Developing a Strategy for Generating Electrical Load
Ekaba s.o #, Ekoko u*,Ofili c.c# ,Mario Chiadika*
# Department of Electrical/Electronic Engineering (DSPG)
* Department of Computer Engineering (DSPG)
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.