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POWER QUANTS

IT’S QUITE enough to give mathematics a bad name. “Traders Profit as Power Grid is Overworked,” in The New York Times, August 14, 2014, explains how “quants” (those mathematically trained in quantifying data) are exploiting electric power grids.

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The power plant of Port Jefferson, New York, about 60 miles east of Manhattan, was caught up in mathematical intrigue last summer. Image from The New York Times, August 14, 2014, http://goo.gl/Zgj0q4.

At the heart of the problem is the produce-what’s-needed-only-when-needed nature of an electric grid.

That is, it’s neither economically nor scientifically feasible to store significant amounts of power-grid electricity. (As a side issue, this is one challenge of the intermittency of solar and wind power.) If one portion of the grid runs short, it buys power essentially instantaneously from interconnected utilities. This balancing act goes on minute by minute, hour by hour, day by day, coordinated by regional grid operators.

And, following supply and demand, the wholesale prices of electricity vary with time and locale—by a factor of five or more.

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Utilities in New York State are coordinated by NYiso (pronounced NIGH-so), the New York Independent System Operator.

To buffer this, regional operators auction off what are known as congestion contracts, financial instruments akin to stock market derivatives. (Just like in the mathematics of calculus, these derivatives measure how things change.)

Congestion contracts are short-term insurance policies designed to protect the utilities. When strong demand causes irregular spikes in price, contract holders collect the price differences from the grid operators. If a slack causes a drop in price, holders pay the operators.

In theory, these price hedges are supposed to help defray costs and benefit consumers. Platts, an energy trade publication (www.platts.com), reports that more than $2 billion has been invested in the U.S. monthly auctions for energy contracts since 2011.

Enter the quants with their cool computer algorithms exploiting congestion contracts for big bucks.

For example, according to The New York Times, the investment company DC Energy in Vienna, Virginia, made about $180 million over the last decade in New York State alone. Despite its name, DC Energy doesn’t make energy; it trades commodities.

 

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How the game is played. Image from The New York Times; source: New York Independent System Operator.

As an example of congestion-contract trading, last summer DC Energy predicted instability in the Long Island grid. Hence, at a monthly auction it bought congestion contracts paying the differences in prices between multiple points on the Long Island grid, including Northport, 40 miles east of New York City, and Port Jefferson, 20 miles beyond Northport.

Sure enough, a heat wave on May 30, 2013, boosted all electric demand and, thus, prices. However, power-line maintenance near Northport precluded its sharing electricity with Port Jefferson. On that day, the spot price in Northport spiked from an average $70 to $129 per megawatt-hour. But down the road in Port Jefferson, it soared to $326/megawatt-hour—and DC Energy pocketed the difference, more than $1.5 million within only 48 hours.

This gaming of energy arose over the past decade with deregulation of the U.S. electric grid. The idea was to replace monopolistic practices with competitive markets. It—or at least electric consumers—came up short once the quants applied their mathematical algorithms.

The practice of energy trading differs from flash trading (see http://wp.me/p2ETap-2de), though both depend on quants and powerful computers. Flash traders exploit split-second differences in stock prices; it is a game of nanoseconds. Energy traders exploit the multiplicity of congestion contracts, typically held by electric utilities in a regional grid; it is a game of megacombinations.

Though my heart may question exploitation of consumers, my head has to admire the adroitness of quants and their algorithms.

It’s quite enough to encourage one into mathematics. ds

© Dennis Simanaitis, SimanaitisSays.com, 2014

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