Improving the performance of PV systems by faults detection using GISTEL approach

Tadj, Mohammed; Benmouiza, Khalil; Cheknane, Ali; Silvestre, S.

doi:10.1016/j.enconman.2014.01.030

Cited by 93 publications

(31 citation statements)

References 18 publications

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“…Applying satellite information and unmanned extra-terrestrial drone system based thermal image processing will potentially be the future for monitoring and diagnosis of PV systems faults. Fault detection performance is improved using satellite imaging by estimating the irradiance and DC power output [94]. In this case, the satellite data measurement for sunlight intensity is processed using fuzzy logic then compared with the ground measurement.…”

Section: Image Processing In Pv Fault Diagnosticsmentioning

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: Image Processing In Pv Fault Diagnosticsmentioning

confidence: 99%

Review on Methods of Fault Diagnosis in Photovoltaic System Applications

Syafaruddin¹,

Zinger²

2019

JESTR

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“…In order to detect failures in GCPV, the expected energy yield calculated based on the hourly satellite-derived irradiance and the actual one has been compared [13]. To conduct a more precise diagnosis, the GISTEL model and fuzzy logic approach have been combined [14]. In addition, a technique to set an accumulation period and to extract the maximum point of output power and satellite-derived irradiance, respectively, has been reported [15].…”

Section: Previous Study Using Satellite Datamentioning

confidence: 99%

A Method for the Detection of Decrease in Power in PV Systems Using Satellite Data

Kawasaki¹,

Okajima²

2019

SGRE

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In this paper, a method to detect a decrease in the output power of photovoltaic systems is proposed. This method is based on using satellite irradiance data. In addition, fault detection is carried out with only one day's data in this method. Thus, the time elapses since the decrease in output is shorter than with the other methods. In order to mitigate the error in satellite data and improve the accuracy of fault detection, data extraction is carried out, which consists of two steps. In the first step, effective data are extracted by setting a lower irradiance limit. In the second step, "Calculation day" is determined depending on the number of effective data in one day. Fault detection, which is only conducted on the Calculation day, is conducted by comparing the expected power and the measured power. The parameters used in this study were optimized by testing 45 systems that appear normal. Subsequently, 340 systems were analyzed with the proposed method, using optimized parameters. The results showed the effectiveness of our method from the viewpoints of both accuracy and time required. In addition, three data extraction methods were considered to distinguish between the permanent decrease caused by failure, and the temporary decrease caused by partial shade. Fuzzy cluster analysis showed the best result among the three methods used.

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“…[3][4][5]. Under partial shade conditions, current mismatch and voltage mismatch can dramatically reduce the power generation of a PV array [6][7][8]. In particular, if shading occurs at midday, when solar irradiation is high, the shadow effect would be significant [9].…”

Section: Introductionmentioning

confidence: 99%

Reconfiguration Method to Extract More Power from Partially Shaded Photovoltaic Arrays with Series-Parallel Topology

Liu

Wang

2019

Energies

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A photovoltaic (PV) array is composed of several panels connected in series-parallel topology in most actual applications. However, partial shading of a PV array can dramatically reduce power generation. This paper presents a new reconfiguration method to extract more power from PV arrays under partial shade conditions. The method is designed using the effective maximum power point current and voltage of a PV panel. Its advantages involve (i) the method reconfigures the PV array without measuring the irradiance profile, and (ii) the reconfiguration is executed on the level of a PV module. Based on these two aspects, the method disperses the shade uniformly within the PV array, reducing the mismatch loss significantly and increasing power generation. The performance of the proposed method is investigated for different shade patterns and results show improved performance under partial shade conditions.

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Improving the performance of PV systems by faults detection using GISTEL approach

Cited by 93 publications

References 18 publications

Review on Methods of Fault Diagnosis in Photovoltaic System Applications

Review on Methods of Fault Diagnosis in Photovoltaic System Applications

A Method for the Detection of Decrease in Power in PV Systems Using Satellite Data

Reconfiguration Method to Extract More Power from Partially Shaded Photovoltaic Arrays with Series-Parallel Topology

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