Managing the Quality of Smart Grid Data

The Smart Grid (SG) concept reflects the integration of Information and Communication Technologies (ICT) together with Internet of Things (IoT) technologies into the electrical power grid, which enables devices to produce data regarding their energy consumption and, by that, to manage the electricity consumption and production in a smarter way. The vast amounts of data generated and processed in SG environments raise the issue of data quality (DQ) management. The "Quality of Context" approach observes DQ from a business-value perspective, focusing more on data contents and use and less on its physical characteristics. Accordingly, this study explores two SG-relevant DQ aspects - sampling frequency and density. The former reflect the high sampling rate needed for ubiquitous computing environments such as the SG, while the latter reflects real-world limitations on sensor infrastructures. As the study progresses, our goal is to further conceptualize these DQ dimensions and evaluate their impact in both simulated and real-world SG environments, toward defining mechanism for their optimal configuration.