  The growing demand for electrified heating, electrified transportation, and
power-intensive data centres challenge distribution networks. If
electrification projects are carried out without considering electrical
distribution infrastructure, there could be unexpected blackouts and financial
losses. Datasets containing real-world distribution network information are
required to address this. On the other hand, social data, such as household
heating composition, are closely coupled with people's lives. Studying the
coupling between the energy system and society is important in promoting social
welfare. To fill these gaps, this paper introduces two datasets. The first is
the main dataset for the distribution networks in Great Britain (GB),
collecting information on firm capacity, peak demands, locations, and parent
transmission nodes (the Grid Supply Point, namely GSP) for all primary
substations (PSs). PSs are a crucial part of the UK distribution network and
are at the lowest voltage level (11 kV) with publicly available data for most
UK Distribution Network Operators (DNOs). Substation firm capacity and peak
demand facilitate an understanding of the remaining room of the existing
network. The parent GSP information helps link the dataset of distribution
networks to datasets of transmission networks. The second dataset extends the
main network dataset, linking each PS to information about the number of
households that use different types of central heating recorded in census data.
The derivation of the second dataset is based on locations of PSs collected in
the main dataset with appropriate assumptions. The derivation process may also
be replicated to integrate other social datasets.
