Compiled June 21, 2001 by Bruce W. Radford, editor-in-chief, from contributions as noted from Carl J. Levesque, associate editor, and Phillip S. Cross and Lori A. Burkhart, contributing legal...

## Gas-fired Generation: Can Renewable Energy Reduce Fuel Risk?

both customers and company shareholders than the fixed-price contract

scenario (i.e., the standard deviations are larger), whether wind is present or not. The reason is that the capacity payments in the power pool are highly volatile, as they depend on loss-of-load probability, which fluctuates greatly with peak load.

Moreover, the effect of substituting wind for gas varies strikingly between the two unregulated market scenarios. In the power pool scenario, the addition of wind appears to increase the standard deviation of revenues, but it decreases the standard deviation of the return on equity. The expected revenues, net income and return on equity are all somewhat lower with wind, to the benefit of electricity consumers but to the detriment of company shareholders. The main reason is that the wind plant slightly reduces the amount of high-cost fossil generation needed to supply loads at the margin and therefore reduces the variable portion of the electricity price. The results of the contract scenario, on the other hand, closely resemble those of the regulated market scenario. The main difference is the reduction in the standard deviation of return on equity resulting from the wind addition, which is accompanied by a slight increase in the mean ROE.

Valuing Risk Reduction

A critical issue in interpreting the results of a study like this one is estimating the value of changes in risk either for customers or utility company shareholders. There is, first, the possibility of a change in the expected, or mean, outcome, which occurs if the probability distributions of the input parameters are skewed in some fashion. In our study, the only such skewed distribution is that of environmental regulatory costs, which we believe are far more likely to increase than to decrease. The effect of this bias is easy to account for, and we already see it in the difference in mean revenues between the gas and wind cases in the regulated market scenario. (In Table 1, with no variations in the input parameters, the difference in mean revenues is $308 million, but in Table 2 it is $21 million. Thus, one can say that accounting for high

environmental regulatory risks reduces the mean revenues of the wind case compared with the gas case by $287 million.)

More challenging is the problem of assigning a value to changes in the variability of a cash flow. This is accomplished in decision analysis by calculating a risk premium, which is proportional to the

variance (or standard deviation squared) of some cash flow. This approach derives from expected utility theory. The certainty equivalent of the cash flow, which is the amount it is worth to a decision maker absent any risks, combines the mean with the risk premium in the equation:

CE=(CF)+a-2s2CF

where a is known as the risk aversion coefficient. In future cash flows, the certainty equivalent can be converted to a present value by discounting at a suitable risk-free discount rate.

The risk aversion coefficient can be measured directly by surveying the opinions or observing the investment behavior of the key decision makers or stakeholders. Absent such information,