Potential induced degradation (PID): Review

Miranda, Hellen Ferreira Barreto; Costa, Luan Peixoto da; Soares, Stefhany Oliveira; Silva, Jonathan Velasco da

doi:10.1109/tdla47668.2020.9326184

Cited by 1 publication

(2 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In previous studies, there has been a focus on the improvement of solar-cell materials to prevent PID [10,11], especially crystalline silicon solar cells [12,13]; thus, control of the base resistivity of materials is one of the methods to reduce PID. Earlier studies have pointed out that the PID problem can be effectively slowed down [14] when the base resistivity is higher.…”

Section: Basic Knowledge Related and Research Motivation Of The Studymentioning

confidence: 99%

“…Furthermore, we have further reviewed and studied past research [10][11][12][13][14][15][16][17][18], and it is clear that most of the articles are focused on large modules (also known as standard modules) for the PID test. However, there are three influential differences from past studies for different combinations of modules, which contribute different degrees of production variances but result in some shortcomings such as testing time and production costs.…”

Section: Shortcomings and Contributions Of Previous Studies And Resea...mentioning

confidence: 99%

See 1 more Smart Citation

Prevention of PID Phenomenon for Solar Panel Based on Mathematical Data Analysis Models

Chen,

Hung,

Lin

et al. 2023

Mathematics

View full text Add to dashboard Cite

In recent years, the problem of potential-induced degradation (PID) phenomenon has been deeply associated with solar power issues because it causes serious power attenuation of solar panels and results in lowering its power generation efficiency. Thus, effectively identifying the PID problem from insights of industry data analysis to reduce production costs and increase the performance of power generation is an interesting and important subject for the solar power industry. Moreover, by the traditional standard rule (IEC62804) and the condition of a 96 h testing time, the costs of testing time and assembling materials against PID are very high and must be improved. Given the above reasons, this study proposes a hybrid procedure to organizes four mathematical methods: the mini-module testing, solar cell testing, a settling time, and a neural network, which are named as Method-1–Method-4, respectively, to efficiently solve the PID problem. Consequently, there are four key outcomes from the empirical results for solar power application: (1) In Method-1 with a 96 h testing time, it was found that the large module with higher costs and the mini module with lower costs have a positive correlation; thus, we can replace the large-module testing by the effective mini module for lower cost on module materials. (2) In Method-2 with a 24 h testing time, it was also found that the mini module and the solar cell are positively correlated; this result provides evidence that we can conduct the PID test by the easier solar cell to lower the costs. (3) In Method-3, the settling time achieves an average accuracy of 94% for PID prediction with a 14 h testing time. (4) In Method-4, the experimental result provides an accuracy of 80% when identifying the PID problem with the mathematical neural network model and are obtained within a 2 h testing time. From the above results, these methods succeed in reducing cost of materials and testing time during the manufacturing process; thus, this study has an industrial application value. Concurrently, Method-3 and Method-4 are rarely seen in the limited literature review for identifying PID problem; therefore, this study also offers a novel contribution for technical application innovation.

show abstract

Section: Basic Knowledge Related and Research Motivation Of The Studymentioning

confidence: 99%

Section: Shortcomings and Contributions Of Previous Studies And Resea...mentioning

confidence: 99%

Prevention of PID Phenomenon for Solar Panel Based on Mathematical Data Analysis Models

Chen,

Hung,

Lin

et al. 2023

Mathematics

View full text Add to dashboard Cite

show abstract

Potential induced degradation (PID): Review

Cited by 1 publication

References 24 publications

Prevention of PID Phenomenon for Solar Panel Based on Mathematical Data Analysis Models

Prevention of PID Phenomenon for Solar Panel Based on Mathematical Data Analysis Models

Contact Info

Product

Resources

About