Manar Mahmoud
Nearest-Neighbor-Based Approach for Aging Quantification of Photovoltaic Modules in a Utility-Scale PV Plant with Sun-Tracking Systems.
Rel. Filippo Spertino, Gabriele Malgaroli. Politecnico di Torino, Corso di laurea magistrale in Ingegneria Energetica E Nucleare, 2026
Abstract
In the context of the energy transition and the growing diffusion of renewable energy sources, photovoltaic technology plays an increasingly important role in the production of sustainable electricity. In particular, utility-scale photovoltaic plants (typically with rated power higher than 1 MW) represent the solution for large-scale energy generation, but they require increasingly accurate monitoring tools to ensure their reliability and their operational efficiency. The performance assessment of these plants is complex, since the generated power is strongly affected by environmental and operational conditions, including incident irradiance, module temperature, and shadowing. For this reason, a direct comparison between data acquired in different periods may lead to poorly representative conclusions, as possible differences in power output may be due not only to permanent losses, but also to different operating conditions.
This thesis proposes a data-driven method, implemented in Python ambient, to compare the performance of a utility-scale PV plant by identifying, within the dataset of each year under analysis, groups of real operating conditions that are as similar as possible
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