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Amherst Island Wind Info |
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Aside from carbon emission savings, another intuitive benefit of wind energy would be to improve the performance of the current electrical grid - things like closing fossil fuel plants and divesifying our supply. As usual, the devil is in the details, and it seems the ability of wind power to join the current grid has three aspects: reliable supply (or Capacity Credit), grid integration, and delivery during peak demand.
Capacity Credit must not be confused with Capacity Factor, which is simply what percentage of capacity a plant actually generates. Capacity Credit is a measure of how much electricity a new plant can be depended upon to deliver. In the case of wind turbines, it is typically expressed as how much other generation wind can actually allow to be shut down. For traditional generation, it is calculated using statistical techniques, using the reliability characteristics of the different technologies. If the generating plants are very reliable it means the utility doesn't have to maintain large reserves which both cost money and produce emissions.
You'd think the reliability characteristics for traditional nuclear and fossil fuel plants would be well known and predictable, but I discovered a fairly wide range for values, anywhere from 75 - 100%. Hydro might vary depending on rainfall, and of course wind energy would vary even more widely depending on the wind. I suspect the variance has to do with the time window involved. For one-day operational windows all the traditional technologies are extremely reliable, approaching 100%. The fuel is on-hand, the unit is operational, and only a "forced outage" will cause the electricity to not be available. For longer periods, like over a year, you have to include scheduled downtime. Nuclear reactors are on average available maybe 75% of the time (I read CANDU's only 60% so far), coal and gas 90%, while hydro and wind will vary. In my technology chart I settled on 90% for all of them, just for simplicity's sake.
For wind power Capacity Credit has been controversial. Proponents are eager, of course, to show that wind is reliable and can stand on its own as part of a robust grid. So they apply traditional computational techniques to the question, saying that all technologies are unreliable, just to a different degree. The results of this method produce numbers that vary as the penetration of wind increases. At low penetrations the Capacity Credit is close to the Capacity Factor, decreasing as the penetration increases. At a penetration of 20% it drops to somewhere in the 10% range.
Adopting traditional computational techniques for wind strikes me as invalid, and the ISO's seem unsure of it as well. Ontario's IESO used to use a flat 10% until November of 2008 when they decided to use the median output (i.e. in the summer - 16%). By definition, half of the time wind will produce less than that, so this seems nonsensical. More recently IESO papers have demonstrated the need for a much lower number, 3.2mb, see the chart on p. 21 and the conclusions on p. 22. California originally used statistical techniques for its early wind projects (like Altamont Pass) and came up with numbers in the 20's. Then the summer of 2006 showed just how risky this method was. A calm spell in Germany tells me that anything above 0% is wishful thinking.
All the traditional technologies are dispatchable - they (barring a failure) produce when they are told to do so. Wind, on the other hand, just produces what it can and the grid accepts it. (Well, at least until it overwhelms the demand, as sometimes happens in areas with high penetrations at times of low demand.) This difference is so fundamental that I think a new methodology is needed, but I'm not enough of a statistician to figure out what that might be. Proponents often drop back to the geographical dispersion argument - that the wind must always be blowing somewhere. When presented with the facts, 0.8mb they then drop back further to arguing about the need for a new grid that can transport lots of power long distances. What they don't do is to include the substantial costs of this new grid in their economic justifications.
In a backward sort of way, I approach this same topic in my co2 discussion. Where the two topics meet is the importance of forecasting. After all, if you can accurately forecast the wind (and thus the power production) your "unreliability" goes down and your Capacity Credit goes up.
Some references are below, and you can also google "capacity credit" (preferably with the quote marks) to get some flavor of the arguments.
The GE Report, 1.6mb was undertaken at NY's expense, and states that wind energy can be used, in part, as base load. It is often sited by wind proponents and is thus often attacked as flawed by wind opponents. As an example of reality impinging on industry studies, GE says in the summer peak days the grid operators should be able to count on a production of 17% of the rated output. As mentioned above, and as detailed here, 3.2mb, assuming this high a value is foolhardy.
Reliability also affects the presumed co2 savings claimed by wind power, and is further discussed on my co2 savings page.
Grid integration is a topic I don't have enough knowledge about to even evaluate the papers each side presents. I especially like anything by Mr. Palmer as being the most understandable.
The peak demand for electricity in Ontario is now in the summer (it used to be in the winter), and unfortunately the wind tends to blow less at that time. Given that especially during summer there is a good chance wind will contribute essentially nothing to the grid, it becomes necessary to have other means of generation available at all times. Wind will not displace other generation methods. We will still need enough nuclear, coal, hydro and gas to meet the peak, regardless if wind is in the mix or not. This certainly has been the experience in Denmark, Germany and Spain.
Below are other papers that contain information regarding different aspects of these issues. If you know of any additional papers that should be included here, please let me know.