Earthquakes cause outages of power transmission system components due to direct physical damage and also through the initiation of cascading processes. This article explores what are the optimal capacity investments to increase the resilience of electric power transmission systems to earthquakes and how those investments change with respect to two issues: (1) the impact of including cascades in the investment optimization model and (2) the impact of focusing more heavily on the early stages of the outages after the earthquake in contrast to more evenly focusing on outages across the entire restoration process. A cascading outage model driven by the statistics of sample utility data is developed and used to locate the cascading lines. We compare the investment plans with and without the modeling of the cascades and with different levels of importance attached to outages that occur during different periods of the restoration process. Using a case study of the Eastern Interconnect transmission grid, where the seismic hazard stems mostly from the New Madrid Seismic Zone, we find that the cascades have little effect on the optimal set of capacity enhancement investments. However, the cascades do have a significant impact on the early stages of the restoration process. Also, the cascading lines can be far away from the initial physically damaged lines. More broadly, the early stages of the earthquake restoration process is affected by the extent of the cascading outages and is critical for search and rescue as well as restoring vital services. Also, we show that an investment plan focusing more heavily on outages in the first 3 days after the earthquake yields fewer outages in the first month, but more outages later in comparison with an investment plan focusing uniformly on outages over an entire 6-month restoration process.
Leader–follower equilibria to examine investment decisions in grid resilience‐enhancing measures
Large‐area, long‐duration power outages are increasingly common in the United States, and cost the economy billions of dollars each year. Building a strategy to enhance grid resilience requires an understanding of the optimal mix of preventive and corrective actions, the inefficiencies that arise when self‐interested parties make resilience investment decisions, and the conditions under which regulators may facilitate the realization of efficient market outcomes. We develop a bi‐level model to examine the mix of preventive and corrective measures that enhances grid resilience to a severe storm. The model represents a Stackelberg game between a regulated utility (leader) that may harden distribution feeders before a long‐duration outage and/or deploy restoration crews after the disruption, and utility customers with varying preferences for reliable power (followers) who may invest in backup generators. We show that the regulator's denial of cost recovery for the utility's preventive expenditures, coupled with the misalignment between private objectives and social welfare maximization, yields significant inefficiencies in the resilience investment mix. Allowing cost recovery for a higher share of the utility's capital expenditures in preventive measures, extending the time horizon associated with damage cost recovery, and adopting a storm restoration compensation mechanism shift the realized market outcome toward the efficient solution. If about one‐fifth of preventive resilience investments is approved by regulators, requiring utilities to pay a compensation of $365 per customer for a 3‐day outage (about seven times the level of compensation currently offered by US utilities) provides significant incentives toward more efficient preventive resilience investments.
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- Award ID(s):
- 1832290
- PAR ID:
- 10483322
- Publisher / Repository:
- Risk Analysis
- Date Published:
- Journal Name:
- Risk Analysis
- Volume:
- 43
- Issue:
- 2
- ISSN:
- 0272-4332
- Page Range / eLocation ID:
- 280 to 307
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1111/risa.13921
