A comparative analysis of smart metering data aggregation performance

Abstract

In the Smart Grid era fine-grained energy information pertaining real world processes can be collected and may reveal new insights if these can be analyzed in real-time. Energy “Big Data” analytics can lead to a plethora of new innovative applications and enhance decision making processes. However, to do so, we need new enterprise tools and approaches that can take into consideration the specifics of the energy domain and offer high performance analytics on its raw data. In this work, experiments are conducted to measure the performance of the different levels of energy data aggregation. Thousands of smart meters are aggregated, by usage of the collected energy readings from a real-world trial. Using a selected dataset, the traditional database system (row-based) performance is compared to the emerging column-based approach in order to assess the suitability for real-time analytics in such scenarios.