Comparative Study of Solar PV System Performance under Partial Shaded Condition Utilizing Different Control Approaches

Al-Wesabi, Ibrahim; Fang, Zhijian; Ameur, Khaled; Deng, Min; Shafik, M B; Al-Muthanna, Galal

doi:10.17485/ijst/v14i22.827

Cited by 15 publications

(5 citation statements)

References 62 publications

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“…These MPP tracking devices are equipped with algorithms specifically designed for this purpose. Among the most common algorithmic methods are Perturbation and Observation (P&0), hill climbing, INcremental Conductance (INC), short circuit current tracking, open-circuit voltage tracking, and ripple correlation techniques [1][2][3][4][5][6]. Some algorithms have been tailored to reduce hardware requirements and enhance performance [7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Genetic and Cuckoo Search Algorithms for MPPT in Partial Shaded

2024

ijSmartGrid

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The exploitation of solar energy through photovoltaic technology has become crucial for electricity production. To maximize this production, optimizing solar radiation is essential. However, various challenges for example fixed structures, structures, and winds carrying sand particles can diminish light intensity, thereby reducing efficiency. These conditions may result in multiple maximum power points appear on the static characteristic of maximum power as a function of photovoltaic voltage. curve. Consequently, more efficient metaheuristic algorithms for maximum power point tracking are needed to ensure optimal operation, particularly during inclement weather and instances of partial shading, such as non-uniform irradiation. This work provides a comparative analysis of metaheuristic approaches specifically Cuckoo Search and Genetic Algorithm, used for tracking the maximum power point in photovoltaic systems under partial shading conditions.

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Section: Introductionmentioning

confidence: 99%

Analysis of Genetic and Cuckoo Search Algorithms for MPPT in Partial Shaded

2024

ijSmartGrid

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“…In [12], the V MPP parameter was used to identify the occurrence of partial shading using the voltage drop on the I-V curves. Similar techniques can be seen in [13,14]. Another technique is to determine the steps on the I-V curves are calculate the curve's first or second derivative.…”

Section: Introductionmentioning

confidence: 99%

Comparative analysis of the performance of supervised learning algorithms for photovoltaic system fault diagnosis

Eldeghady,

Kamal,

Moustafa Hassan

2024

STET

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New trends were introduced in using photovoltaic (PV) energy which are mostly attributable to new laws internationally having a goal to decrease the usage of fossil fuels. The PV systems efficiency is impacted significantly by environmental factors and different faults occurrence. These faults if they weren’t rapidly identified and fixed may cause dangerous consequences. A lot of methods have been introduced in literature to detect faults that may occur in a PV system such as using I-V curves measurements, atmospheric models and statistical methods. In this paper, various machine learning techniques in particular supervised learning techniques are used for PV array failure diagnosis. The main target is the identification and categorization of several faults that may occur such as shadowing, degradation, open circuit and short circuit faults that has a great impact on PV systems performance. The results showed the techniques high ability of fault diagnosis capability. The KNN technique showed the best fault prediction performance. It achieves prediction accuracy 99.2% and 99.7% AUC-ROC score. This shows its superiority in faults prediction in PV systems over other used methods Decision Tree, Naive Bayes, and Logistic Regression.

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“…However, the main drawback of the latter is its high computational complexity. Hybrid methods, which combine two or more MPPT techniques, have recently been established to improve MPPT performance and efficiency [22]. According to the literature, the GMPP may be successfully monitored utilizing hybrid methods under various PSCs.…”

Section: Introductionmentioning

confidence: 99%

“…Several studies [22,[38][39][40][41] claimed that the original PSO approach could monitor the GP in general, but they ignored the fact that the SP varies with time and that therefore the GP's location and value vary as well. In addition, the original PSO has visible oscillations around the steady state and a sluggish convergence speed.…”

Section: Introductionmentioning

confidence: 99%

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A High Speed MPPT Control Utilizing a Hybrid PSO-PID Controller under Partially Shaded Photovoltaic Battery Chargers

et al. 2023

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Improving photovoltaic systems in terms of temporal responsiveness, lowering steady-state ripples, high efficiency, low complexity, and decreased tracking time under various circumstances is becoming increasingly important. A particle-swarm optimizer (PSO) is frequently used for maximum power-point tracking (MPPT) of photovoltaic (PV) energy systems. However, during partial-shadowing circumstances (PSCs), this technique has three major drawbacks. The first problem is that it slowly converges toward the maximum power point (MPP). The second issue is that the PSO is a time-invariant optimizer; therefore, when there is a time-variable shadow pattern (SP), it adheres to the first global peak instead of following the dynamic global peak (GP). The third problem is the high oscillation around the steady state. Therefore, this article proposes a hybrid PSO-PID algorithm for solving the PSO’s three challenges described above and improving the PV system’s performance under uniform irradiance and PSCs. The PID is designed to work with the PSO algorithm to observe the maximum voltage that is calculated by subtracting from the output voltage of the DC-DC boost converter and sending the variation to a PID controller, which reduces the error percentage obtained by conventional PSO and increases system efficiency by providing the precise converter-duty cycle value. The proposed hybrid PSO-PID approach is compared with a conventional PSO and bat algorithms (BAs) to show its superiority, which has the highest tracking efficiency (99.97%), the lowest power ripples (5.9 W), and the fastest response time (0.002 s). The three aforementioned issues can be successfully solved using the hybrid PSO-PID technique; it also offers good performance with shorter times and faster convergence to the dynamic GP. The results show that the developed PID is useful in enhancing the conventional PSO algorithm and solar-system performance.

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Comparative Study of Solar PV System Performance under Partial Shaded Condition Utilizing Different Control Approaches

Cited by 15 publications

References 62 publications

Analysis of Genetic and Cuckoo Search Algorithms for MPPT in Partial Shaded

Analysis of Genetic and Cuckoo Search Algorithms for MPPT in Partial Shaded

Comparative analysis of the performance of supervised learning algorithms for photovoltaic system fault diagnosis

A High Speed MPPT Control Utilizing a Hybrid PSO-PID Controller under Partially Shaded Photovoltaic Battery Chargers

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