Excerpt

On August 14, 2003, fifty million people across the American Northeast lost electrical power. Around 70,000 megawatts went AWOL, which for reference is on the order of one hundred coal plants spontaneously disappearing from energy production.

The initial cause was thought to be a fault in a 345-kilovolt line in northern Ohio. In less than an hour, this fault led to further lines being lost due to excessive load propagating through the power grid. This negative-electrical epidemic spread across a considerable part of the nation and led to a regional blackout.

Further investigation pointed to additional “causes.” A parallel and compounding problem was a software failure in a control center. Another was that trees that had been supporting electrical cables had grown too tall, promoting short circuits. Another was that the utility companies managing parts of the grid did not have as effective or efficient a communication strategy as is needed under pressure.

The blackout inflicted an economic cost of around $10 billion.

To summarize, a software network interacted with a physical cable network supported by a forest ecological network overseen by a stressed human social network. The failure was not “disciplinary” or “departmental;” it was complex. A full understanding of one critical infrastructure, the power grid, requires an understanding of a multitude of overlapping networks.

Complexity science is an effort to discern and theorize common patterns in complex systems from multiple scientific perspectives. Many scientific disciplines are already associated with powerful models and theories: in biology, for example, there is the theory of evolution; in economics there is utility maximization and game theory; and in engineering mathematics there is Alan Turing’s theory of computation.

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