DEVELOPING A STRATEGY FOR GENERATING ELECTRICAL LOAD
Electricity consumption data profiles that include details on the consumption
can be generated with a bottom-up load models. In this paper 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. The modeling is based on a simplified approach where openly
available data and statistics are used, i.e. data that is subject to privacy
limitations, such as smart meter measurements are excluded.
Authors Name: Ekaba S. O., Ekoko U., Chiadika M, Ofili C.C
Email: ekaba.samuel@mydspg.edu.ng