From Smart Grids to Smart Planets: The Role of AI in Global Energy Transformation

In response to climate change, growing energy demand, and renewable variability, this paper proposes a comprehensive AI-driven framework to transition from smart grids to globally coordinated, intelligent energy ecosystems - termed "Smart Planets."The framework integrates layered AI capabilities for perception, prediction, and control, addressing forecasting, optimization, demand response, and grid resilience challenges. Through real-world case studies, we demonstrate the effectiveness of this approach: solar forecasting with LSTM models achieved 92% accuracy; hybrid MPC-RL controllers halved frequency recovery time; DRL-based demand response reduced peak loads by 21% and energy costs by 17%; and AI-enabled microgrid reconfiguration maintained 93% power delivery to critical loads during disturbances. Performance evaluations across IEEE test systems revealed improvements in carbon intensity (36% reduction) and prediction accuracy (41% RMSE decrease), with edge-deployable inference. The paper concludes with a policy roadmap for scaling AI across infrastructure and governance, reinforcing AI's critical role in sustainable, resilient energy futures.