To Avoid a Repeat of Blackouts, Researcher Suggests Diversifying

Thousands of Californians suffered blackouts this fall, but research offers steps for utilities to prevent similar outages in the future.

Texas McCombs
Dec 11, 2019 · 4 min read

Based on the research of Stathis Tompaidis

In October and November, more than 800,000 Californians lost power, when Pacific Gas & Electric turned off transmission lines to prevent wildfires. In 2011, 54 Japanese nuclear plants were closed, after a tsunami caused three of them to melt down. These two events had something in common, says Stathis Tompaidis, professor of Information, Risk, and Operations Management at Texas McCombs. They were dependent outages: several units going down at the same time, from the same root cause, due to being interconnected.

Electric grids are frequently set up in ways that lead to interconnected shutdowns. The result, as Californians learned, is that grids are not as reliable as they think.

In a new paper, Tompaidis and his co-authors — Vishwakant Malladi from the Indian School of Business and Rafael Mendoza-Arriaga from discretionary fund manager Man GLG — measured the odds of electric grids suffering simultaneous outages. Through the use of more diverse fuel sources and incentives, massive blackouts — like the ones in California — could be prevented.

Shared transmission lines are one source of dependent outages. Are there other kinds of dangerous linkages?

Think about Texas and the Northeast where pipelines are used to deliver natural gas to power plants. Occasionally those pipelines freeze. When they can’t get natural gas, they don’t run. Or take hydroelectric power on the West Coast. It’s associated with the amount of rain that falls. Those plants empty at similar rates, and they end up going out together.

How do you model the chances that several plants will shut down jointly?

Within each group, we captured historical outages. How often do five of them go down at the same time? How often do six go down? In ERCOT [the grid that covers most of Texas], between 2008 and 2012, there were 14 outages of seven or more plants. Once we matched the model to those data, we could predict what rates of simultaneous outages we should see.

So what’s the solution?

You didn’t have data on wind or solar. Are they vulnerable, too?

To get a blackout-resistant power mix, how can we encourage operators to build other types of power plants, which aren’t prone to joint shutdowns?

Or, if the form of power they’re selling is not as reliable as they’d like, the seller might need to promise reserves in a different technology. To get a contract for your solar plant, they might have to couple it with a certain amount of battery storage or natural gas backup.

You say your model doesn’t just apply to electric plants. How else could it be used?

It doesn’t just apply to physical networks. Our methodology was originally developed for modeling joint defaults on corporate debt. In the 2008 financial crisis, multiple firms faced problems coming from the same sources. So, in a particular region, you’d have one default, but it turned into five defaults. A model like this helps to capture that kind of dependence.

Modeling Dependent Outages of Electric Power Plants” published online Dec. 11 in Operations Research.

Story by Steve Brooks

Big Ideas

Research and insights from Texas McCombs

Texas McCombs

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News, business research, and ideas from the McCombs School of Business at The University of Texas at Austin. Learn more at www.mccombs.utexas.edu

Big Ideas

Big Ideas

Research and insights from Texas McCombs

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