Adapted Methods from Statistical Process Control for Evaluation of Load Variations in Distribution Grids

Abstract

In this work, we propose the application of methods from Statistical Process Control (SPC) to evaluate and classify online load variations as neglectable common or as critical variations that require immediate actions. The SPC strategy is adapted to the specific requirements of load profile variation analysis and could offer a low-requirement option to cope with data unavailability in distribution grids. We investigate the feasibility of two control charts, Shewhart and exponentially weighted moving average, to provide insight into the development of the aggregated load profile in areas with limited monitoring and without communication with individual consumers. The performance of the control charts is compared in terms of deviation detection. To investigate the effect of data availability, load variations for 74 households are categorized according to the season, day and time of the day. Finally, the results of the adapted SPC method applied with specific and with general deviation information is compared. Tests showed that the adapted SPC method is feasible to support assumptions about the load curve trend if its limitations are taken into account.