Photovoltaic (PV) energy generation plays a crucial role in the energy transition. Small-scale, rooftop PV installations are deployed at an unprecedented pace, and their safe integration into the grid requires up-to-date, high-quality information. Overhead imagery is increasingly being used to improve the knowledge of rooftop PV installations with machine learning models capable of automatically mapping these installations. However, these models cannot be reliably transferred from one region or imagery source to another without incurring a decrease in accuracy. To address this issue, known as distribution shift, and foster the development of PV array mapping pipelines, we propose a dataset containing aerial images, segmentation masks, and installation metadata (i.e., technical characteristics). We provide installation metadata for more than 28000 installations. We supply ground truth segmentation masks for 13000 installations, including 7000 with annotations for two different image providers. Finally, we provide installation metadata that matches the annotation for more than 8000 installations. Dataset applications include end-to-end PV registry construction, robust PV installations mapping, and analysis of crowdsourced datasets.

In 2013, the European Network of Transmission System Operators (TSOs) for electricity (ENTSO-E) created the Pan-European Climate Database (PECD), a tool that has underpinned most studies conducted by TSOs ever since. So far, the different versions of the PECD have used so-called modern-era ‘reanalysis’ products that represent a gridded amalgamation of historical conditions from observations. However, scientific evidence suggests, and recent European regulation requires, that power system adequacy studies should take climate change into account when estimating the future potential of variable renewable resources, such as wind, solar and hydro, and the impact of temperature on electricity demand. This paper explains the need for future climate data in energy systems studies and provides high-level recommendations for building a future-proof reference climate dataset for TSOs, not just in Europe, but also globally.

The EU Copernicus Climate Change Service (C3S) has produced an operational climate service, called C3S Energy, designed to enable the energy industry and policymakers to assess the impacts of climate variability and climate change on the energy sector in Europe. The C3S Energy service covers different time horizons, for the past 40 years and the future. It provides time series of electricity demand and supply from wind, solar photovoltaic and hydropower, and can be used for recent trends analysis, seasonal outlooks or the assessment of climate change impacts on energy mixes in the long term. This article introduces this service and the resulting dataset, with a focus on the design and validation of the energy conversion models, based on ENTSO‐E energy data and the ERA5 climate reanalysis. Flexibility and coherence across all countries have been preferred upon models' accuracy. However, the comparison with ENTSO‐E data shows that the models provide plausible energy indicators and, in particular, allow comparing climate variability effects on power demand and generation in a harmonized manner all over Europe.