Study of a New Hybrid Optimization-Based Method for Obtaining Parameter Values of Solar Cells
| Autor: | Selma Tchoketch_Kebir |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Computer science
020209 energy InformationSystems_INFORMATIONSTORAGEANDRETRIEVAL Data_FILES 0202 electrical engineering electronic engineering information engineering 02 engineering and technology 021001 nanoscience & nanotechnology 0210 nano-technology GeneralLiterature_REFERENCE(e.g. dictionaries encyclopedias glossaries) |
| DOI: | 10.5772/intechopen.93324 |
| Popis: | This chapter presents a comprehensive study of a new hybrid method developed for obtaining the electrical unknown parameters of solar cells. The combination of a traditional method and a recent smart swarm-based optimization method is done, with a big focus on the application of the topic of artificial intelligence algorithms into solar photovoltaic production. The combined approach was done between the traditional method, which is the noniterative Levenberg-Marquardt technic and between the recent meta-heuristic optimization technic, called Grey Wolf optimizer algorithm. For comparison purposes, some other classical solar cell parameter determination optimization-based methods are carried out, such as the numerical (iterative, noniterative) methods, the meta-heuristics (evolution, human, physic, and swarm) methods, and other hybrid methods. The final obtained results show that the used hybrid method outperforms the above-mentioned classical methods, under this study. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|