Statistical Analysis of Power System Frequency Measurements Based on Motif Theory

Modern power systems have been experiencing unexpected challenges of system-wide power balance in the face of intermittent renewable energy generation and extreme societal events (e.g., pandemic). In principle, frequency is a global indicator of power system operational security, especially the shortage or surplus of active power. Inspired by the motif theory, we extract the variation patterns of large-scale historical frequency measurements from the complex network perspective. In particular, recent data records of the Great Britain (GB) power system are studied as an example. It is then found that, in this system, the frequency variation reveals anomalous patterns in 2018 and in the summer of 2020, which are consistent with the maximum generation/load percentage margin and the societal influences of COVID-19, respectively. It is finally concluded that the proposed method could serve as a powerful and trustworthy tool to perform big data analysis of operational characteristics.