Frequency Monitoring Analysis based Power Quality Operational Data Management System

Abstract

In this work, a low-cost measurement solution (named PyFreqDAQ) has been developed to monitor the frequency of the electrical network, which is regarded a quality parameter of the electrical supply, and at the same time provide a more precise result thanks to the usage of the Allan variance. Software (Grafana) is available for free and can be used to track the frequency’s change over time in order to better understand how it is maintained within certain parameters. Two distinct techniques of calculating the frequency have been used to show the device’s power consumption. For starters, we’ll follow the guidelines established by IEC 61000-4-30 The Allan variance-based approach, on the other hand, uses an algorithm that offers a more precise frequency measurement and a GPS-traceable reference value. With the Allan variance-based method, one can expect improved precision and accuracy, as well as faster calculations and a wider range of observations. A significant advantage over other applications (e.g. labVIEWTM) is the flexibility demonstrated by Python while programming the data capture card and interacting with the database Because Python is a more powerful programming language, it allows for operations and calculations to be carried out using simple codes, while also allowing for minimal computational load and consuming considerably less working memory. To date, there hasn’t been any comparative research done between Python and LabVIEWTM.