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Nateghi named Co-PI for NSF project

Nateghi named Co-PI for NSF project

Photo of Roshanak Nateghi
Roshanak Nateghi will be a Co-PI
for the project.
Dr. Roshanak Nateghi was named as a Co-PI on a recently-funded National Science Foundation (NSF) project.

The three-year project is titled "Towards a Resilient Grid: An Investment Prioritization Decision Framework that Integrates the Growing Risks of Severe Weather- Induced Outages".

IE PhD student Ben Rachunok will work on the project with Nateghi. Makarand Hastak, head of construction engineering and management and professor of civil engineering, is the PI, and Wallace Tyner, James & Lois Ackerman professor of agricultural economics, is the co-PI.


Severe weather induced power outages cost billions of dollars in economic losses each year. It is estimated that these outages have cost the U.S. economy an inflation-adjusted annual average of $20 billion to $55 billion during the period of 2003-2012. However, presently the federal and state-level risk and reliability metrics and standards do not internalize the impact of extreme events on electric power service, and have no effective mechanisms for assessing and regulating the levels of preparedness and response of the utilities impacted by extreme events. In the light of addressing this gap, this research intends to develop a risk-based decision support system that will help the state utility commissions to systematically account for the severe weather-induced power outage risks. This would lead to a better informed regulatory decision-making process aimed to minimize such risks and enhance the overall security of the grid. 

The transformative risk-based decision support system will integrate and advance the scientific area through (1) advanced algorithm-based probabilistic risk analysis models for estimating risk of major power outages under severe weather events; (2) advanced economic models to estimate the compounding economic losses due to failure of interdependent infrastructure due to such power outages; and (3) optimization techniques to determine the optimal strategies considering the deep uncertainties of the future. The core framework of this research is not only applicable to scenario-based risk assessment and optimal strategy development to enhance regional electricity sector resilience, but also applicable to other utility sectors such as, natural gas, renewable energy sector, water systems, etc.