Extended Analysis of Data Cleaning for Electrical Energy Consumption Data of Public Buildings

Abstract

In the past years both companies and academic's communities pulled their efforts in generating input that consist in new abstractions, interfaces, approaches for scalability and crowdsourcing techniques. Quantitative and qualitative methods were created with the scope of error reduction and were covered in multiple surveys and overviews in order to cope with outlier detection. The aim of tis paper is to provide an outlier analysis over the consumption data of twelve public buildings from the Technical University of Cluj-Napoca, collected during an EU 2020 Horizon project.