{"title":"Computer Modeling of the Temperature Regime of Solar Panels using Global Climate Databases","authors":"L. Knysh, D. Zakharov","doi":"10.3103/S0003701X24600115","DOIUrl":null,"url":null,"abstract":"<p>The results of computer modeling of temperature distribution in the layers of a solar panel, obtained using global climate databases, are presented. The non-stationary mathematical model for determining temperatures in the solar panel included approximation functions for solar flux density, wind speed, and ambient temperature. The approximation functions corresponded to the selected day of the year and the geographic data. These approximation functions were constructed in the program code based on regression analysis of data from global climate databases, both in real-time and archived. The adequacy of the mathematical model, numerical algorithm, and computer simulation results was confirmed through comparison with experimental data. The proposed approach allows determining the impact of real climate data on the temperature of the solar panel, identifying the errors when using average climate data for the solar panel’s location, finding the correlation between changes in climate data during daylight and the temperature regime of the solar panel, and calculating changes in the solar panel’s efficiency based on its temperature. Computer modeling was performed for a solar panel in which polycrystalline silicon solar cells were positioned between two glass surfaces. However, the proposed approach is universal and, with minor modifications, can be used to determine the thermal and energy characteristics of a solar panel with any design and any type of solar cells.</p>","PeriodicalId":475,"journal":{"name":"Applied Solar Energy","volume":"60 4","pages":"595 - 603"},"PeriodicalIF":1.2040,"publicationDate":"2024-12-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Solar Energy","FirstCategoryId":"1","ListUrlMain":"https://link.springer.com/article/10.3103/S0003701X24600115","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Energy","Score":null,"Total":0}
Computer Modeling of the Temperature Regime of Solar Panels using Global Climate Databases
The results of computer modeling of temperature distribution in the layers of a solar panel, obtained using global climate databases, are presented. The non-stationary mathematical model for determining temperatures in the solar panel included approximation functions for solar flux density, wind speed, and ambient temperature. The approximation functions corresponded to the selected day of the year and the geographic data. These approximation functions were constructed in the program code based on regression analysis of data from global climate databases, both in real-time and archived. The adequacy of the mathematical model, numerical algorithm, and computer simulation results was confirmed through comparison with experimental data. The proposed approach allows determining the impact of real climate data on the temperature of the solar panel, identifying the errors when using average climate data for the solar panel’s location, finding the correlation between changes in climate data during daylight and the temperature regime of the solar panel, and calculating changes in the solar panel’s efficiency based on its temperature. Computer modeling was performed for a solar panel in which polycrystalline silicon solar cells were positioned between two glass surfaces. However, the proposed approach is universal and, with minor modifications, can be used to determine the thermal and energy characteristics of a solar panel with any design and any type of solar cells.
期刊介绍:
Applied Solar Energy is an international peer reviewed journal covers various topics of research and development studies on solar energy conversion and use: photovoltaics, thermophotovoltaics, water heaters, passive solar heating systems, drying of agricultural production, water desalination, solar radiation condensers, operation of Big Solar Oven, combined use of solar energy and traditional energy sources, new semiconductors for solar cells and thermophotovoltaic system photocells, engines for autonomous solar stations.