Power system security with climate change effects and smart assets: A review on modeling paradigm shift to smart grids

Abstract

Climate change, increasing renewable-energy penetration, and the growing dependence of power networks on digital and smart assets are changing the conditions under which power system security must be assessed and maintained. This paper presents a critical review of deterministic, probabilistic, risk-based, and intelligence-assisted approaches to power system security, with particular attention to climate-related uncertainty and the transition toward smart grids. The effects of rising temperatures, extreme weather, and changing resource availability on generation, transmission, distribution, and electricity demand are examined. The review also evaluates the contributions of smart asset management, smart generators, dynamically rated transmission lines, and smart transformers to security-constrained operation. The reviewed literature shows that deterministic methods provide physically interpretable security margins but do not directly quantify event likelihood, whereas probabilistic and risk-based methods represent uncertainty more explicitly but depend on suitable probability models, data quality, and computational resources. Intelligence-assisted methods can improve prediction and decision speed, although their reliability requires representative data, physical consistency, and validation under rare and previously unseen conditions. A major research gap is the limited integration of climate-dependent asset deterioration, component failure probability, and system-level security assessment. Future security frameworks should therefore combine physics-based network models, probabilistic uncertainty representation, real-time measurements, asset-health information, and intelligent decision support. Such integration is necessary for developing adaptive, climate-resilient, and secure power systems while supporting the transition toward net-zero energy systems.