  The issue of estimating the detailed appliance level load consumption has
received considerable attention. This paper first presents a Labelled
hIgh-Frequency daTaset for Electricity Disaggregation (LIFTED), which can be
used for research on nonintrusive load monitoring (NILM). This dataset consists
of one-week detailed appliance-level electricity usage information including
voltage, current, active power, and reactive power for a single apartment in
the United States, down-sampled at 50Hz. This paper also proposes an efficient
Lossless Coding considering Precision (LCP) algorithm on data compression. This
algorithm considers both the precision requirements of practical applications
on load datasets and the unique characteristics of household appliance-level
load datasets. The LCP algorithm is tested on the LIFTED dataset and the
results demonstrate that LCP can achieve a higher compression ratio compared to
several existing algorithms.
