# Anomaly Detection Techniques in Smart Grid Systems: A Review

arXiv: https://arxiv.org/abs/2306.02473 · HTML: https://mlsanity.com/paper/2306.02473/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 5 of its 45 references that are in the map.
- First posted on arXiv 4 Jun 2023.

## Builds on (most cited first, 5 of 5)

- [Smart Anomaly Detection in Sensor Systems: A Multi-Perspective Review](https://mlsanity.com/paper/2010.14946/) (2020)
- [Time Series Anomaly Detection for Smart Grids: A Survey](https://mlsanity.com/paper/2107.08835/) (2021)
- [Regression-based Online Anomaly Detection for Smart Grid Data](https://mlsanity.com/paper/1606.05781/) (2016)
- [A New Era of Mobility: Exploring Digital Twin Applications in Autonomous Vehicular Systems](https://mlsanity.com/paper/2305.16158/) (2023)
- [Implementing Man-in-the-Middle Attack to Investigate Network Vulnerabilities in Smart Grid Test-bed](https://mlsanity.com/paper/2306.00234/) (2023)

## Built on by (most cited first, 2 of 2)

- [Large Language Models for Power System Security: A Novel Multi-Modal Approach for Anomaly Detection in Energy Management Systems](https://mlsanity.com/paper/2508.10044/) (2025)
- [Real-Time Adaptive Anomaly Detection in Industrial IoT Environments](https://mlsanity.com/paper/2601.03085/) (2026)

## Abstract (arXiv)

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.