Digital twins for hazard-resilient power grids: A systematic review and roadmap

The increasing exposure of modern power systems to climate-induced hazards, cyber threats, and operational uncertainty has intensified the energy trilemma of sustainability, security, and affordability. Rapid decentralisation and digitalisation driven by renewable integration, microgrids, and active demand participation have rendered conventional planning and operational approaches inadequate for ensuring resilient and sustainable electricity networks. This challenge requires adaptive, data-driven frameworks that provide real-time situational awareness, predictive intelligence, and coordinated control under uncertainty. This paper presents a PRISMA-guided systematic review of Digital Twin (DT) technologies, with a particular focus on Climate-Aware Digital Twins (CADTs) and AI-driven analytics for enhancing sustainability and resilience in modern power systems. The review synthesises recent advances in predictive forecasting, decentralised energy management, grid resilience enhancement, and hazard-informed system restoration. Key application domains include microgrid resilience, demand response optimisation, renewable-dominated networks, and satellite-assisted recovery following extreme events. Enabling technologies such as machine learning, edge-cloud computing, blockchain, and the Internet of Things (IoT) are examined as foundational components supporting real-time synchronisation, secure data exchange, and autonomous control. Across the reviewed literature, four persistent challenges are identified: data latency and availability constraints, high computational and modelling complexity, limited interoperability with legacy infrastructure, and unresolved cybersecurity risks. Building on these findings, the paper proposes a strategic roadmap for integrating DTs with climate-aware forecasting and adaptive control architectures, highlighting pathways towards intelligent, self-healing, and hazard-resilient power systems.