IMPLEMENTATION OF AN AI-ASSISTED HOME ENERGY MANAGEMENT SYSTEM FOR SOLAR RESIDENTIAL APPLICATIONS

The increasing demand for electricity and the growing adoption of renewable energy systems require
intelligent energy management solutions. This paper presents the design and implementation of a
Home Energy Management System (HEMS) that monitors solar battery parameters and dynamically
manages household loads based on available energy. The system is built using an ESP32
microcontroller, current and voltage sensors, relay-based load control, and cloud-based data
monitoring. Energy parameters such as battery voltage, current, and power consumption are measured
and transmitted to the ThingSpeak IoT cloud platform for analysis. The system prioritizes loads
depending on battery voltage levels to ensure critical loads remain powered during low energy
conditions. Additionally, the collected data can be used for AI-based analysis to predict consumption
patterns and optimize energy usage. This prototype demonstrates the integration of renewable energy
systems, IoT monitoring, and intelligent energy management for future smart homes.

Github repository link :
https://github.com/madhava-a11y/-IMPLEMENTATION-OF-AN-AI-ASSISTED-HOME-ENERGY-MANAGEMENT-SYSTEM-FOR-SOLAR-RESIDENTIAL-APPLICATIONS-

Видео IMPLEMENTATION OF AN AI-ASSISTED HOME ENERGY MANAGEMENT SYSTEM FOR SOLAR RESIDENTIAL APPLICATIONS канала Madhav Shilpi