The integration of Artificial Intelligence (AI) and the Internet of Things (IoT) into power electronics has transformed renewable energy management and smart grid operations. This article explores how AI-driven predictive analytics and IoT-enabled sensing networks can enhance efficiency, stability, and sustainability in modern energy systems. AI techniques such as deep reinforcement learning (DRL), fuzzy logic, and neural networks are employed to optimize energy conversion, fault detection, and real-time control. Meanwhile, IoT provides a distributed communication infrastructure that enables edge-based monitoring, demandside management, and grid resilience. The convergence of AI and IoT-driven power electronics offers a pathway toward self-healing, adaptive, and low-carbon energy ecosystems.
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