Driven by industrial development and the rising population, the upward trend of electricity consumption is not going to curb. While the electricity suppliers make every endeavor to satisfy the needs of consumers, they are facing the plight of indirect losses caused by technical or non-technical factors. Technical losses are usually induced by short circuits, power outage, or grid failures. The non-technical losses result from humans’ improper behaviors, e.g., electricity burglars. Due to the restrictions of the detection methods, the detection rate in the traditional power grid is lousy. To provide better electricity service for the customers and minimize the losses for the providers, a leap in the power grid is occurring, which is referred to as the smart grid. The smart grid is envisioned to increase the detection accuracy to an acceptable level by utilizing modern technologies, such as cloud computing. With the aim of obtaining achievements of anomaly detection for electricity consumption with cloud computing, we firstly introduce the basic definition of anomaly detection for electricity consumption. Next, we conduct the surveys on the proposed framework of anomaly detection for electricity consumption and propose a new framework with cloud computing. This is followed by centralized and decentralized detection methods. Then, the applications of centralized and decentralized detection methods for the anomaly electricity consumption are listed. Finally, the open challenges of the accuracy of detection and anomaly detection for electricity consumption with edge computing are discussed.

在工业发展和人口增长的推动下，用电量的上升趋势不会受到抑制。在电力供应商尽一切努力满足消费者需求的同时，他们也面临着技术或非技术因素造成的间接损失的困境。技术损失通常是由短路，断电或电网故障引起的。非技术性损失是由人类的不当行为引起的，例如电贼。由于检测方法的限制，传统电网的检测率比较差。为了向客户提供更好的电力服务并最大程度地减少提供商的损失，正在发生电网的飞跃，这被称为智能电网。可以预见，智能电网将通过利用现代技术（例如云计算）将检测精度提高到可接受的水平。为了通过云计算获得用电量异常检测的成果，我们首先介绍用电量异常检测的基本定义。接下来，我们对拟议的用电量异常检测框架进行调查，并提出一个具有云计算的新框架。其次是集中式和分散式检测方法。然后，列举了集中式和分散式检测方法在异常用电量上的应用。最后，讨论了利用边缘计算对电能消耗进行检测和异常检测的准确性面临的开放性挑战。