commercial and industrial customers, with costs ranging from $466 to $742 for a one-hour outage, with the lowest costs found on weekends and during the winter season and the highest costs found in summer and on weekends. The same patterns are found for medium and large commercial and industrial customers, though at higher costs: averaging between $4,190 (weekends) to over $16,000 (weekday outages and summer outages) (Sullivan et al. 2018). The tool is not designed for resiliency planning, especially for events lasting more than twenty-four hours or outside the United States. Nonetheless it could provide a baseline assessment method for resiliency investment and planning and is the focus of recent work comparing generator costs and other aspects of resiliency in post-event evaluations.

Much of the recent work related to power system resiliency has been focused on cyber-security<sup>3</sup> . While a valuable body of research and an important consideration in power system design, this falls outside the scope of the present study and should be a considered in resilience planning, particularly for smart grid systems. Here we focus on understanding component and system vulnerabilities to a wide range of natural disasters found through case study assessments.

# **2.0 - METHODOLOGY**

We consider the power system impacts of earthquakes, wild fires, hurricanes, droughts, floods, heat waves, as well as snow, ice, wind and thunder storms. The assets investigated include transmission and distribution infrastructure (e.g. substations, wires, and poles) as well as fuel-specific generation facilities. The data for the events studied falls into three general categories: hazard event case studies with multiple data sources covering many assets within a power system; single-facility operation disruptions from weather or water-related issues in the United States (McCall, Macknick, and Macknick 2016) or globally (Karagiannis et al. 2017a); major outage events in the United States between 2000 and 2016 focused on the cause of the disruption and customers affected (Mukherjee, Nateghi, and Hastak 2018c). The latter data were limited to customers affected, and the causal event. Where possible, cost estimates to repair damage back to operational capacity was recorded as were recommendations to improve performance. The types of events for which case study level data were available for different hazard events are summarized in Table 1.

This paper does not specifically address the impacts of climate change but instead focuses on empirical assessment of past hazard events and their impacts on the electrical power grid. Many studies cite that the impacts of a changing climate may increase the severity or intensity of natural hazard events and should be considered in the planning of new infrastructure (e.g. Meyer et al. 2013). Some examples of ways to incorporate climate change considerations in planning can be found, including a 2016 study of vulnerabilities of power system infrastructure to flooding (Chattopadhyay et al. 2016) and others focused on different types of critical infrastructure (Schweikert, Espinet, and Chinowsky 2018). This is an important consideration for future work and discussed in the recommendations at the end of this work.

**Table 1: Case Study Summary** - Over 50 events and more than 700 outages were investigated in this analysis. The 13 events detailed in this table represent analyses that covered multiple infrastructure assets and sources to provide a picture of the impacts of a specific natural hazard event on the electric power <u>system in the affected region.</u>

||**Number**|||||**Damaged Assets**|
|---|---|---|---|---|---|---|
|**Hazard**|**of Case**|**Event Name**|**Date**|**Location**|**Severity**|**(for which data**|
||**Studies**|||||**was available)**|

3 For more information on this important consideration, several resources are available, including The United States’ Department of Energy Office of Cybersecurity, Energy Security, and Emergency Response (CESER)(Department of Energy n.d.).

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