AI-Enhanced Hybrid Solar-Wind Systems for Sustainable Energy Solutions in Rural Communities

This research focuses on designing a hybrid solar-wind system to provide a reliable backup electricity supply. Access to reliable electricity remains a major challenge for many rural communities, where frequent power outages disrupt daily life and essential services. This research explores the development of a sustainable hybrid solar-wind energy system, enhanced with Artificial Intelligence (AI), to provide a dependable backup power solution for these underserved areas. By integrating solar panels as the primary energy source and wind turbines as a secondary source, the system maximizes energy generation based on local environmental conditions, ensuring a steady and sustainable power supply. A key feature of this system is its AI-driven monitoring and optimization capabilities, which enable real-time tracking of battery levels, energy production, and consumption. Using Arduino IDE to program the ESP8266 microcontroller, the system continuously adjusts energy flow to improve efficiency and resilience. Designed with user-friendliness in mind, the system empowers rural households to manage their energy resources effectively, reducing reliance on unstable grids while promoting renewable energy adoption. To ensure its practicality and effectiveness, the system undergoes thorough assessment through stakeholder feedback and expert evaluations. This research not only aims to enhance energy security for rural communities but also supports global sustainability efforts by promoting clean energy solutions. If successfully implemented, this AI-powered hybrid system could serve as a model for similar initiatives in other regions facing energy challenges, contributing to a future of more resilient and eco-friendly energy infrastructures.