Diagnose Algorithm and Fault Characterization for Photovoltaic Arrays: A Simulation Study

Murillo-Soto, Luis Diego; Meza, Carlos

doi:10.1007/978-3-030-37161-6_43

Cited by 5 publications

(4 citation statements)

References 20 publications

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“…It should be noticed that V max is the higher voltage in the string, and it belongs to the module with less degradation. This criterion is simple to incorporate into other fault detection proposals that use differential voltages as input signals such as [44,45].…”

Section: Discussionmentioning

confidence: 99%

Detection Criterion for Progressive Faults in Photovoltaic Modules Based on Differential Voltage Measurements

Murillo-Soto

Meza

2022

Applied Sciences

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PV modules may experience degradation conditions that affect their power efficiency and affect the rest of the PV array. Based on the literature review, this paper links the parameter variation on a PV module with the six most common degradation faults, namely, series resistance degradation, optical homogeneous degradation, optical heterogeneous degradation, potential induced degradation, micro-cracks, and light-induced degradation. A Monte Carlo-based numerical simulation was used to study the effect of the faults mentioned above in the voltage of the modules in a PV array with one faulty module. A simple expression to identify faults was derived based on the obtained results. The simplicity of this expression allows integrating the fault detection technique in low-cost electronic circuits embedded in a PV module, optimizer, or microinverter.

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Section: Discussionmentioning

confidence: 99%

Detection Criterion for Progressive Faults in Photovoltaic Modules Based on Differential Voltage Measurements

Murillo-Soto

Meza

2022

Applied Sciences

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“…The latter methods also can be further split into several branches: signal processing and statistical methods (e.g., [8,25,26]), i − v curve characteristics analysis (e.g., [27,28]), power losses analysis or efficiency analysis (e.g., [17,29,30]), current and/or voltage measurements (e.g., [31,32]), and artificial intelligent methods (e.g., [9,33,34]). The diagnosis algorithm implemented in this work is based on the IF-THEN rules presented by the authors in [35] and follows the diagnosis branch based on current-voltage measurements.…”

Section: Automated Fault Management System Approachmentioning

confidence: 99%

“…The diagnosis algorithm is based on the logic rules published in [35]. The algorithm requires the following input variables to work; one of them is a matrix voltage V where each cell V(i, j) contains the differential voltage of a module in the PV array.…”

Section: Modeling the Control Unit 241 Diagnosis Algorithmmentioning

confidence: 99%

Automated Fault Management System in a Photovoltaic Array: A Reconfiguration-Based Approach

Murillo-Soto

Meza

2021

Energies

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This work proposes an automated reconfiguration system to manage two types of faults in any position inside the solar arrays. The faults studied are the short-circuit to ground and the open wires in the string. These faults were selected because they severely affect power production. By identifying the affected panels and isolating the faulty one, it is possible to recover part of the power loss. Among other types of faults that the system can detect and locate are: diode short-circuit, internal open-circuit, and the degradation of the internal parasitic serial resistance. The reconfiguration system can detect, locate the above faults, and switch the distributed commutators to recover most of the power loss. Moreover, the system can return automatically to the previous state when the fault has been repaired. A SIMULINK model has been built to prove this automatic system, and a simulated numerical experiment has been executed to test the system response to the faults mentioned. The results show that the recovery of power is more than 90%, and the diagnosis accuracy and sensitivity are both 100% for this numerical experiment.

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“…Research into fault detection techniques has led to their implementation in inverters [1], however there are still many limitations. In [4] a summary of the types of faults and available techniques is made, among which, we can find visual inspection, the use of drones for infrared thermography [5] and the analysis of electrical variables such as power [6].…”

Section: Introductionmentioning

confidence: 99%

Quantitative Comparison of Infrared Thermography, Visual Inspection, and Electrical Analysis Techniques on Photovoltaic Modules: A Case Study

et al. 2022

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This paper compares multiple techniques to detect suboptimal conditions in the PV system. Detection of suboptimal conditions in the PV system is required to achieve optimal photovoltaic (PV) systems. Therefore, maintenance managers need to choose the most suitable techniques objectively. However, there is a lack of objective information comparing the effectiveness of the methods. This article calculates and compares the effectiveness of Infrared thermography (IRT), visual inspection (VI), and electrical analysis (EA) in detecting soiling, partial shadows, and electrical faults experimentally. The results showed that the VI was the best at detecting soiling and partial shading with 100% of effectiveness. IRT and EA had an effectiveness of 78% and 73%, respectively, detecting the three types of conditions under study. It was not possible to achieve maximum detection using only one of the techniques, but that VI must be combined with IR or EA. This research represents a significant contribution by achieving an objective comparison between techniques for detecting suboptimal conditions, being very useful to guide PV system maintainers and designers of fault detection techniques.

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Diagnose Algorithm and Fault Characterization for Photovoltaic Arrays: A Simulation Study

Cited by 5 publications

References 20 publications

Detection Criterion for Progressive Faults in Photovoltaic Modules Based on Differential Voltage Measurements

Detection Criterion for Progressive Faults in Photovoltaic Modules Based on Differential Voltage Measurements

Automated Fault Management System in a Photovoltaic Array: A Reconfiguration-Based Approach

Quantitative Comparison of Infrared Thermography, Visual Inspection, and Electrical Analysis Techniques on Photovoltaic Modules: A Case Study

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