Metaheuristic optimization based fault diagnosis strategy for solar photovoltaic systems under non-uniform irradiance

Das, Saborni; Hazra, Abhik; Basu, Mousumi

doi:10.1016/j.renene.2017.10.053

Cited by 28 publications

(9 citation statements)

References 23 publications

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“…These methods have achieved successful identification and localization of fault types under different testing scenarios. The Improved Real Coded Genetic Algorithm (IRCGA) is another meta-heuristic optimization approach that can be used to detect, localize and distinguish the open and short-circuit faults under non-uniform sunlight intensity and temperature distribution [26]. After extensive simulation performance, the IRCGA method accurately estimated the possible fault location and type of faults.…”

Section: Methodsmentioning

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: Methodsmentioning

confidence: 99%

Review on Methods of Fault Diagnosis in Photovoltaic System Applications

Syafaruddin¹,

Zinger²

2019

JESTR

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“…Short impacts of shading, open/short circuits, and snow covering on a PV installation have been investigated and faults are classified accordingly in [26], based on different parameters extracted from 720 I-V curves, which is a very complex process. In [27], three different classes of cracks for PV modules are detected and differentiated by using RF classifiers based on 735 electroluminescence images. A summary of the ML based techniques for PV fault detection including key contribution literature gaps is presented in Table 1.…”

Section: Machine-learning-based Fault Detectionmentioning

confidence: 99%

Unified Fuzzy Logic Based Approach for Detection and Classification of PV Faults Using I-V Trend Line

et al. 2022

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Solar photovoltaic PV plants worldwide are continuously monitored and carefully protected to ensure safe and reliable operation through detecting and isolating faults. Faults are very common in modern solar PV systems which interrupt normal system operation adversely affecting the performance of the PV systems. When undetected, faults not only cause significant reduction in the efficiency and life span of the PV system, but also result in damage and fire hazards compromising their reliability. Therefore, early fault detection and diagnosis of photovoltaic plants is a necessity for safe and reliable operation required for growing solar PV systems. Unfortunately, several recent fire incidents have been reported recently caused by undetected faults in solar PV systems. Motivated by this challenge, this paper, utilizing a proposed fuzzy logic algorithm, presents a novel technique for detecting and classifying faults in solar PV systems. Furthermore, the proposed method introduces fault indexing as a performance indicator that measures the degree of deviation from the normal operating conditions of the photovoltaic system. Various signatures of each fault scenario are identified in the shape of corresponding current-voltage trajectories and their extracted parameters. The effectiveness of the proposed technique is evaluated both in simulation and experimentally using a 5 kW grid connected solar array. It is demonstrated that the proposed technique is capable of diagnosing the occurrence of different faults with more than 98% accuracy.

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“…Cristaldi et al ( 2017) discuss the root cause and risk analysis of photovoltaic balance system failure. Das et al (2018) focus on metaheuristic optimization-based diagnosis of fault for a photovoltaic system with nonuniform irradiance. Garoudja et al (2017) proposed a fault-detection approach for detecting of shading of a photovoltaic system based on the direct current by combining the flexibility, and simplicity of a onediode model.…”

Section: Literature Reviewmentioning

confidence: 99%

Reliability and performance prediction of a small serial solar photovoltaic system for rural consumption using the Gumbel-Hougaard family copula

Maihulla

Yusuf

2021

Life Cycle Reliab Saf Eng

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The current study looks into the dependability and performance of a solar photovoltaic system that is configured in series. The system's performance is measured using system strength indicators such as reliability, availability, mean time to failure, and cost measures. The system is made up of four subsystems: a 3-out-of-5 panel, a charge controller, a 2-out-of-3 battery bank, and an inverter. In contrast to some industrial and manufacturing systems, the system is assumed to operate at full capacity. In the current study, failure is classified as complete or incomplete. A complete failure occurs when any of the subsystems fails, whereas an incomplete failure occurs when a unit in the panel subsystem or battery bank fails. The system is analyzed using the linear differential-difference equation, supplementary variable technique, Gumbel-Hougaard family of copula to obtain expressions of reliability measures of determining system strength such as availability, reliability, mean time to failure (MTTF), and profit function. To illustrate the obtained results and to analyze the effect of various system parameters, numerical examples are provided. The current study is beneficial to areas with low energy consumption, such as schools and homes, in alleviating some of the challenges they face. KeywordsCopula • Solar panel • Availability • Parallel • Photovoltaic Abbreviations s Laplace transform variable for all expressions t Time variable on a time scale 1 Failure rate of the unit in subsystem 1 2 Failure rate of the unit in subsystem 2 3 Failure rate of the unit in subsystem 3 4 0 (x) Copula repair of full failure of unit in subsystem 1 0 (y) Copula repair of full failure of unit in subsystem 2 0 (z) Copula repair of full failure of unit in subsystem 3 0 (k) Copula repair of full failure of unit in subsystem 4 * Ibrahim Yusuf

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Metaheuristic optimization based fault diagnosis strategy for solar photovoltaic systems under non-uniform irradiance

Cited by 28 publications

References 23 publications

Review on Methods of Fault Diagnosis in Photovoltaic System Applications

Review on Methods of Fault Diagnosis in Photovoltaic System Applications

Unified Fuzzy Logic Based Approach for Detection and Classification of PV Faults Using I-V Trend Line

Reliability and performance prediction of a small serial solar photovoltaic system for rural consumption using the Gumbel-Hougaard family copula

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