Photovoltaics at home: Current status, future pathways, and impacts on electricity demand
Abstract
Peer-reviewed paper 4-187-26 Rooftop photovoltaic (RPV) panels are becoming increasingly common in Europe. Public subsidies, declining technology costs, and attractive feed-in tariffs have helped to leverage this technology. In France, national-level statistics based on peak power are regularly updated by the French distribution system operator and other official bodies. However, they only offer a partial picture, as many variables needed to create accurate models are missing. To address this gap, the Base de Données Photovoltaïque (photovoltaic database) (BDPV), an initiative driven by an association of photovoltaic panel owners, collects comprehensive data on thousands of installations (13,777). While this database offers valuable insights, it relies on a voluntary basis and thus cannot guarantee statistical representativeness. In this paper, we compared and cross-referenced several data sources to create a consolidated representation of the stock of French residential RPV installations, including key variables required for modelling photovoltaic production (peak power, tilt angle, orientation). A photovoltaic model suitable for this level of detail was then developed and validated against the empirical daily production data for a sample of 1,000 RPVs from the BDPV. On average, the model exhibits a bias of 16% (NMBE) and a CVRMSE of 32%. Finally, using an initial prospective scenario, we assess the impact of a full deployment of residential RPV on electricity demand using standard indicators of residential RPV production.
Related
- Climate change impacts on the predicted performance of optimized building-integrated photovoltaics
- Towards sustainable catalyst production: A prospective life cycle assessment of resource-efficient Ni-CeO2 scale-up across current and future electricity mixes
- In-situ groundwater level monitoring reveals worldwide status, trends and impacts
- Impacts of Two Land-Use Conversion Pathways on Soil Properties and Microbial Communities in Tropical Forests of Hainan Island.
- River Sand and Gravel Mining: Global Drivers, Impacts, and Pathways for Sustainable Management
BibTeX
@article{moreau2026photovoltaics,
title = {{Photovoltaics at home: Current status, future pathways, and impacts on electricity demand}},
author = {Valentin Moreau and Evan Grimaud and Guillaume Binet and Yves-Marie Saint-Drenan and David Trebosc and Durca Pathmanathan},
journal = {eceee Summer Study proceedings},
year = {2026},
month = jul,
doi = {10.66506/essp.4-187-26},
url = {https://minesparis-psl.hal.science/hal-05750704v1},
note = {CC BY},
}
RIS
TY - JOUR
TI - Photovoltaics at home: Current status, future pathways, and impacts on electricity demand
AU - Valentin Moreau
AU - Evan Grimaud
AU - Guillaume Binet
AU - Yves-Marie Saint-Drenan
AU - David Trebosc
AU - Durca Pathmanathan
PY - 2026
DA - 2026/07/16
JO - eceee Summer Study proceedings
DO - 10.66506/essp.4-187-26
UR - https://minesparis-psl.hal.science/hal-05750704v1
AB - Peer-reviewed paper 4-187-26 Rooftop photovoltaic (RPV) panels are becoming increasingly common in Europe. Public subsidies, declining technology costs, and attractive feed-in tariffs have helped to leverage this technology. In France, national-level statistics based on peak power are regularly updated by the French distribution system operator and other official bodies. However, they only offer a partial picture, as many variables needed to create accurate models are missing. To address this gap, the Base de Données Photovoltaïque (photovoltaic database) (BDPV), an initiative driven by an association of photovoltaic panel owners, collects comprehensive data on thousands of installations (13,777). While this database offers valuable insights, it relies on a voluntary basis and thus cannot guarantee statistical representativeness. In this paper, we compared and cross-referenced several data sources to create a consolidated representation of the stock of French residential RPV installations, including key variables required for modelling photovoltaic production (peak power, tilt angle, orientation). A photovoltaic model suitable for this level of detail was then developed and validated against the empirical daily production data for a sample of 1,000 RPVs from the BDPV. On average, the model exhibits a bias of 16% (NMBE) and a CVRMSE of 32%. Finally, using an initial prospective scenario, we assess the impact of a full deployment of residential RPV on electricity demand using standard indicators of residential RPV production.
SN - 2001-7960
SN - 2001-7960
ER -