Quantifying the Environmental Sensitivity of SSTDR Signals for Monitoring PV Strings

LaFlamme, Cody; Benoit, Evan; Edun, Ayobami; Furse, Cynthia; Kuhn, Paul K.; Scarpulla, Michael A.; Harley, Joel B.

doi:10.1109/jphotov.2021.3127465

Cited by 6 publications

(2 citation statements)

References 28 publications

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“…Despite its succes, the study in [60] highlights the limitations of SSTDR in the fault diagnosis of several PVS. One such shortcoming is its susceptibility to environmental factors such as temperature and humidity.…”

Section: A Statistical Signal and Processing Approachesmentioning

confidence: 99%

Recent Advances in Fault Diagnosis Techniques for Photovoltaic Systems: A Critical Review

Yang,

Zheng,

Han

et al. 2024

Prot. Control Mod. Power Syst.

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If a failure in the components of a photovoltaic (PV) system, such as PV module, controller, inverter, load, cable, etc. goes undetected and uncorrected, it can seriously affect the efficiency, safety, and reliability of the entire PV power plant. In addition, fires can occur if specific faults, such as arc, ground, and line-to-line faults remain unresolved. Therefore, PV system (PVS) fault diagnoses (FD) are crucial for PV power plant reliability, efficiency, and safety. Many fault diagnosis methods and techniques for PVS components have been developed. In addition, with the development of PV devices, more advanced and intelligent diagnostic technologies are continuously being researched and developed. However, a systematic and thorough analysis, summary, and conclusion are still urgently required. Thus, this paper introduces the types, causes, and impacts of PVS faults, and reviews and discusses the methods proposed in the literature for PVS fault diagnosis, and in particular, failures in PV arrays (PVA). Special attention is paid to the optimization direction of various fault diagnosis methods under different priorities, and their limitations, feasibility, complexity, and cost-effectiveness. Finally, challenges and suggestions are put forward for future research.

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Section: A Statistical Signal and Processing Approachesmentioning

confidence: 99%

Recent Advances in Fault Diagnosis Techniques for Photovoltaic Systems: A Critical Review

Yang,

Zheng,

Han

et al. 2024

Prot. Control Mod. Power Syst.

View full text Add to dashboard Cite

show abstract

“…52 The quest for a comprehensive, efficient, and practical approach remains paramount in enhancing the reliability and performance of PV systems. LaFlamme et al 53 after presenting a quantitative analysis of environmental impacts on SSTDR measurements, identify the need for multiple baselines in different environmental conditions to make fault detection simpler.…”

Section: Introductionmentioning

confidence: 99%

Advanced impedance mismatch technique for detecting faults in photovoltaic systems

Lamdihine,

Ouassaid

2024

Energy Science & Engineering

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This paper presents a comprehensive exploration of the Advanced Impedance Mismatch Technique (AIMT), a novel approach designed for the accurate detection of simultaneous and varied faults within photovoltaic (PV) systems. This investigation integrates a spectrum of fault detection strategies, pinpointing reflectometry as a notably effective tool. Despite its utility, conventional reflectometry applications face critical constraints, notably the limitation to identify only the primary fault location within a PV array and the inability to distinguish between different fault types. This work introduces an innovative mathematical model that estimates the impedance of PV modules, enhancing the reflectometry method to enable the precise identification and localization of multiple defective modules within a string. The proposed technique exhibits a remarkable sensitivity to detect slight impedance differences between a functional PV string and one with defective modules. The validity of the AIMT's mathematical model is corroborated through simulation experiments on a string of seven PV modules afflicted with multiple simultaneous faults. These experiments rigorously evaluate the technique's accuracy in pinpointing the locations of defective modules within a PV string. The outcomes of our proposed ‐times faster AIMT reveal a strong concordance between the simulated reflective signals and the impedance values forecasted by the model, highlighting the proposed method's proficiency in the detailed detection and diagnosis of progressive faults within PV systems.

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Anomaly Detection of Disconnects Using SSTDR and Variational Autoencoders

et al. 2022

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Quantifying the Environmental Sensitivity of SSTDR Signals for Monitoring PV Strings

Cited by 6 publications

References 28 publications

Recent Advances in Fault Diagnosis Techniques for Photovoltaic Systems: A Critical Review

Recent Advances in Fault Diagnosis Techniques for Photovoltaic Systems: A Critical Review

Advanced impedance mismatch technique for detecting faults in photovoltaic systems

Anomaly Detection of Disconnects Using SSTDR and Variational Autoencoders

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