Fault-Tolerant Embedded Control Strategies for Intelligent Renewable Energy Integration

Abstract

ABSTRACT: The integration of renewable energy into traditional power grids presents significant operational challenges due to the intermittent and unpredictable nature of solar and wind resources. This paper introduces a fault-tolerant embedded control strategy that enhances the resilience and reliability of systems with high renewable penetration. The proposed model employs redundant sensing, adaptive control loops, and a decision-making engine powered by deep learning algorithms. Unlike conventional approaches that rely on centralized monitoring systems, this approach embeds intelligence directly into local controllers, enabling fast and autonomous mitigation of faults such as voltage dips, converter failures, and communication disruptions. Comprehensive simulations under various fault scenarios demonstrate that the system maintains stable operation with minimal interruption and outperforms baseline controllers by reducing fault-propagation effects by over 50%. The research emphasizes the need for local autonomy, especially in geographically distributed renewable installations.

KEYWORDS: Fault tolerance, Renewable energy, Embedded controllers, Adaptive control, Deep learning