This tutorial shows you how to use DataWorks together with Machine Learning Platform for AI (PAI) to automatically identify users who steal electricity. This makes sure that users use electricity in a safe manner.
The traditional methods of identifying electricity theft and metering device failures include regular inspection, regular check of electricity meters, and users' reporting of electricity theft. These methods require manual operations. In addition, these methods are inefficient if you want to identify users who steal electricity or are involved in electricity leakage.
Currently, the staff of power supply bureaus, such as those who inspect electricity marketing and who check and meter electricity usage, use the existing automated system for metering electricity usage. To monitor electricity usage online, they use the system to trigger alerts for abnormal electricity usage and query electricity usage data. The system collects data about abnormal electricity usage, abnormal load, abnormal line loss, and alerts reported by terminals, and builds models for analyzing the data. In this way, relevant staff can identify electricity theft, electricity leakage, and metering device failures in real time. After alerts are triggered, the system builds models for analyzing abnormal electricity usage based on the current, voltage, and load before and after the alert time. This also helps relevant staff identify electricity theft, electricity leakage, and metering device failures.
The existing automated system for metering electricity usage can monitor abnormal electricity usage. However, due to frequent false positives and false negatives, it is difficult to precisely identify users who steal electricity or are involved in electricity leakage. In addition, experts need to determine the weight of each metric for the model to be built based on their knowledge and experience. This process is subjective.
The existing automated system for metering electricity usage can collect all kinds of electricity load data, such as the current, voltage, and power data, and alert data that terminals report. Electrical inspection staff can also collect electricity theft and leakage data from the online inspection system or by conducting on-site inspection.
Based on the preceding data, DataWorks together with PAI can abstract key features of users who steal electricity or are involved in electricity leakage and build a model for identifying such users. In this way, electricity theft or leakage can be automatically detected. This reduces the inspection workload of electrical inspection staff and guarantees normal and secure electricity usage.