Towards Sustainable DC Microgrids: A Comprehensive Review of IoT-Driven Frameworks

¹ Department of EEE, CVR College of Engineering, Ibrahimpatnam, Hyderabad, India, 501510
² Professor, Department of EEE, JNTUH University College of Engineering Science & Technology, Hyderabad, Hyderabad, India

^* Corresponding author: morampudirajita@gmail.com

Abstract

A comprehensive review of cyber-physical architectures for DC microgrids is presented, focusing on the integration of deep learning and LoRa technology for secure, efficient, and scalable communication networks. DC microgrids, with their decentralized energy resources and low inertia, face challenges such as real-time monitoring, fault detection, and vulnerability to cyber-attacks. The review highlights the potential of LoRa technology for long-range, low-power communication, ensuring seamless data exchange between distributed components, including renewable energy sources, storage systems, and control units. Deep learning models are explored for their application in predictive maintenance, fault detection, and cyber-attack mitigation, such as false data injection attacks. By integrating these technologies, the review underscores enhanced operational efficiency, robust cybersecurity, and real-time control in DC microgrids. The scalability of such architectures is evaluated, showing suitability for diverse microgrid scales, from residential setups to utility-level implementations. Findings from this review emphasize the synergy between IoT-driven communication networks and machine learning models in addressing energy management and cybersecurity challenges. The paper calls for standardized frameworks and collaborative efforts to further develop and deploy secure, resilient DC microgrid architectures, laying the groundwork for sustainable and efficient energy systems of the future.