Design and Simulation of an IoT-Based Smart Energy Monitoring and Power Management System
This record contains the manuscript and the reproducible simulation files for the design and simulation of an IoT-based smart energy monitoring and power-management system for residential and small commercial use. The proposed architecture combines voltage and current sensing, an ESP32-class microcontroller, Wi-Fi communication, MQTT data transmission and a remote dashboard. It calculates RMS voltage, RMS current, power factor, active power and cumulative energy, and raises alerts when configurable power or daily-energy thresholds are exceeded. A one-minute-resolution Python simulation was developed using an assumed six-load household profile (4.805 kWh/day; 144.15 kWh over 30 days), together with a 30-day stochastic run and a Monte-Carlo study of assumed sensor and ADC errors. All numerical results are simulation outputs based on stated assumptions; they are not laboratory measurements from a physical prototype. The archive includes: simulate.py (simulation script, fixed random seed 42), CSV files with the results, and the figures used in the manuscript.
Authors
- Shahid Imran
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-09-29
- DOI
- https://doi.org/10.5281/zenodo.23030942
- Primary Topic
- Smart Grid Energy Management
- Type
- article
- Field-Weighted Citation Impact
- 0.00