SEVERAL YEARS AGO, ENGINEERS AT AMERICAN ELECTRIC Power measured the transfer capability or transmission capacity (in this article we will use the terms interchangeably) between AEP and Commonwealth Edison. Using traditional methods, they found that the winter transmission capacity that year was 3,500 megawatts.
Then they performed a more exhaustive and nonstandard analysis. It showed that during the month of January, transmission capacity actually varied from a low of 1,600 MW (less than half the nominal amount) to a high of 6,000 MW (70 percent higher than nominal).
Why is transmission capacity random? How is the probability structure of transmission capacity computed? Why doesn't anybody use random transmission capacity today? This article will try to answer these questions.
But first, it is important to understand why transmission capacity must be modeled correctly - including its random characteristics. Recognizing electric power transmission system capacity as a random variable will reduce risk and transmission costs and will allow increased use of the transmission system. It will improve both planning decisions and energy contracting in the evolving power markets.
Reducing Risk, Increasing Use
It seems a most ingenious paradox, that modeling transmission capacity as a random variable can reduce risk. After all, isn't risk a function of uncertainty? And isn't a random variable a kind of uncertainty?
Pretending that transmission capacity is a nice, solid, constant, deterministic number doesn't make it so. Facing the uncertainty head on is inherently less risky than assuming away reality.