Beyond N-1: The Iberian blackout reveals interconnected risks in power systems

The 2025 Iberian blackout, a highly disruptive large-scale grid failure, underscores the increasing fragility of deeply interconnected and decarbonizing power systems. Traditional security paradigms, such as the N-1 criterion, were designed for isolated and predictable contingencies but are increasingly unable to anticipate or contain cascading failures. Using the Iberian blackout as a reference case, this review synthesizes global case studies to identify common structural drivers of modern power system vulnerability. This review argues that the reliability paradigm must shift from static, component-level robustness toward the management of dynamic failure propagation pathways, reduced system inertia, and cross-sector interdependencies. To operationalize this paradigm shift, this review proposes an integrated, multi-layered resilience framework. From an analytical perspective, this review details the transition toward probabilistic dynamic security assessment for characterizing failure propagation trajectories. At the engineering layer, controllable regional islanding, adaptive protection schemes, and artificial-intelligence-enhanced control execution enable rapid system stabilization within narrow operational time windows. To address computational complexity, this review proposes an integrated interdisciplinary methodological framework that leverages stochastic interaction graphs and digital twins to achieve multi-scale system observability, while employing deep reinforcement learning and coalitional game theory to coordinate fast-timescale physical control with slow-timescale market mechanisms. Finally, this review outlines a governance transition from prescriptive compliance toward continuous, state-aware risk management supported by unified cross-border resilience metrics. By reframing resilience as a dynamically managed systemic attribute, this review presents a structured agenda for safeguarding interconnected power grids against escalating cascading risks.