Computing and data visualisation for selected problems in solar energy using python programming language.
| dc.contributor.author | Lungu, Misheck | |
| dc.date.accessioned | 2025-01-17T08:49:27Z | |
| dc.date.available | 2025-01-17T08:49:27Z | |
| dc.date.issued | 2024 | |
| dc.description | Thesis of Master of Science in Physics. | |
| dc.description.abstract | Solar energy plays a vital role in reducing energy deficits by providing a renewable and sustainable power source, and it significantly reduces contributions to climate change compared to fossil fuels. A deeper understanding of the concepts involved in the study of solar energy is crucial for the development of more efficient systems. Many textbooks contain key concepts such as mathematical expressions, tabulated values, and graphical representations that are used as pedagogical tools for the mastery of the subject. However, many of these tools are not interactive and may not be able to provide solutions in real-time. Therefore, this study addresses this gap by developing a user-friendly graphical interface for solving, simulating and visualizing six key solar energy problems. The codes were created using Python 3 and its libraries from the Jupyter Notebook environment. To empower user interaction and variable control, Ipywidgets, a Jupyter Notebook library was used. Later, the codes were migrated to the Tkinter framework for further development. The developed graphical user interface (GUI) applications were converted into executable files which were deployed on Windows systems. By facilitating real-time problem solving and data visualization the applets can enhance learning and empower researchers. | |
| dc.identifier.uri | https://dspace.unza.zm/handle/123456789/9092 | |
| dc.language.iso | en | |
| dc.publisher | The University of Zambia | |
| dc.title | Computing and data visualisation for selected problems in solar energy using python programming language. | |
| dc.type | Thesis |