Amory Lovins and His Nuclear Illusion – Part Five (Nuclear Plant Reliability)

We are now on part five in the continuing series that seriously looks at RMI’s latest nuclear bashing paper. RMI tries extremely hard on pages 21-26 in their paper to show that nuclear plants are unreliable. Sadly for RMI, a widely publicized set of data refutes their claim: capacity factors. A capacity factor is the amount of electricity a power plant actually produces in a period of time divided by the amount of electricity the plant is rated to produce during that same period of time. A high capacity factor implies high reliability.

From RMI, page 24 (pdf):

Though micropower’s unreliability is an unfounded myth, nuclear power’s unreliability is all too real.

In arguing that nuclear plants are unreliable, the RMI paper brings up a Union of Concerned Scientists’ report on long outages, refueling outages, heat waves, the shutdown of seven Japanese reactors due to an earthquake, and the 2003 Northeast Blackout. Other than the Japanese shutdowns, the four issues RMI brings up are all captured by the data in the graph below. Since 1971, U.S. nuclear plants have substantially improved their performance and reliability. RMI’s paper focuses on some unflattering situations that affected selected nuclear plants. As a fleet, though, U.S. nuclear plants have performed at a 90% capacity factor since 2000. RMI’s cherry-picking is showing again. They focus on a few negative events and ignore the outstanding performance of the rest of the fleet.
It is also interesting to note that nuclear plants have the highest capacity factors of any fuel type in the U.S. (source: Ventyx/Global Energy Decisions based on EIA data). Last year, nuclear plant capacity factors averaged almost 92 percent. If that is “unreliable,” as RMI claims, then what IS reliable?
From RMI’s paper, page 24:

Nuclear plants are capital-intensive and run best at constant power levels, so operators go to great pains to avoid technical failures. These nonetheless occur occasionally, due to physical causes that tend to increase with age due to corrosion, fatigue, and other wear and tear.

Actually, the data show the opposite is true. The average age of the operating U.S. nuclear plants is 28. The first graph above shows that the U.S. nuclear plants have improved their performance as they have become older. Not only that, Nine Mile Point 1 and Oyster Creek (nearly 40 years old and the oldest operating reactors in the U.S.) both averaged a capacity factor greater than 90 percent over the past three years.

From RMI’s paper, page 24:

Yet size does matter. Even if all sizes of generators were equally reliable, a single one-million-kilowatt unit would not be as reliable as the sum of a thousand 1-MW units or a million 1-kW units. Rather, a portfolio of many smaller units is inherently more reliable than one large unit—both because it’s unlikely that many units will fail simultaneously...

Inherently? Actually no. Let's do the math. Say one power plant at 1,000 MW is 90 percent reliable. According to RMI's logic, two 500 MW plants at a 90 percent capacity factor are more reliable than the 1,000 MW plant. The probability that these two plants will provide 1,000 MW, however, is not 0.9 (90 percent). It's 0.81. All you do is multiply 0.9 times 0.9. This is called joint probability which means that in order to find the probability of an event with two or more random variables, you multiply each of their probabilities together. So if you have 10 units at 100 MW each, the probability that all ten will be able to provide the 1,000 MW is 0.35. The probability of success continues to diminish as you increase the number of plants. The same conclusion occurs if you change the capacity factor up or down. There is of course much, much more to managing the grid but based on this simplistic statement from RMI, I am curious how they make the math work!

RMI's statement from above comes from Mr. Lovins' book Small is Profitable. I don't know if there's more information that backs up their statement above, because the $60 book is temporarily out of stock on Amazon and the link to buy the book on its own website is broken. But based on my simple calculation, one plant is more reliable than 10, 100 or 1,000 plants that are “equally reliable” providing the same amount of capacity.

That’s it for this post. I only need to show capacity factor data that is objective and traceable to a widely accepted source and calculate some simple probabilities to show that RMI’s claims are spurious. For those new to this debate, here are links to my previous posts for this series: Amory Lovins and His Nuclear Illusion – Intro, Amory Lovins and His Nuclear Illusion – Part One (The Art of Deception), Amory Lovins and His Nuclear Illusion – Part Two (Big Plants vs. Small Plants), Amory Lovins and His Nuclear Illusion – Part Three (Energy Efficiency and “Negawatts”), and Amory Lovins and His Nuclear Illusion – Part Four (Costs of New Nuclear Plants). One more post from me left to go...