Review on Methods of Fault Diagnosis in Photovoltaic System Applications

Syafaruddin, X; Zinger, D.S.

doi:10.25103/jestr.125.07

Cited by 17 publications

(6 citation statements)

References 78 publications

(87 reference statements)

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“…Moreover, Figure 2 demonstrates an apparent increasing interest on the topic in the last few years. Therefore, emphasis is placed on the analysis of recent literature reviews [52][53][54][55][56][57][58][59][60][61][62][63][64][65][66][67][68]. In addition, the literature is complemented with standards [69][70][71], selected papers [72][73][74][75][76], and reports [77].…”

Section: Photovoltaic (Pv) Systemsmentioning

confidence: 99%

“…Additional testing procedures with demanding requirements for result analysis are described in the literature such as I-V curvebased approaches to study PV system performance from its I-V characteristic [53,57,73,74]. Other investigations use infrared thermography to detect hot spots in PV systems [56,62,64,69]. Moreover, flash, electroluminescence, and X-ray tests are employed to find defects in PV arrays [59,60,72].…”

Section: Fault Diagnosis and Condition Assessment Of Pv Systemsmentioning

confidence: 99%

See 1 more Smart Citation

Condition Assessment of Medium Voltage Assets: A Review

Mesino,

Caicedo,

Mamaní

et al. 2023

Adv. sci. technol. eng. syst. j.

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Condition assessment of medium voltage assets is essential to ensure reliability and costeffective operation of power distribution networks. This article presents a literature review of condition assessment of medium voltage assets related to a distribution system in a noninterconnected zone in Colombia, namely, power transformers, photovoltaic systems, switchgear, lines and cables, and instrument transformers. Advanced search rules are formulated to obtain bibliographic records of relevant academic literature from the database Scopus. The retrieved data are analyzed quantitatively to provide insights on the current state of research on the topic. Next, the most relevant academic papers for each medium voltage asset are selected and analyzed in a critical review along with more diverse literature including standards, technical reports, and white papers obtained through complementary searches. The results of the review show that several approaches have been formulated for condition assessment of medium voltage assets, ranging from traditional diagnostic methods to advanced artificial intelligence-based approaches. Moreover, research on some assets is already mature including power transformers, and photovoltaic systems, whereas other assets have been incipiently studied such as distribution and instrument transformers. Therefore, the need for deeper condition assessment research for these critical assets is highlighted. Research gaps are identified in the standardization and integration of condition assessment tools for distribution system operators.

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Section: Photovoltaic (Pv) Systemsmentioning

confidence: 99%

Section: Fault Diagnosis and Condition Assessment Of Pv Systemsmentioning

confidence: 99%

Condition Assessment of Medium Voltage Assets: A Review

Mesino,

Caicedo,

Mamaní

et al. 2023

Adv. sci. technol. eng. syst. j.

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“…Other methods are presented in [58], [59], and [60]. All of the developed electrical FDD based techniques can be done through offline adaptation (test of the technique's effectiveness) [36] or online adaptation at a real-time [60][61][62][63].…”

Section: Fdd Electrical-based Techniquesmentioning

confidence: 99%

“…Shading AI: decision-tree [50], fuzzy [50][51], neuro-fuzzy [53], heuristic [54], Meta-heuristic [56][57] Standard analysis error in I-V [64] PCA [65] DWT [66] Short-circuit (SC) AI based on I-V curve: ANN [44], [49] Fuzzy [51][52], heuristic [54], meta-heuristic [56,57] Open-circuit (OC) AI based on I-V curve [48] Decision-tree [50], Fuzzy [50][51] Abnormal degradations Visual inspections and drones IR, EL, PL Line to Line Fault (LLF) Wavelet-Packets [50] Support vector machine (SVM) [63] Arc-Fault (AF) I-V test curve [64] Frequency domain reflectometry [37] Blocking and bypassing diode fault (BBP) [72,73] PV panels are used. Cleaning can be dry or wet, related to the type of region.…”

Section: Pvg Faults Detection and Diagnosis Used Techniquesmentioning

confidence: 99%

A comprehensive study of diagnosis faults techniques occurring in photovoltaic generators

et al. 2021

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Recently, many focuses have been done in the field of renewable energies, especially in solar photovoltaic energy. Photovoltaic generator, considered as the heart of any photovoltaic installation, exhibits sometimes malfunctions which involve degradations on the overall photovoltaic plant. Therefore, diagnosis techniques are required to ensure failures detection. They avoid dangerous risks, prevent damages, allow protection, and extend their healthy life. For these purposes, many recent studies have given focuses on this field. This paper summarizes a large number of such interesting works. It presents a survey of photovoltaic generator degradations kinds, several types of faults, and their major diagnosis techniques. Comparative studies and some critical analyses are given. Other trending diagnosis solutions are also discussed. A proposed neural networks-based technique is developed to clarify the main process of diagnosis techniques, using artificial intelligence. This method shows good results for modelling and diagnosing the healthy and faulty (shaded) photovoltaic array.

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“…Fault diagnosis techniques for equipment have prominent applications in electric power systems [1,2], chemical process systems [3,4], photovoltaic systems [5][6][7][8][9], bearings [10,11], building energy systems [6], control systems [12,13], and automation equipment [14]. The electrical control system of rapier loom is susceptible to various disturbances during operation and is prone to malfunction.…”

Section: Introductionmentioning

confidence: 99%

Research on rapier loom fault system based on cloud-side collaboration

et al. 2021

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The electrical control system of rapier weaving machines is susceptible to various disturbances during operation and is prone to failures. This will seriously affect the production and a fault diagnosis system is needed to reduce this effect. However, the existing popular fault diagnosis systems and methods need to be improved due to the limitations of rapier weaving machine process and electrical characteristics. Based on this, this paper presents an in-depth study of rapier loom fault diagnosis system and proposes a rapier loom fault diagnosis method combining edge expert system and cloud-based rough set and Bayesian network. By analyzing the process and fault characteristics of rapier loom, the electrical faults of rapier loom are classified into common faults and other faults according to the frequency of occurrence. An expert system is built in the field for edge computing based on knowledge fault diagnosis experience to diagnose common loom faults and reduce the computing pressure in the cloud. Collect loom fault data in the cloud, train loom fault diagnosis algorithms to diagnose other faults, and handle other faults diagnosed by the expert system. The effectiveness of loom fault diagnosis is verified by on-site operation and remote monitoring of the loom human-machine interaction system. Technical examples are provided for the research of loom fault diagnosis system.

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Review on Methods of Fault Diagnosis in Photovoltaic System Applications

Cited by 17 publications

References 78 publications

Condition Assessment of Medium Voltage Assets: A Review

Condition Assessment of Medium Voltage Assets: A Review

A comprehensive study of diagnosis faults techniques occurring in photovoltaic generators

Research on rapier loom fault system based on cloud-side collaboration

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