Version 1
: Received: 12 July 2024 / Approved: 15 July 2024 / Online: 15 July 2024 (07:58:56 CEST)
How to cite:
Kasmi, G.; Touron, A.; Blanc, P.; Saint-Drenan, Y.-M.; Fortin, M.; Dubus, L. Remote Sensing-Based Estimation of Rooftop Photovoltaic Power Production Using Physical Conversion Models and Weather Data. Preprints2024, 2024071128. https://doi.org/10.20944/preprints202407.1128.v1
Kasmi, G.; Touron, A.; Blanc, P.; Saint-Drenan, Y.-M.; Fortin, M.; Dubus, L. Remote Sensing-Based Estimation of Rooftop Photovoltaic Power Production Using Physical Conversion Models and Weather Data. Preprints 2024, 2024071128. https://doi.org/10.20944/preprints202407.1128.v1
Kasmi, G.; Touron, A.; Blanc, P.; Saint-Drenan, Y.-M.; Fortin, M.; Dubus, L. Remote Sensing-Based Estimation of Rooftop Photovoltaic Power Production Using Physical Conversion Models and Weather Data. Preprints2024, 2024071128. https://doi.org/10.20944/preprints202407.1128.v1
APA Style
Kasmi, G., Touron, A., Blanc, P., Saint-Drenan, Y. M., Fortin, M., & Dubus, L. (2024). Remote Sensing-Based Estimation of Rooftop Photovoltaic Power Production Using Physical Conversion Models and Weather Data. Preprints. https://doi.org/10.20944/preprints202407.1128.v1
Chicago/Turabian Style
Kasmi, G., Maxime Fortin and Laurent Dubus. 2024 "Remote Sensing-Based Estimation of Rooftop Photovoltaic Power Production Using Physical Conversion Models and Weather Data" Preprints. https://doi.org/10.20944/preprints202407.1128.v1
Abstract
The global photovoltaic (PV) installed capacity, vital for the electric sector decarbonation, has reached 1,552.3 GWp in 2023. In France, the capacity stood in April 2024 at 19.9 GWp. The growth of the PV installed capacity over a year was nearly 32% worldwide and 15.7% in France. However, integrating PV electricity into grids is hindered by poor knowledge of rooftop PV systems, constituting 20% of France's installed capacity, and the lack of measurements of the production stemming from these systems. This problem of lack of measurements of the rooftop PV power production is referred to as the lack of observability. Using ground truth measurements of individual PV systems, available at an unprecedented temporal and spatial scale, we show that estimating the PV power production of an individual rooftop system by combining solar irradiance and temperature data, the characteristics of the PV system inferred from remote sensing methods and an irradiation-to-electric power conversion model provides accurate estimations of the PV power production. Our study shows that we can improve rooftop PV observability, and thus its integration into the electric grid, using little information on these systems, a simple model of the PV system and weather data.
Keywords
photovoltaic energy; PV power estimation; rooftop PV; remote sensing; conversion model
Subject
Engineering, Electrical and Electronic Engineering
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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