Impact of Spatial Aggregation on Electricity Profiles

Abstract

The increasing use of renewable energy and the spread of smart energy services require detailed studies of the system load. The data from the advanced metering infrastructure assist these requirements by providing detailed picture of electricity consumption patterns and profiles. However, high resolution electricity data can cause computational challenges and privacy concerns. As a result, the data are often spatially aggregated. This paper investigates the impact of data aggregation on the data understanding and the electricity load characteristics. The study looks at the similarity among different groups combinations within the same aggregation level, the variation in the load diversity and peaks occurrences, and on the hourly electricity variations between the individual customer and its aggregated group. The study concludes that the individual customers' behaviors are lost with the increasing levels of aggregation, and that the similarity among groups on the same aggregation level increases with the aggregation level.