Whereas whitewater churns in response to localized conditions within the stream, the duo showed that turbulence in superheated plasma in fusion reactors has more to do with the total amount of energy in the system. After the total heat grew beyond a critical point, the probability of collapse grew exponentially. In the parlance of systems theory, it was a classic complex system with a “self-organizing point of criticality” — a concept elaborated in the 1980s by theoretical physicist Per Bak. It describes how growing sand piles collapse in avalanches when the strain on the grains becomes too great. After a certain amount of sand is in the pile, the likelihood of collapse becomes imminent.
By the mid-’90s, scientists had identified similar patterns of growth and collapse in diverse natural systems, from forest fires to earthquakes. Newman and Carreras discovered that the same theory explains why plasmas have lasted no longer than a few seconds in fusion reactor tests to date. The work earned Newman a Presidential Early Career Award — the highest federal honor bestowed upon young scientists.
In 1995, Newman saw a news report on a blackout and wondered if this “point of criticality” theory might also apply to major power outages — and whether it could help prevent them. Carreras, eager for a new problem to solve, suggested they bring in a grid expert. They found one in Dobson, who had earned a reputation as an innovative power systems engineer by using advanced math to unmask unsuspected relationships between voltage drops and blackouts. The trio first looked at the historical record of big blackouts to see if they could detect criticality’s distinctive imprint. They mined a database of blackouts in North America and plotted them by size. If big blackouts were just a random, unlucky confluence of many small failures, as grid planners and operators believed, a major grid collapse would occur only once in a thousand years or so, showing up as the slim tail on a bell curve. Instead, the plot bulged out to the right, showing that blackouts were striking hundreds of times more often.
For the trio, it was a strong suggestion that blackouts were, indeed, the power grid equivalent of a sand pile’s avalanche. “It’s as if there is a physical law there,” says Carreras.
In January 2000, Carreras, Dobson and Newman reported the overabundance of big blackouts at the Hawaii International Conference on System Sciences (HICSS), one of the biggest and longest-running annual gatherings for systems scientists. They speculated that blackout risk might spike when power flows on grids exceeded some threshold, the familiar critical point in systems theory. But what was pushing grids to the point of criticality? They knew power consumption was rising, while financial pressures limited the construction of new lines. Could these influences combine to put extra strain on the grid’s transmission lines, enough to reach a tipping point?
To test this theory, the trio realized they’d have to rethink power grid simulation. Existing simulators could not handle direct modeling of big blackouts because of the complexity of power grids. But what if they could create a simpler simulator that could be set in motion and observed as power levels increased over time, like Bak’s growing sand piles?