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http://hdl.handle.net/10362/160362| Title: | Como prever o efeito do soiling em sistemas fotovoltaicos? |
| Author: | Rodrigues, Marta Lourenço |
| Advisor: | Costa, Ana Cristina Marinho da |
| Keywords: | Solar panels Solar Efficiency Soiling SDG 7 - Affordable and clean energy SDG 9 - Industry, innovation and infrastructure SDG 12 - Responsible production and consumption SDG 13 - Climate action |
| Defense Date: | 25-Oct-2023 |
| Abstract: | Electricity is a form of secondary energy as it is obtained by converting other forms of energy. These energies can be classified as renewable or non-renewable. In this dissertation, the focus will be on renewable energies, more specifically on photovoltaic solar energy. The production of a solar panel is affected by the environment that surrounds it, the local meteorology and by its characteristics, this study aims to analyze the spatial distribution of these equipments and their production efficiency in Continental Portugal considering several factors (either physical or external to the equipment, such as meteorology or soiling). Soiling is the phenomenon in which the panel loses efficiency due to the accumulation of dust or particles on its surface. Due to the lack of information on the effect of soiling on the energy efficiency of solar panels according to their location, this study will focus more deeply on this phenomenon. To identify which are the local characteristics that most affect the efficiency of each solar panel, Multiscale Geographically Weighted Regression models were estimated with a set of explanatory factors that, supported by several studies, represent the effect of soiling. The results show that wind speed is positively correlated with efficiency on a global scale, and that irradiation has a negative impact on a regional scale in southern Portugal. It is suggested that in future studies data with greater spatial and temporal resolution be used, in particular monthly or seasonal data. |
| Description: | Dissertation presented as the partial requirement for obtaining a Master's degree in Statistics and Information Management, specialization in Risk Analysis and Management |
| URI: | http://hdl.handle.net/10362/160362 |
| Designation: | Mestrado em Estatística e Gestão de Informação, especialização em Análise e Gestão de Risco |
| Appears in Collections: | NIMS - Dissertações de Mestrado em Estatística e Gestão da Informação (Statistics and Information Management) |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| TEGI2289.pdf | 3,55 MB | Adobe PDF | View/Open |
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