed health monitoring system which is installed in a grid-connected PV system. Each of the PV modules is monitored via WSN to detect any individual faulty module. The analysis of PV string failure includes several electrical fault scenarios and their impact on the PV string characteristics. The results show that a degraded or faulty module exhibits low operating voltage as compared to the normal module. The developed health monitoring system also includes a graphical user interface (GUI) program which graphically displays the real-time operating voltage of each module with colors and thus helping users to identify the faulty modules easily. The faulty modules identification approach is further validated using the PV module electroluminescence (EL) imaging system.

show abstract

PV array fault DiagnosticTechnique for BIPV systems

Cited by 62 publications

References 31 publications

Statistical fault detection in photovoltaic systems

Statistical fault detection in photovoltaic systems

Review on Methods of Fault Diagnosis in Photovoltaic System Applications

Analysis of Photovoltaic String Failure and Health Monitoring with Module Fault Identification

Contact Info

Product

Resources

About