[OC] UK Domestic Electricity By Property Type, Month, Heat Pump, EV And Tariff — 150 Cohorts With Hourly Load Shapes, Derived From 3M Smart-meter-based Profiles (CSV/JSON, CDLA-Permissive-2.0)

Centre for Net Zero’s Faraday dataset (OpenSynth) is excellent and effectively

unusable casually — it’s ~6GB of parquet with the load profiles stored as

delimited strings. So I aggregated it and published the result.

150 cohorts, each with a mean daily total, a 24-hour load shape, and deciles

where the cell was thick enough:

– baseline (no solar/battery/EV/heat pump)

– property type, EPC band, and the cross-tab

– month

– tariff type (standard / Economy 7 / smart / automated)

– heat pump: with vs without, unmatched, matched on property+EPC, by month,

and by tariff

– EV: with vs without, and by tariff

– LSOA k-means cluster

Cross-check, which is the reason to trust any of it: baseline comes out at

9.737 kWh/day and a median of 8.31. SERL Statistics Report 1 — separate

source, ~13,000 real metered GB homes — publishes a mean of 9.8 and a median

of 8.2. Two moments of the distribution, two unrelated datasets, ~1% apart.

Limitations, up front:

– Synthetic. Faraday is a generative model trained on ~1bn smart meter

readings from Octopus customers, who over-index on smart tariffs and LCT.

– No household identifier, so the deciles are over household-DAYS, not

households. That spread is wider than the between-home spread — treat it

as an upper bound. It’s recorded in `distributionOver` in the JSON.

– EPC band moves consumption by <0.1% within a property type, including for

heat pump households where insulation should dominate. I read that as the

model being under-conditioned on EPC rather than a finding about housing,

and I’ve built nothing on those cuts. Published anyway — a null result is

still a result.

– `cluster_label` is a k-means grouping of LSOAs on socio-demographic

features, NOT geography. Published as clusters, never as regions. Each

cluster’s country mix (from LSOA code prefixes) is included so you can join

your own geography.

– Cohorts under 500 profiles are dropped rather than published thin.

CSV and JSON, CDLA-Permissive-2.0 (same as the source), no registration.

Derivation script is in the repo and reproduces the file exactly.

https://www.energycosting.co.uk/data/uk-domestic-electricity

All credit to Centre for Net Zero for Faraday — I’ve only aggregated it.