By B.L. THERAJA and A. K. THERAJA

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3 Multiple Generation As observed in Chapter 7, the complexity of the unit commitment problem under the present regulatory environment increases exponentially with the number of generators. However, in an idealized electricity marketplace under deregulation, an owner of several generators can optimize each generator individually, which means that the computation increases only linearly. The key difference between the two situations is that a utility in the present coordinated environment dispatches generation according to optimal power flow; if a given generator is turned off, then the output of all other generators will need to be readjusted in order to remain optimal.

41) Xn2 In this matrix notation, the rows correspond to individual cases or sets of observations, while the columns correspond to different independent variables. 42) where the elements of the error vector e are unobservable. 47) The square root of this estimate (a) is known as the standard error of regression. After a least squares computation is performed, there are a large number of tests and studies that can be done to determine whether the original linear model is in fact appropriate for the data.

15) Unlike the random walk, the variance of a mean-reverting process tends toward a constant for values in the distant future. It is important to note that this conclusion is inappropriate when using mean-reverting processes to model prices, as the parameters x and 1] will slowly change over time. 15) provide a good estimate of future prices. 2 Price Models using Logarithms It should be noted that price models often are applied to the logarithm of the price rather than the actual price, as price changes are observed to be larger at higher price values (a lognormal distribution model), and the use of logarithms means that the price does not fall below zero [6].

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