Concentration of CO2 in the Atmosphere

March 7th DEC Lunch: Assessing and mitigating the risk of cascading blackouts

The next Dartmouth Energy Collaborative Pizza Lunch will be held on March 7th

Assessing and mitigating the risk of cascading blackouts
Speaker: Dr. Margaret J. Eppstein
Thursday, March 7th
Fahey First Floor Commons, Dartmouth
Large cascading failures in electrical grids are rare but catastrophic, sometimes affecting millions of people and incurring substantial social and economic costs. Quantifying the risk of cascading failure is thus of critical importance for grid planning and operation, but is extremely challenging due to the rarity of blackout-causing events amongst the vast search space of possible combinations of component outages. In this talk, we present new approaches for estimating this risk in a computationally tractable way and show that it is orders of magnitude faster than current approaches.  We demonstrate the method on two realistic test cases; a model of the Polish grid with 2896 transmission lines under varying load conditions and a larger model based on the geography of the Western US with 12,706 transmission lines. Examining the sensitivity of overall blackout risk to individual transmission line failures facilitates the identification of low-cost strategies for reducing risk.  For example, we show that the risk of catastrophically large blackouts in the Polish grid model can be reduced by 83% for only a modest 1.9% increase in operational costs. Blackout risk estimation is often simplified by assuming that initiating outages are independent events, so that only pairwise initiating outages need be considered. In reality, common exogenous causes (such as severe storms) often induce spatial correlation in transmission line outages. We develop methods to incorporate such spatial correlation and show that the contribution to risk of 3-component initiating outages, relative to 2-component initiating outages, increases as a function of spatial correlation. We are currently exploring tractable methods for estimating the risk due to even higher-order contingencies.
About Margaret:

Margaret (Maggie) J. Eppstein received the B.S. degree in zoology from Michigan State University in 1978 and the M.S. degree in computer science and the Ph.D. degree in civil & environmental engineering from the University of Vermont (UVM), Burlington, VT, in 1983 and 1997, respectively. She is currently Research Professor and Professor of Computer Science Emerita at UVM, where she has been on the faculty since 1983. She was founding director of the Vermont Complex Systems Center (2006-2010) and Chair of the UVM Department of Computer Science (2012-2018). Her research interests comprise interesting computational challenges in modeling and analysis of complex systems in a variety of application domains.
Hosted by the Dartmouth Energy Collaborative
*The Dartmouth Energy Collaborative is a partnership of the Arthur L. Irving Institute for Energy and Society, the Revers Center for Energy at Tuck, the Dartmouth Sustainability Office and the Thayer School of Engineering

About Margaret:

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