Artificial Intelligence for Sustainable Power Systems: A Path Toward Green and Resilient Energy Infrastructure

Artificial Intelligence (AI) is revolutionizing the global energy landscape by enabling thedesign, operation, and optimization of sustainable power systems. This paper exploreshow AI enhances sustainability across power generation, transmission, and consumption.It presents AI-driven approaches for energy forecasting, smart grid operation, demand-side management, fault prediction, and renewable integration. Through real-world casestudies and empirical analysis, the paper demonstrates AI’s potential to minimize carbonemissions, reduce costs, and improve efficiency. A simulation of an AI-based energymanagement system for a solar-diesel microgrid using LSTM and Deep Q-Networksyielded a 12.4% improvement in energy efficiency, a 19.8% reduction in grid dependency,and a 15.6% decrease in CO₂ emissions compared to baseline rule-based systems.Additionally, predictive models reduced energy forecasting errors by 22.1% (RMSE).These results highlight the transformative potential of AI in building low-carbon, resilient,and intelligent power infrastructures. The paper also identifies challenges and outlinesfuture directions for AI in sustainable energy systems, emphasizing the need fortransparent, ethical, and inclusive AI models.