  Many countries are rolling out smart electricity meters. These measure a
home's total power demand. However, research into consumer behaviour suggests
that consumers are best able to improve their energy efficiency when provided
with itemised, appliance-by-appliance consumption information. Energy
disaggregation is a computational technique for estimating
appliance-by-appliance energy consumption from a whole-house meter signal.
  To conduct research on disaggregation algorithms, researchers require data
describing not just the aggregate demand per building but also the `ground
truth' demand of individual appliances. In this context, we present UK-DALE: an
open-access dataset from the UK recording Domestic Appliance-Level Electricity
at a sample rate of 16 kHz for the whole-house and at 1/6 Hz for individual
appliances. This is the first open access UK dataset at this temporal
resolution. We recorded from five houses, one of which was recorded for 655
days, the longest duration we are aware of for any energy dataset at this
sample rate. We also describe the low-cost, open-source, wireless system we
built for collecting our dataset.
