The analysis of parameter uncertainty on performance and reliability of photovoltaic cells

Zhang, Feng; Wu, Mingying; Hou, Xinting; Cheng, Han; Wang, Xinhe; Liu, Zhongbing

doi:10.1016/j.jpowsour.2021.230265

Cited by 17 publications

(10 citation statements)

References 33 publications

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“…Photovoltaic systems generate electric energy directly through the solar light drive producing zero pollution [90]. They also have several advantages, e.g., noiseless operation, low maintenance, and high reliability [91]. In recent years, the development of emerging photovoltaic technologies has been subject to extensive research that focuses on increasing the efficiency and lifetime of these devices, combined with employing lowcost materials and processes [89].…”

Section: Photovoltaic Cellsmentioning

confidence: 99%

The differential measure for Pythagorean fuzzy multiple criteria group decision-making

Sharaf

2022

Complex Intell. Syst.

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Pythagorean fuzzy sets (PFSs) proved to be powerful for handling uncertainty and vagueness in multi-criteria group decision-making (MCGDM). To make a compromise decision, comparing PFSs is essential. Several approaches were introduced for comparison, e.g., distance measures and similarity measures. Nevertheless, extant measures have several defects that can produce counter-intuitive results, since they treat any increase or decrease in the membership degree the same as the non-membership degree; although each parameter has a different implication. This study introduces the differential measure (DFM) as a new approach for comparing PFSs. The main purpose of the DFM is to eliminate the unfair arguments resulting from the equal treatment of the contradicting parameters of a PFS. It is a preference relation between two PFSs by virtue of position in the attribute space and according to the closeness of their membership and non-membership degrees. Two PFSs are classified as identical, equivalent, superior, or inferior to one another giving the degree of superiority or inferiority. The basic properties of the proposed DFM are given. A novel method for multiple criteria group decision-making is proposed based on the introduced DFM. A new technique for computing the weights of the experts is developed. The proposed method is applied to solve two applications, the evaluation of solid-state drives and the selection of the best photovoltaic cell. The results are compared with the results of some extant methods to illustrate the applicability and validity of the method. A sensitivity analysis is conducted to examine its stability and practicality.

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Section: Photovoltaic Cellsmentioning

confidence: 99%

The differential measure for Pythagorean fuzzy multiple criteria group decision-making

Sharaf

2022

Complex Intell. Syst.

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“…For the real-time status of PV arrays, the available parameters only include the current and voltage of PV arrays. In practical engineering, various uncontrollable factors will result in the uncertainty of PV power generation [16][17][18], and the volatility of data causes the characteristics of different faults of PV arrays to be easily confused [19]. Scholars at home and abroad often turn to non-parametric estimation methods to deal with the above problems.…”

Section: Introductionmentioning

confidence: 99%

Classification Method of Photovoltaic Array Operating State Based on Nonparametric Estimation and 3σ Method

Tong¹,

Li²,

Ren

et al. 2023

Sustainability

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Photovoltaic (PV) array, as the key component of large-scale PV power stations, is prone to frequent failure that directly affects the efficiency of PV power stations. Therefore, accurate classification of the operating state of PV arrays is the basis for fault location. Thus, a novel classification method for PV array operating state was designed based on nonparametric estimation and a 3σ method. The actual data analysis proves the hypothesis that performance ratio (PR) distribution characteristics of PV arrays can characterize the operating state of PV arrays. The modeling curve of the PV array with an excellent performance has only one peak and the peak value is large, while the distribution curve of the PV array with a poor performance has a small peak. In this paper, the distribution characteristics of PV arrays are modeled, the peak value is used to classify the operating state of PV arrays, and finally the effectiveness of the proposed method is compared. Overall, this paper makes a valuable contribution by proposing a novel method for accurately classifying the operating state of PV arrays. The proposed method can help improve the efficiency and fault diagnosis of PV power stations.

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“…Many authors specify the modeling method by the number of diodes and the number of parameters to be extracted. Based on this convention, the most used models of photovoltaic cells are 1 diode and 4 parameters (1D4P), 1 diode and 5 parameters (1D5P), and 2 diodes and 7 parameters (2D7P) 8 …”

Section: Introductionmentioning

confidence: 99%

“…Based on this convention, the most used models of photovoltaic cells are 1 diode and 4 parameters (1D4P), 1 diode and 5 parameters (1D5P), and 2 diodes and 7 parameters (2D7P). 8 Due to the presence of diodes, the models present non-linear equations for extracting the parameters. Thus, it is necessary to use mathematical methods to solve the equations.…”

Section: Introductionmentioning

confidence: 99%

Modeling of the operating characteristics of photovoltaic modules based on particle swarm optimization

Provensi

Grala

Zukeram

et al. 2022

Env Prog and Sustain Energy

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This work evaluates the use of particle swarm optimization to extract the parameters that represent a photovoltaic cell in the model of one diode and five parameters (1D5P) to obtain current versus voltage characteristic curves (I Â V) of a photovoltaic module operating under a wide range of temperature and irradiation scenarios. In all the modeling and simulation processes, only information of the module's data sheet provided by the manufacturers was used, without depending on results from other simulations or external data collections. To validate the study, the simulation of the current versus voltage (I Â V) curves of a commercial photovoltaic module was made, and this was compared with data provided by the manufacturer and also compared with Chenni's method, which is consolidated by the literature. Errors of less than 0.3% were obtained for the simulations performed under the standard test conditions and in temperature and irradiation situations commonly found in practice, as is the case, of G = 700 W/m 2 and T c = 40 C, the 1D5P method showed an average error of approximately 1%, slightly surpassing the Chenni's method where the error was approximately 1.4%. Statement of Industrial Relevance:In developing countries, such as Brazil, a significant increase in the portion referring to solar energy in the Brazilian energy grid is noted. As in 2016, this portion was only 0.02%, though in 2020, according to the Brazilian Solar Energy Association (ABSOLAR), 1 this portion had an increase of 75 times and reached the value of 1.5%. In addition, ABSOLAR's forecast for 2030 is that solar energy will reach 10% of the Brazilian energy grid. One of the reasons for this is that industrial consumer units are increasingly looking for alternative energy sources due to high energy inflation. Photovoltaic generators are an excellent option for industries because they are clean and sustainable energy. 2 It is silent and brings a financial return for the investor. Although, even with all the benefits, the photovoltaic generator has a high acquisition cost, especially for consumer units that demand much energy, as is the case of industries. Thus, correct and precise dimensioning for the photovoltaic generator is necessary. One way to increase the accuracy of dimensioning is to use simulation of the photovoltaic modules, which is the objective of this article.Novelty or Significance: The developed method uses the particle swarm optimization with constriction factor to simulate I Â V curves of a photovoltaic module for any

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The analysis of parameter uncertainty on performance and reliability of photovoltaic cells

Cited by 17 publications

References 33 publications

The differential measure for Pythagorean fuzzy multiple criteria group decision-making

The differential measure for Pythagorean fuzzy multiple criteria group decision-making

Classification Method of Photovoltaic Array Operating State Based on Nonparametric Estimation and 3σ Method

Modeling of the operating characteristics of photovoltaic modules based on particle swarm optimization

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