Extreme Weather Event Modeling

Provider(s):
Washington State University

Description:
Extreme weather events pose serious concerns for the nation's critical infrastructure systems. Severe windstorms remain the primary cause of extensive power grid damages resulting in widespread customer outages and expensive recovery. Hurricane Ida (Sept. 2021) is estimated to have cost $16 to 24 billion in flooding damage in the Northeastern US. About 1.2 million customers were left without power, and it took almost 15 days to restore the electric power entirely. An accurate climate-grid impact model is needed to develop effective long-term planning solutions for grid resilience against climate change. The lack of understanding of the impacts of extreme weather events on critical infrastructures such as power grid components poses challenges to developing effective climate-impact models. Although long-range climate prediction models have improved in recent years, they have not been adequately utilized to evaluate climate impacts on the power grid. Our goal is to develop a simulation-based approach to model the impacts of hurricanes on the power grid infrastructure and system outages. The proposed simulator uses a numerical weather prediction model to model historical and hypothetical hurricanes, storm surge models to estimate the flooding levels due to the hurricane, component-level climate impact models and power grid simulators to estimate system damages as a function of climate and geological terrain properties. The outcome of this task is a probabilistic loss function capturing the probabilities of system outages and the outage risks due to extreme weather events. Student interns will expand the existing climate-grid impact model to include flooding damage due to hurricanes. They will also support graduate students in developing methods to quantify the resulting system outages due to compounded effects of flooding and wind damages. 
Qualifications Required:
Basic programming skills (python/matlab),

Research Component:

The project requires machine learning models to analyse the weather datasets and to forecast the rare extreme weather events. Moreover, analytical models require an application of probability theory and stochastic modeling.
​Location:
Remote
Hours per week:
20+
Duration of internship:
10 weeks
Stipend:
Yes
Timeline:
To be discussed with the provider during interview process

Eligibility:

High school students currently in grades 9-12 in the USA can apply.

Sorry, we cannot support international students. Please read Read Me sections in the website for more details