Optimizing Grid-Connected Solar Energy Systems for Agricultural Applications in the Algerian Sahara (El Oued) Using AI-Based Maximum Consumption Point Tracking (MCPT)

Abstract

This paper proposes an innovative AI-based method called Maximum Consumption Point Tracking (MCPT) to optimize solar energy systems connected to the electrical grid for agricultural use in the Algerian Sahara (El Oued), Algeria. By analyzing real-world consumption patterns of local farmers (averaging 20,000 kWh/year), the model dynamically allocates photovoltaic energy using a hybrid deep learning framework. The study demonstrates enhanced energy efficiency, minimized waste, and better load prediction under variable solar irradiance [1], [2].