With the accelerating pace of global climate change and urbanization, pluvial flooding has become a pervasive urban hazard, posing severe threats to critical lifeline infrastructure such as power distribution systems. Power distribution facilities are generally designed with limited flood protection standards, and intense rainfall may trigger urban flooding that inundates power distribution substations, leading to widespread power outages. Furthermore, post-disaster repair and replacement of flooded distribution assets impose substantial economic burdens on utilities. While distribution companies bear societal responsibility for maintaining power supply under extreme events, they must also operate as commercial entities with financial considerations. Consequently, managing pluvial flood risk in an effective and economically efficient manner has become an urgent challenge. This paper proposes a comprehensive disaster risk management (DRM) framework for power distribution systems, consisting of four risk analysis modules: hazard, exposure, vulnerability, and capacity. The framework integrates four types of risk treatment measures (avoidance, reduction, transfer, and retention) and explicitly accounts for both societal and business objectives of DRM. By leveraging the occurrence exceedance probability and the compound Poisson distribution, the pluvial flood risk management problem is formulated as a bi-objective mixed integer linear programming model that simultaneously minimizes the expected annual aggregate customer interruptions and the annualized total cost of risk. The proposed model is applied to a modified 33-node distribution system and a real-world distribution system in central China. Numerical results demonstrate that the model effectively exploits the complementary strengths of risk control and risk finance measures, achieving a trade-off optimization in pluvial flood risk management for urban distribution systems.
Sun et al. (Mon,) studied this question.