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The operating temperature of photovoltaic (PV) modules is affected by external factors such as irradiance, wind speed and ambient temperature as well as internal factors like material properties and design properties. These factors can make a difference in the operating temperatures between cells within a module and between modules within a plant. This is a three-part thesis. Part 1 investigates the behavior of temperature distribution of PV cells within a module through outdoor temperature monitoring under various operating conditions (Pmax, Voc and Isc) and examines deviation in the temperature coefficient values pertaining to this temperature variation. ANOVA, a statistical tool, was used to study the influence of various factors on temperature variation. This study also investigated the thermal non-uniformity affecting I-V parameters and performance of four different PV technologies (crystalline silicon, CdTe, CIGS, a-Si). Two new approaches (black-colored frame and aluminum tape on back-sheet) were implemented in addition to the two previously-used approaches (thermally insulating the frame, and frame and back sheet) to study temperature uniformity improvements within c-Si PV modules on a fixed latitudetilt array. This thesis concludes that frame thermal insulation and black frame help reducing thermal gradients and next best viable option to improve temperature uniformity measurements is by using average of four thermocouples as per IEC 61853-2 standard. Part 2 analyzes the temperature data for two power plants (fixed-tilt and one-axis) to study the temperature variation across the cells in a module and across the modules in a power plant. The module placed in the center of one-axis power plant had higher temperature, whereas in fixed-tilt power plant, the module in north-west direction had ii higher temperatures. Higher average operating temperatures were observed in one-axis tracking as compared to the fixed-tilt PV power plant, thereby expected to lowering their lifetime. Part 3 focuses on the determination of a thermal model coefficients, using parameters similar to Uc and Uv thermal loss factors in PVsyst, for the modules of four different PV technologies experiencing hot-desert climate conditions by statistically correlating a year-long monitored data. Thermal models help to effectively quantity factors influencing module temperatures to estimate performance and energy models.
It depends upon the mounting structure Solar Panels are going to be installed.
And PVSyst also defines these values in the help section.
Normally free mounted is the highest you should go, and that is for the Pole mounted solar Panels, while the integeration with fully insulated back is the lowest of the preset values for as name suggests, the strings with insulated backs.
Here is the some information I found, hope this is helpfull
The determination of the parameters Uc and Uv is indeed a big question. We have some reliable measured data for free mounted arrays, but there is a severe lack of information when the modules are integrated. What value should be chosen according to the air duct sizes under the modules, and the length of the air path ?
It should be noticed that the heat capacity of the air is very low. Even with large air vents, the flowing air under the modules may quickly attain the equilibrium with the modules temperature at the end of the duct, leading to no heat exchange at all. Therefore for the top of the array the back-U value may be the fully insulated U-value; you can have big differences between the regions of the array near the air inlet, and at the outlet. PVsyst doesn't take this inhomogeneity of the array temperature into account.
On the other hand, the use of the wind dependence is very difficult. Reliable knowing of the wind velocity is extremely seldom (some programs construct synthetic hourly values from monthly data, but on which basis and with which models ?). And the "meteo quality" wind velocity (measured at 10 meter height in free environment) is not representative of the velocity at the array level (there may be a factor of 1.5 between them). In this respect the Uv value is obviously not the same for these two definitions of the wind velocity.
Photovoltaic depends in two factors
External factors like, irradiance, wind speed, & ambient temp.
Internal factors like, materials and design properties.
