  Datasets are important for researchers to build models and test how well
their machine learning algorithms perform. This paper presents the Rainforest
Automation Energy (RAE) dataset to help smart grid researchers test their
algorithms which make use of smart meter data. This initial release of RAE
contains 1Hz data (mains and sub-meters) from two a residential house. In
addition to power data, environmental and sensor data from the house's
thermostat is included. Sub-meter data from one of the houses includes heat
pump and rental suite captures which is of interest to power utilities. We also
show and energy breakdown of each house and show (by example) how RAE can be
used to test non-intrusive load monitoring (NILM) algorithms.
