Article,
A model for generating household electricity load profiles
International Journal of Energy Research, (2006)
Abstract
Electricity consumption data profiles that include details on the
consumption can be generated with a bottom-up load models. In these
models the load is constructed from elementary load components that
can be households or even their individual appliances. In this work
a simplified bottom-up model is presented. The model can be used
to generate realistic domestic electricity consumption data on an
hourly basis from a few up to thousands of households. The model
uses input data that is available in public reports and statistics.
Two measured data sets from block houses are also applied for statistical
analysis, model training, and verification. Our analysis shows that
the generated load profiles correlate well with real data. Furthermore,
three case studies with generated load data demonstrate some opportunities
for appliance level demand side management (DSM). With a mild DSM
scheme using cold loads, the daily peak loads can be reduced 7.2%
in average. With more severe DSM schemes the peak load at the yearly
peak day can be completely levelled with 42% peak reduction and sudden
3 h loss of load can be compensated with 61% mean load reduction.
