Enhancing Grid Resilience Through Real-Time Self-Healing: Integrating Python-PowerFactory-IoT with ESP32

The modern power grid demands innovative solutions to improve its resilience and reliability. This research aims to develop a novel approach to real-time self-healing in power distribution networks by integrating Internet of Things (IoT) technology with advanced simulation tools, specifically DIgSILENT PowerFactory. The proposed system utilizes ESP32 microcontrollers equipped with sensors to measure electrical parameters such as voltage and current, collecting real-time data from the network. This data is transmitted via Wi-Fi to a MySQL database on a central server. Python (Jupiter Notebook) scripts facilitate the connection between the database and DlgSILENT PowerFactory, enabling real-time load flow simulations within the network. The results of this system show significant improvements in fault response times and overall grid resilience. Our implementation demonstrates that this integrated approach can effectively reduce downtime and enhance the stability of power distribution networks.