Abstract. Flood damage assessment is a critical aspect in any decision-making process on flood risk management. For this reason, reliable tools for flood damage estimation are required for all the categories of exposed elements. Despite infrastructures can suffer high economic losses in case of flood, compared to other exposed sectors, their flood damage modelling is still a challenging task. This is due, on the one hand, to the structural and dynamic complexity of infrastructure networks, and, on the other hand, to the lack of knowledge and data to investigate damage mechanisms and to calibrate and validate damage models. Grounding on the investigation of the state-of-the-art, this paper presents a conceptualization of flood damage to power grids and reviews the methodologies in the field for an in-depth understanding of the existing modelling approaches, challenges, and limitations. The conceptual model highlights: (i) the different kinds of damage (i.e., direct, indirect, and systemic) the network can suffer, (ii) the hazard, exposure, and vulnerability parameters on which they depend, (iii) the spatial and temporal scales required for their assessment, (iv) the interconnections among power grids and economic activities, and (v) the different recipients of economic losses. The development of the model stresses the importance of dividing the damage assessment into two steps: the estimation of damage in physical units and the consequent economic losses in monetary terms. The variety of damage mechanisms and cascading effects shaping the final damage figure arises, asking for an interdisciplinary and multi-scale evaluation approach. The ultimate objective of the conceptual model is to be an operative tool in support of more comprehensive and reliable flood damage assessments to power grids.

<p>Natural hazards are a leading driver of power outages worldwide. Although flooding has lower impact compared to other natural hazards, it may still have a significant impact on power grids functionality in terms of frequency, magnitude, and duration of power outage. Maintaining the security of power supply under emergency conditions triggered by natural hazards, such as floods, is a challenging task because of the inherent structural and dynamic complexity of the system. In such a context, this paper presents a new model for the estimation of direct, indirect, and systemic flood damage to power grids. The key objective of the model is to be an operational tool able to: (i) consider the magnitude, probability of occurrence, and spatiotemporal variability of flood hazard, (ii) identify the vulnerable components of power grids and evaluate their probability of failure in case of flood, (iii) analyze the cascading effects of individual or multiple failure states on the power transmission and distribution networks, (iv) and assess the impacts of power outages on the power-dependent economic activities and infrastructures. To achieve this goal, the model combines deterministic flood hazard scenarios, a spatially distributed power flow model, fragility curves of power grid components for different voltage levels, and a social model, describing the various users connected to the power grid. For quantitative illustration purposes, a synthetic model has been developed by referring to the IEEE 14 bus system benchmark, to which a spatial dimension has been allocated. Furthermore, to account for differentiated social impacts, the power flow model has been linked to a synthetic social model including several communities (hubs) with different social and economic characteristics.</p><p>The development of the synthetic model constitutes a preliminary step in understanding and quantifying the impacts that sustained power interruptions caused by floods can have on the customers of power grids. Next research efforts will be devoted, on the one hand, to the adoption of a probabilistic approach, by substituting deterministic hazard scenarios with spatial dependent, probabilistic ones; on the other hand, to the sensitivity analysis of the different modeling phases to identify the components of the model on which the final damage scenario depends mostly. The final aim is to provide a modeling and simulation tool for risk analysis, so as to enable stakeholders, authorities, and policy makers to formulate effective strategies to guarantee public security and ensure financial well-being.</p>