Deriving model approximations in emerging distribution grids

Data received with high reporting rates and aggregated data from measurement equipment (i.e. with lower reporting rates and usually complying with power quality time-aggregation standards) are sometimes used in the same application. This is raising the question of merging the two types of information and assessing the quality of the result. Modern control algorithms process information acquired from distributed, synchronized measurement systems. Their requirements are difficult to meet when multiple measurement approaches are simultaneously used: on one side, the existing time-aggregation assessments in SCADA framework, including smart meters; on the other side, the high-resolution waveform-based monitoring devices like PMUs with fault-recorder functionality which are increasingly deployed in distribution systems. In this paper we propose a methodology for assessing the variability of a particular quantity in the monitored power network while using two different reporting rates and time-aggregation algorithms.