A systematic review on the current scenarios and future frontiers for securing smart grid systems

Abstract

The rapid development of smart grid infrastructure has transformed power generation and transmission, supporting bidirectional energy flow, decentralized energy systems and real-time monitoring. These developments encounter challenges in securing smart grids against evolving cyberattacks. In this paper, we present a review on securing smart grid systems, threat landscape and real-time cyberattack cases and advanced defense techniques. The review is classified on the basis of threat taxonomy and the integration of emerging security mechanisms such as AI-based intrusion detection systems, blockchain-based frameworks and quantum cryptographic techniques. Data driven models such as machine learning, deep learning, reinforcement learning and federated learning algorithms enable adaptive threat detection in handling evolving threat configurations. These technologies form a layered and synergistic defense framework for resilient smart grid operations. The analysis indicates that AI models can achieve an accuracy of over 99% in FDIA detection, but their performance decreases by more than 30% under adversarial attacks, and robustness enhancement mechanisms are urgently needed. This work presents the strategic roadmap for India’s power generation and evolution by outlining key technological modifications to achieve sustainable, reliable and low-carbon footprints. Open research challenges and future directions are identified, highlighting the need for privacy preserving architectures and lightweight quantum-resilient security mechanisms to ensure the long-term resilience of smart grid infrastructures.