Short and open circuit faults study in the PV system inverter

Bouzidi, Mohammed; Harrouz, Abdelkader; Tadj, Mohammed; Mansouri, Smail

doi:10.11591/ijpeds.v12.i3.pp1764-1771

Cited by 3 publications

(6 citation statements)

References 26 publications

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“…Several scholars have extensively examined this topic in their publications [7][8] and [13][14][15][16][17][18].…”

Section: Modelling Of Photovoltaic Systemsmentioning

confidence: 99%

“…(5) At the inflection point, the maximum power produced by a panel is zero when the derivative of power with respect to voltage is zero, which is the product of the maximum current (Imp) and the maximum voltage (Vmp) [7], [19][20]. V mp (7) The value of the limit between the brackets in equation ( 3) on the right-hand side is negligible compared to the other side [7][8][9], [20][21]:…”

Section: Determine Pv Panel Model Parametersmentioning

confidence: 99%

“…A significant number of studies employ the single-diode model, which relies on variables such as short-circuit current and diode saturation current. Precise models are essential for the design and optimization of photovoltaic systems [6][7][8].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Extracting electrical parameters of solar cells using Lambert function

Bouzidi,

Ben Rahmoune,

Nasri

et al. 2024

Diagnostyka

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Photovoltaic cells are intricate systems that transform solar energy into electrical power. Certain internal parameters, such as diode saturation current, conversion resistance, and series resistance, significantly influence the performance of electrical components. Frequently, manufacturers do not provide these parameters. At the moment, researchers need new and clear ways to measure these factors so they can get a better idea of how solar cells work and improve efficiency through simulations. We present a novel approach to accurately determining the five parameters (series resistance, shunt resistance, photovoltaic cell current, and diode saturation current) for multi-crystalline silicon solar cell models. This approach employs the Lambert function and the curve of parasitic resistance. By utilizing the extracted internal electrical parameters, this method will enhance the efficiency of solar cells through the facilitation of more accurate simulations.

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“…Several scholars have extensively examined this topic in their publications [7][8] and [13][14][15][16][17][18].…”

Section: Modelling Of Photovoltaic Systemsmentioning

confidence: 99%

Section: Determine Pv Panel Model Parametersmentioning

confidence: 99%

See 1 more Smart Citation

Extracting electrical parameters of solar cells using Lambert function

Bouzidi,

Ben Rahmoune,

Nasri

et al. 2024

Diagnostyka

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“…The mathematical model for the single-diode equivalent circuit of a photovoltaic cell can be expressed by the following equation (Mohd Amiruddin et al, 2020b;Rahmoune et al, 2023), (Bouzidi et al, 2021a(Bouzidi et al, , 2022a:…”

Section: Modeling Of a Pv Panelmentioning

confidence: 99%

Intelligent fault detection of photovoltaic panel using neural networks

Bouzidi,

Rahmoune,

Nasri

2024

SEES

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This research primarily aims to leverage artificial neural network technology for diagnosing power output issues in photovoltaic (PV) panels stemming from fluctuations in solar irradiance and temperature. The proposed diagnostic approach relies on constructing a reference model that captures the expected normal operating behavior of the PV panel under fault-free conditions. This reference model is then compared against the actual power output, and the difference, known as the residual, is analyzed to detect potential faults. The neural network is trained using real-world data inputs like solar irradiance and temperature measurements, with the sole output being the power produced by the PV panel. Through training, the neural network learns to map the complex non-linear relationships between environmental inputs and expected power output, effectively modeling the PV system's intrinsic behavior under healthy conditions. Results demonstrate the neural network-based approach's remarkable ability to diagnose faults with high accuracy while avoiding potential non-linear complications. This intelligent monitoring system provides a reliable protocol for early fault detection through training on actual measurements, eliminating the need for complex mathematical models. Consequently, it streamlines the maintenance process by negating intricate procedures to identify PV panel issues. The neural network effectively learns the mapping between environmental conditions and expected power output through exposure to real-world data during training. By analyzing deviations from this learned mapping, represented by the residual signal, the approach can reliably detect anomalies indicative of faults or performance degradation in the PV system. This data-driven nature allows the system to adapt to site-specific characteristics and capture non-linear effects without explicit modeling.

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“…In order to accurately determine the status of the position sensor, three sets of data residual comparisons were used to vote on the status of the position sensor. In addition to the position sensor data, the other two sets are the speed estimates obtained from the stator voltage and current estimation and the processed historical data [32]. Also, in order to improve the credibility of the historical data, two types of data are selected in this paper, one is the velocity values of the historical data obtained from the RBF neural…”

Section: Fault Tolerant Monitoring Of Generator Setmentioning

confidence: 99%

Research on fault adaptive fault tolerant control of distributed wind solar hybrid generator

et al. 2023

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Due to the poor accessibility, poor operating conditions, high failure rate, long maintenance time, and difficult maintenance of wind hybrid generators, the economic loss is huge once the failure stops. To this end, the fault adaptive fault-tolerant control of distributed wind and wind hybrid generators is studied, the historical operation data of offshore wind and wind hybrid generators and onshore wind and wind hybrid generators are counted and compared, and the fault characteristics of key components of offshore wind and wind hybrid generators are analyzed. The generator sets are summarized, and the common electrical faults of wind turbines and their impacts on the system are analyzed. This paper summarizes the current research status of fault-tolerant operation of existing offshore wind and wind complementary generators in terms of software fault tolerance and hardware fault tolerance, summarizes the current fault tolerance schemes for offshore wind and wind complementary generators, and analyzes the application feasibility of existing fault tolerance schemes. In addition, the main problems of fault-tolerant offshore wind and solar complementary generator sets are pointed out, and future research hotspots are foreseen.

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Short and open circuit faults study in the PV system inverter

Cited by 3 publications

References 26 publications

Extracting electrical parameters of solar cells using Lambert function

Extracting electrical parameters of solar cells using Lambert function

Intelligent fault detection of photovoltaic panel using neural networks

Research on fault adaptive fault tolerant control of distributed wind solar hybrid generator

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