Contribution to a conference proceedings

FZJ-2025-04954

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Assessing the Impact of Ground-Based Cloud Observations on Photovoltaic Generation Forecast

Albanese, M. (Corresponding author)FZJ* ; Carta, D.FZJ* ; Löhnert, U.FZJ* ; Benigni, A.FZJ*

2025
IEEE

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Please use a persistent id in citations: doi:10.1109/IECON58223.2025.11221083

Abstract: The widespread integration of photovoltaic (PV) systems into modern power grids poses several operational challenges, primarily due to the stochastic nature of weather conditions, which leads to uncertainty in power generation. In this context, accurate forecasting of PV output becomes critical, especially for electricity markets and grid management. This paper investigates the relationship between non-conventional weather variables (i.e., ground-based cloud observations) and PV power generation, and evaluates the impact of incorporating such data into a machine learning model to improve forecasting performance. The analysis is conducted using real power output and ground-based meteorological data collected at Forschungszentrum Jülich, in Germany.

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Contributing Institute(s):

1. Modellierung von Energiesystemen (ICE-1)

Research Program(s):

1. 1122 - Design, Operation and Digitalization of the Future Energy Grids (POF4-112) (POF4-112)
2. 1123 - Smart Areas and Research Platforms (POF4-112) (POF4-112)

Appears in the scientific report 2025

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