This thesis presents a modern approach to data acquisition and analysis of power quality using smart meters. In today’s power systems, where the operation of devices and processes heavily depends on the stability and reliability of the electricity supply, monitoring power quality is of critical importance. Poor power quality can lead to various issues, such as network overloads, equipment failures, motor overheating, and disruptions in sensitive electronic systems.
Measuring and monitoring power quality allows for timely detection of such problems and the implementation of appropriate corrective actions. A key tool in this process is power quality analysis (PQ analysis), which includes parameters such as voltage, frequency, harmonic distortions, and fliker. The analysis is based on the guidelines of the SIST EN 50160 standard, which defines the permissible limits of these parameters in distribution systems.
The practical part of the thesis focuses on the use of real measurement data obtained from already installed smart meters in the electricity distribution network. The data is processed using the analytical environment e.Point.SCAN, which enables accurate monitoring of key power quality indicators and checking their compliance with regulatory standards.
With the help of the applied tool, I collected data obtained directly from smart meters in the network. I then analyzed this data and prepared an overview of the network status, which provided insight into the actual operating conditions. The analysis included monitoring voltage fluctuations, flicker phenomena, harmonic distortions, and other key parameters of power quality. Such an approach enables near real-time detection of deviations and irregularities, contributing to better network control and allowing faster response to identified anomalies. In addition to the technical results, the tool also provides a clear and comprehensible visualization of the data, which is essential for effective interpretation and management of the power system.
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