Development of a bottom-up methodology for modelling electrical residential load from event data

Electricity utilities are increasingly targeting the residential load sector with energy management interventions, either in response to generation and transmission capacity constraints or with the view to realize energy savings in support of energy sustainability and environmental considerations. This increases the importance of load modelling for the residential sector, particularly with reference to appliance inventories, the associated usage patterns and end-user behaviour. Measurement and verification of the impacts of energy conservation measures introduced in this sector also requires more detailed statistical information on the energy consumption models for the individual load technologies found in typical domestic scenarios. Due to the distributed nature of residential loads and large and diverse end-user population, obtaining this information through measurements is expensive and time-consuming. This paper investigates a methodology and supporting database development for use in deriving statistically significant samples of load data for individual residential load components using inexpensive event loggers, including the implementation of a software application to derive the cumulative load profile using a bottom-up approach. Some results are given for a case study for a typical middle-income residential household.