  Smart grid data can be evaluated for anomaly detection in numerous fields,
including cyber-security, fault detection, electricity theft, etc. The strange
anomalous behaviors may have been caused by various reasons, including peculiar
consumption patterns of the consumers, malfunctioning grid infrastructures,
outages, external cyber-attacks, or energy fraud. Recently, anomaly detection
of the smart grid has attracted a large amount of interest from researchers,
and it is widely applied in a number of high-impact fields. One of the most
significant challenges within the smart grid is the implementation of efficient
anomaly detection for multiple forms of aberrant behaviors. In this paper, we
provide a scoping review of research from the recent advancements in anomaly
detection in the context of smart grids. We categorize our study from numerous
aspects for deep understanding and inspection of the research challenges so
far. Finally, after analyzing the gap in the reviewed paper, the direction for
future research on anomaly detection in smart-grid systems has been provided
briefly.
