I believe distinguishing between these two potential definitions is of value:
1.) The 92.5% expectation of steady supply of 8% or greater of its rated capacity, measured 60 times per second, over a peak demand contract period (typically one hour). (Perhaps analogous to the probability a batter will at least make contact with EVERY PITCH thrown at a particular ‘at bat.’)
2.) The 92.5% expectation that wind will supply 8% of its nameplate capacity or greater at any single future sample increment of peak demand. (The batting average)

After three years of devoted study to this issue, I am sorry to admit that I don’t have my arms fully around the nuances of the terms.
…cause it’s ONE, TWO, THREE strikes you’re out at the old …ball …game !!! !

The 2007 US average per household is 11,232 kWh per year, but there are regional variances and California is 6,955 kWh per year. This information was derived from http://www.eia.doe.gov/cneaf/electricity/esr/esr_sum.html. As California is the target customer area, but not necessarily the actual end user group, the number calculated is about in the middle of that range. The calculation was a test of the basis for the claims made. In any event, as we point out, this is not a realistic way to look at the performance of wind plants.

A while back, as I began to parse the energy implications for wind integration, it was easy to become bogged down with industry argot, which often blurred concepts in the way that experts often do to make even simple ideas appear to be abstruse and “technical.” People spent whole papers arguing about the importance of capacity factors, for example, as if they were arguing the importance of Talmudic texts. In reality, the capacity factor business, I ultimately discovered, obscured the real fly in the ointment, which was wind’s utter lack of effective capacity (capacity value) within a system that insisted upon virtually certain effective capacity. For several years, I have used the two terms–capacity credit and capacity value (or effective capacity) differentially to explain what is distinctive about them.

Good methodology is too often subverted by sloppy definitions, and not just in the energy business. They often create what is known as methodological “slides,” allowing an argument to slip from one focus to another without proper adjustment–such that apples can then appear to be oranges. This is why operating definitions musts be rigorous and fairly applied.

The critical test for “capacity value” for wind is: how much electrical output can we really count on when electricity demand is at peak levels? Since we don’t know if the wind will “actually” be blowing at the time of peak demand, the real answer to the question is “zero.”

Hence, I maintain that there should be a clear standard for explaining the difference between “expected” energy for planning purposes, based upon historical averages, and “actual” availability of energy whenever demanded.

My car, for example, has a capacity factor of, perhaps, 10 percent, given the time I choose to drive it. Based upon my experience, my car also has these days a very high capacity credit beyond 99 percent. And it’s capacity value–or effective capacity-is the level of my confidence that my car will be available for use at any 15 minute time-ahead interval. You will note that this idea is not quite the same as the idea behind capacity credit.

Let’s return to my baseball analogy. Applying these ideas, I can say that a 300 hitter has a 30 percent chance of getting a hit during any future at bat, which would be his capacity credit. But if a particular batter performs in next at bat just as I predict, that is, for me, his effective capacity.

Overwhelmingly, the performance of conventional generators on the grid mirrors my experience with my car, making their capacity credits virtually indistinguishable from their effective capacity. With volatile intermittents like wind, however, the distinction is cavernous–and mathematically infinite, since there is an infinity between zero and one.

And it’s for this reason that the “cost” of wind projects can’t really be fairly compared to the “cost” of conventional generators, since doing so compares things that do work as expected on demand with those that do.

As to the effective capacity issue, I think that if we go back to a definition of effective capacity as the expected value at the 92.5% level, then we get to the kind of 6-8% numbers that are used in various pools. That is to say, we are more than 92% confident that xx% of the wind capacity will be available during specific hours of concern. E.G., with 1,000 MW of wind capacity and an effective capacity of 7.5%, we think that wind can provide 75 MW of capacity during the specified period.

I am more comfortable with the concept of capacity value than capacity credit, which is usually a negotiated and sometimes political number. I hope that we have maintained a clear distinction in this article. Finally, we try to make a clear distinction between capacity value (or effective capacity or capacity contribution) and average output or annual average capacity. I agree that such a figure is misleading and we show in the post how reliance on such a concept leads to erroneous conclusions.

Finally, we wanted to show that a single wind project cannot be considered in isolation from other intermittent suppliers, especially when intermittent supplies are large relative to the overall system.