Data-driven sOLar Massive deployment in European Nations – DOLMEN

The DOLMEN project aims to accelerate the energy transition through the development of a scalable, data-driven approach for the deployment of rooftop photovoltaic (RPV) systems at large scale. Rooftop PV systems significantly contribute to reducing greenhouse gas emissions, but effective deployment requires precise mapping of existing installations and identification of suitable new locations. DOLMEN addresses these needs by combining physical modeling and advanced data-driven methods to systematically map existing and potential PV installations.

The project has five main objectives: (1) develop a comprehensive and exhaustive methodology to locate existing rooftop PV systems; (2) account for heterogeneity by implementing robust and adaptive models based on federated artificial intelligence to handle diverse local conditions; (3) analyze the spatial and temporal dynamics of RPV deployment, including socio-economic drivers and barriers; (4) build a scalable and transferable framework applicable to different regions and countries; and (5) provide open, transparent, and user-friendly tools and datasets for both expert and non-expert stakeholders.

The methodology is structured into three work packages. WP1 focuses on creating a harmonized database using high-resolution aerial imagery, building registry datasets, and socio-economic information. WP2 develops scalable models for identifying PV systems, using federated artificial intelligence and irradiance modeling to ensure robust results across diverse datasets. WP3 examines the spatial and temporal dynamics of solar PV adoption to identify key influencing factors and generate predictive deployment scenarios.

DOLMEN will produce scientific knowledge, datasets, and practical tools for researchers, urban planners, grid operators, and policymakers. By combining technical, socio-economic, and urban planning aspects, the project directly supports ANR's goals for a sustainable energy transition.