As power quality becomes a higher priority in the electric utility industry, the amount of disturbance event data continues to grow. Utilities do not have the required personnel to analyze each event by hand. This work presents an automated approach for analyzing power quality events recorded by digital fault recorders and power quality monitors operating within a power transmission system. The automated approach leverages rule-based analytics to examine the time and frequency domain characteristics of the voltage and current signals. Customizable thresholds are set to categorize each disturbance event. The events analyzed within this work include various faults, motor starting, and incipient instrument transformer failure. Analytics for fourteen different event types have been developed. The analytics were tested on 160 signal files and yielded an accuracy of ninety-nine percent. Continuous, nominal signal data analysis is performed using an approach coined as the cyclic histogram. The cyclic histogram process will be integrated into the digital fault recorders themselves to facilitate the detection of subtle signal variations that are too small to trigger a disturbance event and that can occur over hours or days. In addition to reducing memory requirements by a factor of 320, it is anticipated that cyclic histogram processing will aid in identifying incipient events and identifiers. This project is expected to save engineers time by automating the classification of disturbance events and increase the reliability of the transmission system by providing near real time detection and identification of disturbances as well as prevention of problems before they occur.

翻译：随着电能质量在电力公用事业行业中日益受到重视，扰动事件数据量持续增长。然而，电力公司缺乏足够的人员对每个事件进行人工分析。本文提出一种自动化方法，用于分析输电系统中数字故障录波器与电能质量监测装置记录的扰动事件。该方法利用基于规则的解析技术，通过检查电压和电流信号的时域与频域特性，并设置可自定义阈值，对每个扰动事件进行分类。本研究分析的事件类型包括各类故障、电机启动以及初期互感器故障。目前已开发出针对十四种不同事件类型的解析算法。该算法经160个信号文件测试，准确率达99%。对于持续的标称信号数据，本文采用一种称为"循环直方图"的方法进行分析。该循环直方图流程将集成至数字故障录波器中，以检测因幅值过小无法触发扰动事件、且可能持续数小时或数天的细微信号变化。除将存储器需求降低至原始值的1/320外，循环直方图处理预计还能辅助识别初期事件及征兆。通过自动化扰动事件分类、提供近实时扰动检测与辨识能力，以及实现问题预防，本项目有望节省工程师时间并提升输电系统的可靠性。