Optimizing Home Energy Consumption with Renewable Sources Using Marine Predators Algorithm: An AI-Based Approach

This study presents an innovative optimization methodology for managing home energy consumption in a smart grid environment, integrating renewable energy sources. The proposed system comprises household appliances and photovoltaic (PV) cells, designed without the inclusion of a battery storage unit. The primary goal is to minimize electricity bills by intelligently scheduling household appliances based on their categories - shiftable and non-shiftable loads - using the Marine Predators Algorithm (MPA), a cutting-edge artificial intelligence technique. By prioritizing energy usage during optimal PV generation periods, the methodology effectively balances user comfort and cost efficiency. Experimental results demonstrate a significant reduction in electricity costs by 20.7%, accompanied by a 17.2% decrease in grid dependency. These findings underscore the potential of AI-driven optimization techniques in promoting energy efficiency, enhancing the utilization of renewable energy, and contributing to the development of sustainable smart grid systems.