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All Journal Andalas Journal of Electrical and Electronic Engineering Technology
Nicholas Kirui
Dedan Kimathi University of Technology, Kenya
Control & Systems Engineering Education Electrical & Electronics Engineering Energy Engineering

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Fabrication of Smart Meter for Accurate Use in Home and Industry Nicholas Kirui; Charles Kagiri; Titus Mulembo
Andalas Journal of Electrical and Electronic Engineering Technology Vol. 3 No. 2 (2023): November 2023
Publisher : Electrical Engineering Dept, Engineering Faculty, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/ajeeet.v3i2.63

Abstract

This study addresses the challenges posed by conventional energy meters, which rely on manual readings, leading to human errors and inefficiencies. In response to this, a battery-powered smart meter was developed utilizing an STM32 microcontroller, ADE7758 and STPM32 metering integrated circuits (ICs), SIM and ESP32 communication modules, along with a MYSQL database. Real-time energy data from both single and three-phase appliances were collected, and their energy consumption, errors, Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE) were quantified. The model demonstrated an acceptable accuracy level, with an estimated MAE of approximately 2.912 units and an estimated RMSE of around 4.048 units, particularly in predicting motor power consumption. Additionally, ARIMA forecasting was applied to a three-phase asynchronous motor, revealing an average active motor power of 250.95 watts, indicating precise results over time.
Fabrication of Smart Meter for Accurate Use in Home and Industry Nicholas Kirui; Charles Kagiri; Titus Mulembo
Andalas Journal of Electrical and Electronic Engineering Technology Vol. 3 No. 2 (2023): November 2023
Publisher : Electrical Engineering Dept, Engineering Faculty, Universitas Andalas

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25077/ajeeet.v3i2.63

Abstract

This study addresses the challenges posed by conventional energy meters, which rely on manual readings, leading to human errors and inefficiencies. In response to this, a battery-powered smart meter was developed utilizing an STM32 microcontroller, ADE7758 and STPM32 metering integrated circuits (ICs), SIM and ESP32 communication modules, along with a MYSQL database. Real-time energy data from both single and three-phase appliances were collected, and their energy consumption, errors, Mean Absolute Error (MAE), and Root Mean Squared Error (RMSE) were quantified. The model demonstrated an acceptable accuracy level, with an estimated MAE of approximately 2.912 units and an estimated RMSE of around 4.048 units, particularly in predicting motor power consumption. Additionally, ARIMA forecasting was applied to a three-phase asynchronous motor, revealing an average active motor power of 250.95 watts, indicating precise results over time.
Co-Authors Charles Kagiri Titus Mulembo