Smart Metering Enabled by the Internet of Things for Monitoring Residential Energy Consumption and Power Quality

This work presents the development of an Internet of Things based smart metering system designed for real-time detection and classification of electrical disturbances, with a focus on Power Quality monitoring and energy consumption analysis. The system is built around an ESP32 microcontroller, integrated with ZMPT101B voltage and SCT013 current sensors, to capture high-resolution electrical signals. To detect and classify anomalies such as voltage sags, swells, harmonic distortions, spikes, notches, and transients, the system applies advanced signal processing techniques, including root mean square computation and Fast Fourier Transform. The detection methodology complies with the Brazilian PRODIST standard, which defines reference thresholds for Power Quality parameters using the per-unit system. A physical prototype was constructed using 3D printing, and system behavior was validated through simulations conducted in Proteus. The prototype demonstrated reliable energy monitoring with data acquisition at ten-second intervals and achieved classification accuracy ranging from 87.1% to 94.4% across different types of electrical disturbances. By combining Power Quality analysis with consumption tracking, the proposed Internet of Things enabled smart meter provides a cost-effective and scalable solution for continuous monitoring. Its implementation supports improved efficiency and reliability in electrical systems and is well-suited for residential applications, enabling enhanced energy management and predictive maintenance through detailed consumption insights and disturbance detection.