Geographical and Climate Change Implications on Solar Photovoltaic Performance

Amoah, Matthew (2022) Geographical and Climate Change Implications on Solar Photovoltaic Performance. Doctoral thesis, Staffordshire University.

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Abstract or description

The performance of a Solar PV system depends largely on the weather conditions at the system location. For a better understanding of the effect of weather conditions on PV system performance, the weather conditions at the PV system location and generation data must be considered. A number of correlations have been identified between the geographical location of the PV system, the degradation rate, the life span, and the system's performance. It is well established that a PV system's location strongly affects its degradation rate, life span, and performance.

Africa, Europe, Asia, and North America all showed similar findings based on data monitored across four continents. The performance of the PV system depends on UV radiation levels at the system location. UV radiation, however, contributes to the degradation of PV system performance. PV panels' performance drops over time as they are exposed to UV radiation for a longer period. By providing cooling around the PV panels, the effect can be mitigated, the system's performance will be improved, and its life will be prolonged.

The performance of PV systems is influenced by temperature management during their existence. There is strong evidence that some periods during energy generation experienced a cooling wind and therefore had less impact on performance than other areas where the system experienced a lot of cooling conditions during high-temperature periods. Wind speed can mitigate much of the heat generated by the PV panels during energy generation, which is particularly important to prolong the lifespan of the PV system. It shows that cooling methods have a high level of effectiveness in improving PV performance because they control the temperature.

The results of the data study provided clear-cut guidance to be able to write software programming to represent the findings. Neural networking programming has been developed to predict PV system performance based on wind, temperature, UV, and rainfall inputs at any location from the research findings.

Item Type:	Thesis (Doctoral)
Faculty:	School of Digital, Technologies and Arts > Engineering
Depositing User:	Library STORE team
Date Deposited:	30 May 2023 14:26
Last Modified:	30 May 2023 14:26
URI:	https://eprints.staffs.ac.uk/id/eprint/7786

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