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A new methodological approach to grid resilience created by researchers at The University of Texas at Austin offers policy makers and grid operators a new way to achieve a more equitable power grid as they plan for natural disasters. Researchers from UT’s Cockrell School of Engineering have taken a multi-faceted approach to address a pressing concern: prioritizing resources to enhance power grid resiliency while considering social equity.
Weather events such as hurricanes and floods can disproportionately affect disadvantaged communities. This new approach uses flood simulation and novel equity metrics to mitigate the negative impacts on vulnerable populations.
In the face of a natural disaster, grid operators must make strategic decisions about two things: the physical hardening of vulnerable power substations and managing power demands by intentionally creating outages in specific parts of the grid — a practice known as load shedding.
The new model balances these two management strategies — hardening and load shedding — while simultaneously incorporating equity metrics aimed at reducing the well-being loss of socially vulnerable communities. The model was recently published in Socio-Economic Planning Sciences.
The study’s authors explain that communities are affected differently by the same disaster. “Natural disasters are not equal opportunity menaces,” said John Hasenbein, a professor of Operations Research and Industrial Engineering (ORIE) in the Walker Department of Mechanical Engineering and one of the study’s authors.
Those with more financial resources can more easily relocate, find alternative modes of transportation, and pay for alternative heating and cooling solutions. Vulnerable communities, with limited resources, face significant challenges that make evacuation and recovery difficult. As a result, they experience significant well-being loss. According to the researchers, major natural disasters can result in well-being loss that lasts up to 10 years.
In addition to Hasenbein, the research team included another ORIE professor, Erhan Kutanoglu, and Ph.D. candidate, Gizem Toplu Tutay; all three researchers are from the ORIE program at the Cockrell School of Engineering.
The researchers introduced a 2-stage stochastic optimization model to address the variability associated with flood events. To refine and test their decision-making model, the research team generated 25 flood scenarios and employed a large-scale synthetic grid of Texas.
Seeking precision in equity metrics, the researchers crafted their own calculations instead of simply incorporating the Justice40 standard, which calls for 40% of the benefits of total Federal investments to be directed toward disadvantaged communities. “The justice model makes sense in a crude way of trying to make things equitable, but…we think our model is more nuanced and can result in a decrease in the size of population affected by well-being loss and the expected duration of well-being loss,” said Hasenbein.
Kutanoglu said their study contributes a valuable methodological approach to integrating social equity into decision-making for power grid resilience planning. Future investigations may include similar modeling for other natural disasters such as winter storms and heat waves.
The study was funded by the IC² Institute at The University of Texas at Austin.