Resilience Planning and Optimization of Electric Power Systems Against Extreme Weather Events
Creators: name: Poudyal, Abodh
Publisher: name: Washington State University
Year: 2025
Subjects: Conditional value-at-risk
Extreme Weather Events
Long-term Planning
Resilience
Socioeconomic Vulnerability
Electric Power Systems

description: The socioeconomic losses from the recent unprecedented incidents in the electric power systems suggest the need for alternative planning strategies that account for the expected and extreme events that are less likely to occur. Such high impact low probability (HILP), or black swan, events are typically weather-related, have accounted for billions of dollars in economic losses, and left customers in the dark for several days. Furthermore, the proliferation of distributed energy resources (DERs) on the distribution grid indicates that system operators can also plan resilience from the customer’send, forming intentional microgrid islands when needed. However, existing planning strategies only minimize the expected operating cost and do not explicitly include the risk of extreme events. With the increasing frequency of black swan events in the current scenario, system operators should focus on the HILP events and find the optimal trade-off decision to maximize resilience with available resources. This dissertation aims to investigate the impact of extreme weather events, hurricanes, and floods on the power grid and propose planning solutions to enhance the grid’s resilience.
description: First, we highlight the need for resilience planning and assessment against extreme weather events. Here, we detail the resilience analysis process, characterize several attributes and performance-based resilience metrics, and identify measures to enhance the resilience of existing power distribution systems. Second, we develop a risk-averse two-stage stochastic optimization framework for resilience planning power distribution systems against extreme weather events. The resource planning strategy involves minimizing a risk metric, conditional value-at-risk (CVaR), while adhering to budget constraints for planning. Furthermore, the framework evaluates trade-offs among various factors, including resource availability, data availability, budget constraints, and risks. This facilitates the selection of specific planning decisions from a range of planning portfolios that can optimally restore critical loads during the realization of a HILP event. Third, we extend the risk-based planning framework for bulk power systems. The planning decisions include resilient dispatch of existing generators, line capacity upgrade, line hardening, DG siting, and sizing. Fourth, we decompose the planning problem into several sub-problems that can be solved in parallel. With the proposed approach, the solving time for a reasonably sized planning problem is reduced drastically without significantly compromising the planning solution’s quality. Finally, we propose a modeling framework to assess the spatiotemporal compounding effect of hurricanes and storm surges on electric power systems. The spatiotemporal probabilistic loss metric helps system operators identify the potential impact and vulnerable components as the storm approaches. Additionally, we characterize the impact of extreme weather events on socioeconomically vulnerable communities due to extended power outages induced by extreme weather events.