Capacitor charging method for I–V curve tracer and MPPT in photovoltaic systems

Spertino, Filippo; Ahmad, Jawad; Ciocia, Alessandro; Leo, Paolo Di; Murtaza, Ali Faisal; Chiaberge, Marcello

doi:10.1016/j.solener.2015.06.032

Cited by 85 publications

(64 citation statements)

References 24 publications

(30 reference statements)

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“…A typical scheme of the measurement system with capacitive load is shown in Figure 1; voltage, current, irradiance, and ambient temperature are detected simultaneously (the irradiance sensor and the thermometer for ambient temperature are not represented). Thanks to the capacitive load [25], the scan of the entire I-V curve can be easily performed at any level (module, string and array) up to hundreds of kilowatts. The elaboration of the I-V curve points permits to obtain all the electrical parameters, in particular the actual power output and the performance of the module.…”

Section: Description Of Diagnostics Techniques For Defects Detectionmentioning

confidence: 99%

“…The EL test starts with a forward bias of the PV module, obtained thanks to an appropriate DC power supply (Figure 2), in a totally shaded condition (e.g., in a dark room of a laboratory or on-field with low irradiance). The PV cells work like light emitting diodes (LEDs), in which their semiconductor materials have emission spectra in the infrared (IR) region of Thanks to the capacitive load [25], the scan of the entire I-V curve can be easily performed at any level (module, string and array) up to hundreds of kilowatts. The elaboration of the I-V curve points permits to obtain all the electrical parameters, in particular the actual power output and the performance of the module.…”

Section: Description Of Diagnostics Techniques For Defects Detectionmentioning

confidence: 99%

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Experimental Evidence of PID Effect on CIGS Photovoltaic Modules

et al. 2020

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As well known, potential induced degradation (PID) strongly decreases the performance of photovoltaic (PV) strings made of several crystalline silicon modules in hot and wet climates. In this paper, PID tests have been performed on commercial copper indium gallium selenide (CIGS) modules to investigate if this degradation may be remarkable also for CIGS technology. The tests have been conducted inside an environmental chamber where the temperature has been set to 85 °C and the relative humidity to 85%. A negative potential of 1000 V has been applied to the PV modules in different configurations. The results demonstrate that there is a degradation affecting the maximum power point and the fill factor of the current-voltage (I-V) curves. In fact, the measurement of the I-V curves at standard test condition show that all the parameters of the PV modules are influenced. This reveals that CIGS modules suffer PID under high negative voltage: this degradation occurs by different mechanisms, such as shunting, observed only in electroluminescence images of modules tested with negative bias. After the stress test, PID is partially recovered by applying a positive voltage of 1000 V and measuring the performance recovery of the degraded modules. The leakage currents flowing during the PID test in the chamber are measured with both positive and negative voltages; this analysis indicates a correlation between leakage current and power losses in case of negative potential.

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Section: Description Of Diagnostics Techniques For Defects Detectionmentioning

confidence: 99%

Section: Description Of Diagnostics Techniques For Defects Detectionmentioning

confidence: 99%

Experimental Evidence of PID Effect on CIGS Photovoltaic Modules

et al. 2020

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“…The main parameters are given in Table 1 under Many examples of these methods can be found in the literature. Varying the impedance can be created by using resistive load (Van Dyk et al, 2005), charging or discharging a capacitor (Benzagmont et al, 2018;Mahmoud 2006;Muñoz and Lorenzo, 2006;Spertino et al, 2015) or using an electronic switch like MOS transistor (Kuai and Yuvarajin, 2006). The use of one device depends on the PV power and the desired accuracy of measurements.…”

Section: Experimental Set-up Descriptionmentioning

confidence: 99%

PV shading fault detection and classification based on I-V curve using principal component analysis: Application to isolated PV system

et al. 2019

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Health monitoring and diagnosis of photovoltaic (PV) systems is becoming crucial to maximise the power production, increase the reliability and life service of PV power plants. Operating under faulty conditions, in particular under shading, PV plants have remarkable shape of current-voltage (I-V) characteristics in comparison to reference condition (healthy operation). Based on real electrical measurements (I-V), the present work aims to provide a very simple, robust and low cost Fault Detection and Classification (FDC) method for PV shading faults. At first, we extract the features for different experimental tests under healthy and shading conditions to build the database. The features are then analysed using Principal Component Analysis (PCA). The accuracy of the data classification into the PCA space is evaluated using the confusion matrix as a metric of class separability. The results using experimental data of a 250 Wp PV module are very promising with a successful classification rate higher than 97% with four different configurations. The method is also cost effective as it uses only electrical measurements that are already available. No additional sensors are required.

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“…In Table 1, APV, Pnom, and nom refer to the nameplate area (m 2 ), power (kW), and efficiency (%), respectively. Immediately after the installation of the PV plants, their I-V electrical characteristics were measured in natural sunlight by means of the acquisition of the transient charge of a capacitive load [14], and the actual power Pact and efficiency act in the standard test conditions (STCs) were then estimated and are also reported in Table 1. The relative expanded uncertainty (coverage factor k = 2) for both parameters is about 3.5 %.…”

Section: Monitored Pv Plantsmentioning

confidence: 99%

In-field monitoring of eight photovoltaic plants: degradation rate along seven years of continuous operation

et al. 2019

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<p class="Abstract">The results of more than seven years (October 2010-December 2017) of continuous monitoring are presented in this paper. Eight outdoor photovoltaic (PV) plants were monitored. The monitored plants use different technologies: mono-crystalline silicon (m-Si), poli-crystalline silicon (p-Si), string ribbon silicon, copper indium gallium selenide (CIGS), thin film, and cadmium telluride (CdTe) thin film. The thin-film and m-Si modules are used both in fixed installations and on x-y tracking systems. The results are expressed in terms of the degradation rate of the efficiency of each PV plant, which is estimated using the measurements provided by a multi-channel data acquisition system that senses both electrical and environmental quantities. A comparison with the electrical characterization of each plant obtained by means of the transient charge of a capacitive load is also made. In addition, three of the monitored plants are characterized at module level, and the estimated degradation rates are compared to the values obtained with the monitoring system. The main outcome of this work can be summarized as the higher degradation rate of thin-film based PV modules with respect to silicon-based PV modules.</p>

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Capacitor charging method for I–V curve tracer and MPPT in photovoltaic systems

Cited by 85 publications

References 24 publications

Experimental Evidence of PID Effect on CIGS Photovoltaic Modules

Experimental Evidence of PID Effect on CIGS Photovoltaic Modules

PV shading fault detection and classification based on I-V curve using principal component analysis: Application to isolated PV system

In-field monitoring of eight photovoltaic plants: degradation rate along seven years of continuous operation

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