Bachelor- or Master-Thesis
AI-Driven Photovoltaic Energy Forecasting
13.03.2025, Abschlussarbeiten, Bachelor- und Masterarbeiten
Predicting PV energy generation over a 24-hour period is challenging due to the dynamic nature of solar irradiance and weather conditions. This thesis aims to develop innovative approaches that combine physical modeling of PV system performance with advanced machine learning techniques to generate accurate short-term forecasts.
The rapid expansion of solar photovoltaic (PV) installations worldwide has created a significant need for accurate energy forecasting to support grid stability and energy management. Predicting PV energy generation over a 24-hour period is challenging due to the dynamic nature of solar irradiance and weather conditions. This thesis aims to develop innovative approaches that combine physical modeling of PV system performance with advanced machine learning techniques to generate accurate short-term forecasts.
Kontakt: lingga_aksara.putra@tum.de
Mehr Information
https://www.epe.ed.tum.de/en/res/our-teaching-offer/our-bachelor-and-master-theses/
BA_MA_PV_Energy_Generation_AI_06.03.2025.pdf |
BA_MA_PV_Energy_Generation_AI_06.03.2025.pdf, PDF
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