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.

翻译：智能电网数据可在多个领域中进行异常检测评估，包括网络安全、故障检测、窃电检测等。异常行为可能由多种原因引起，包括用户异常的用电模式、电网基础设施故障、停电、外部网络攻击或能源欺诈等。近年来，智能电网的异常检测引起了研究人员的广泛关注，并广泛应用于多个高影响力领域。智能电网中最重大的挑战之一是对多种异常行为实现高效检测。本文对智能电网异常检测领域的最新研究进展进行了范围综述。我们从多个维度对研究进行分类，以深入理解和审视当前的研究挑战。最后，在分析现有研究空白的基础上，简要指出了智能电网系统异常检测的未来研究方向。