Research on maximum power point tracking of photovoltaic power generation based on improved hybrid optimization algorithm
Abstract Due to environmental factors’ influence, the power–voltage (P–V) curve of a photovoltaic array typically presents multiple peaks. The traditional gravitational search algorithm is inclined to fall into local optimal solutions and demonstrates poor performance in maximum power point tracking...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-02-01
|
| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-025-87694-1 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1832571788735807488 |
|---|---|
| author | Liming Wei Yuan Li |
| author_facet | Liming Wei Yuan Li |
| author_sort | Liming Wei |
| collection | DOAJ |
| description | Abstract Due to environmental factors’ influence, the power–voltage (P–V) curve of a photovoltaic array typically presents multiple peaks. The traditional gravitational search algorithm is inclined to fall into local optimal solutions and demonstrates poor performance in maximum power point tracking. Consequently, this paper proposes applying the PSO algorithm for optimizing the GSA parameters. Meanwhile, introducing the gravitational constant into the GSA algorithm accomplishes the dynamic adjustment of the three key parameters in PSO. Furthermore, the Levy flight step is incorporated to enhance the global search capability. The improved algorithm can improve the search speed and accuracy by adding memory and group interaction to the particle update formula to alleviate oscillation. Simulink modeling and simulation analysis reveals that, compared with traditional algorithms, the improved algorithm can identify the maximum power point of the photovoltaic array more rapidly and stably under static and dynamic shading conditions. |
| format | Article |
| id | doaj-art-5b5c6a3418b74048827104186b51de87 |
| institution | Kabale University |
| issn | 2045-2322 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj-art-5b5c6a3418b74048827104186b51de872025-02-02T12:18:19ZengNature PortfolioScientific Reports2045-23222025-02-0115111810.1038/s41598-025-87694-1Research on maximum power point tracking of photovoltaic power generation based on improved hybrid optimization algorithmLiming Wei0Yuan Li1College of Electrical and Computer Technology, Jilin Jianzhu UniversityCollege of Electrical and Computer Technology, Jilin Jianzhu UniversityAbstract Due to environmental factors’ influence, the power–voltage (P–V) curve of a photovoltaic array typically presents multiple peaks. The traditional gravitational search algorithm is inclined to fall into local optimal solutions and demonstrates poor performance in maximum power point tracking. Consequently, this paper proposes applying the PSO algorithm for optimizing the GSA parameters. Meanwhile, introducing the gravitational constant into the GSA algorithm accomplishes the dynamic adjustment of the three key parameters in PSO. Furthermore, the Levy flight step is incorporated to enhance the global search capability. The improved algorithm can improve the search speed and accuracy by adding memory and group interaction to the particle update formula to alleviate oscillation. Simulink modeling and simulation analysis reveals that, compared with traditional algorithms, the improved algorithm can identify the maximum power point of the photovoltaic array more rapidly and stably under static and dynamic shading conditions.https://doi.org/10.1038/s41598-025-87694-1 |
| spellingShingle | Liming Wei Yuan Li Research on maximum power point tracking of photovoltaic power generation based on improved hybrid optimization algorithm Scientific Reports |
| title | Research on maximum power point tracking of photovoltaic power generation based on improved hybrid optimization algorithm |
| title_full | Research on maximum power point tracking of photovoltaic power generation based on improved hybrid optimization algorithm |
| title_fullStr | Research on maximum power point tracking of photovoltaic power generation based on improved hybrid optimization algorithm |
| title_full_unstemmed | Research on maximum power point tracking of photovoltaic power generation based on improved hybrid optimization algorithm |
| title_short | Research on maximum power point tracking of photovoltaic power generation based on improved hybrid optimization algorithm |
| title_sort | research on maximum power point tracking of photovoltaic power generation based on improved hybrid optimization algorithm |
| url | https://doi.org/10.1038/s41598-025-87694-1 |
| work_keys_str_mv | AT limingwei researchonmaximumpowerpointtrackingofphotovoltaicpowergenerationbasedonimprovedhybridoptimizationalgorithm AT yuanli researchonmaximumpowerpointtrackingofphotovoltaicpowergenerationbasedonimprovedhybridoptimizationalgorithm |