Yesterday, I introduced a series of blog posts aiming to show you the errors and limitations in the latest nuclear bashing paper from Amory Lovins and the Rocky Mountain Institute. This first part (and the longest of this series) deals specifically with the graph below in the RMI paper (also found in their condensed version). There are many details and flaws in the graph, so please bear with me while I walk you through them. If you get lost, don’t despair. Just take your time and if you have questions, please comment.
Nuclear’s “true competitors”
For years now, Amory Lovins and RMI have been claiming that nuclear power’s “true competitors” are not big coal and gas plants but energy efficiency, small scale renewables and decentralized cogeneration. From the condensed version:
While nuclear power struggles in vain to attract private capital, investors have switched to cheaper, faster, less risky alternatives that The Economist calls “micropower”—distributed turbines and generators in factories or buildings (usually cogenerating useful heat), and all renewable sources of electricity except big hydro dams (those over ten megawatts). These alternatives surpassed nuclear’s global capacity in 2002 and its electric output in 2006. Nuclear power now accounts for about 2 percent of worldwide electric capacity additions, vs. 28 percent for micropower (2004– 07 average) and probably more in 2007–08.After digging into the numbers from their Excel spreadsheet and the methodology (pdf) for the above graph and paragraph, I found the story is much different than what the paper claims. According to the graph above, nuclear’s “true competitors” are already beating nuclear … except that they aren’t.
With the exception of nuclear, the data for the chart aren’t actual generation numbers. RMI collected the capacity and capacity factor data for the other sources to calculate the generation. Most of the capacity and capacity factor assumptions are reasonable but there is one capacity factor the methodology assumes that grossly overstates the contribution from nuclear’s “true competitors.”
By far the largest non-nuclear source of electricity in the above chart is decentralized generation (the big orange block) which the Excel file calls “Non-Biomass Decentralized Co-Generation.” The paper assumes an 83 percent capacity factor for this source. The problem with the 83 percent capacity factor is it is twice as high as what it should be. Here is RMI’s explanation for the 83 percent capacity factor found in the methodology (pdf) on page 6:
Having neither electrical output nor capacity factors from any traditional sources, we again turned to help of Michael Brown of WADE. He provided an estimated average capacity factor in terms of hours per year: “7000-7500, possibly more.” Running 7,250 hours per year equates to a capacity factor of 82.8%, which we applied uniformly to all years under consideration.Michael Brown’s statement is ambiguous. Does his statement mean non-biomass decentralized plants operate at full capacity 83% of the time? Or does it mean they are available to run 83% of the time? Being available to run is very different from actually running.
The methodology’s source for decentralized data is the 2005 Survey by the World Alliance for Decentralized Energy (pdf). According to the survey, there were 281.9 GW of decentralized capacity in the world as of 2004 (page ii, the survey also says 282.3 GW on page 32 which is what RMI uses). RMI’s methodology backed out the decentralized renewables’ capacity from the 282.3 GW to find the “non-biomass decentralized cogeneration capacity” at 266.3 GW.
What’s off about WADE’s 2005 Survey is that the surveyed countries reported a total of 341.6 GW of decentralized plants, not 281.9 GW (this was found by adding up each country’s data on pages 13-27). When the generation data of decentralized plants also are added up for the reporting countries, I calculated the capacity factor to be 40.1 percent (excluding Russia because they didn’t report generation numbers). I also added up the same numbers from the 2006 WADE Survey (pdf) and found the capacity factor to be 38.9 percent, pretty close to the 40.1 percent value found from 2005 WADE Survey.
If the capacity factor for all decentralized plants is only 40.1 percent, then it is impossible for “non-biomass decentralized co-generation plants” to achieve an 83 percent capacity factor since they make up the majority of the decentralized capacity. If we substitute a 40.1 percent capacity factor for the incorrect 83 percent capacity factor, here’s what the graph would actually look like:There’s more.
After 2007, the “Total renewables plus decentralized generation” line begins to increase faster than in the previous seven years. Since 2008-2010 are projections, one would think there is a methodology for this increase. There is not. According to the RMI paper, the “non-biomass decentralized co-generation” projection is a “target” based on personal communications with WADE. There is no model, study, or methodology mentioned to support the projection.
Here’s page 6 from RMI’s methodology:
The 2005 WADE survey cites, as a target for decentralized energy, 14% of total world capacity by 2012. In personal communications with WADE director Michael Brown, he conceded that realistic projections would be closer to 12%.Wow. If I were claiming that decentralized generation and renewables are supposedly beating nuclear’s generation, then I would rely on something a bit more meaningful than a “target.”
Distorting the Graph According to Edward Tufte
The original graph from the paper distorts the contribution the “true competitors” are actually making. Edward Tufte, described by The New York Times as "the da Vinci of Data", is a big opponent of chartjunk. Here’s what chartjunk means:
The interior decoration of graphics generates a lot of ink that does not tell the viewer anything new. The purpose of decoration varies — to make the graphic appear more scientific and precise, to enliven the display, to give the designer an opportunity to exercise artistic skills. Regardless of its cause, it is all non-data-ink or redundant data-ink, and it is often chartjunk.RMI’s graph is all “chartjunk.” The graph displays a lot of ink for the “Total renewables plus decentralized generation” data that deceives the eye. Graphical representations of data help people understand the big picture. But there are correct ways and incorrect ways to show the data. If we take away this “chartjunk” and not stack nuclear’s “true competitors” on top of each other, here’s what the graph actually looks like (including the correct capacity factor data for the orange line).From 2000-2007, it looks like all lines have increased the same as nuclear (which is not much). Contrast this with the following statement in RMI’s condensed version:
These alternatives surpassed nuclear’s global capacity in 2002 and its electric output in 2006.Doesn’t quite look like it.
Cherry-Picking the Data
The definition of cherry-picking is:
the act of pointing at individual cases or data that seem to confirm a particular position, while ignoring a significant portion of related cases or data that may contradict that position.My two altered graphs above paint a different picture than what the RMI paper claims. What’s more interesting is that the 2005 WADE Survey (pdf) also tells a story different than that of RMI. Here are some examples:
The US decentralized cogeneration market grew significantly up to 2002 but its subsequent slowdown continues in the face of high gas prices and persistent regulatory barriers. The capacity added in 2004 was the lowest for six years. (Page. ii)It’s hard to imagine the rest of the world booming with decentralized plants if the U.S. and Europe are slowing down. Especially since the total electrical capacity in Europe and the US (xls) is nearly 50 percent of the total capacity in the world. Yet according to RMI’s condensed version:
Europe continues to emerge slowly from an extended period of market paralysis. … The US market for cogeneration, according to US government data, continues to show growth but the rate of expansion has slowed markedly in the last year or so, and this is mirrored overall by unenthusiastic market sentiment. (Page. 1)
negawatts and micropower have lately turned in a stunning global market performance.It is clear that RMI is picking and choosing agreeable data points. This, however, is only one example of cherry-picked data. The rest of my posts will show you other instances in which it appears RMI depends on selective use of data.
Is Coal Included in the “Non-Biomass Decentralized Co-Generation” Data?
Here’s page ii in the 2005 WADE Survey (pdf):
Global installed DE [decentralized energy] capacity stood at around 281.9 GWe at the end of 2004, the great proportion of this consisting of high efficiency cogeneration systems in the industrial and district heating sectors, fuelled by coal and gas and, to a lesser extent, biomass-based fuels.Coal? Nowhere in RMI's condensed version, 52-page paper, or methodology is coal mentioned as being included in the data. This must be why the RMI uses the obscure term “non-biomass decentralized co-generation.” RMI clearly doesn’t like coal since they label it “carbon-spewing”, yet the distributed generation data includes coal to show it beating nuclear. What are we to make of this?
Let’s sum up the apparent mistakes evident in just this one graph. First, RMI’s analysis erroneously uses twice the actual capacity factor for “non-biomass decentralized co-generation.” Second, RMI’s analysis distorts the actual contribution from nuclear’s “true competitors" with the use of chartjunk. Third, RMI’s analysis makes selective use of data in order to state that nuclear’s “true competitors” are turning “in a stunning global market performance” when in fact one their own sources actually says the opposite. Finally, RMI’s analysis misleads the reader by not stating that coal is included in this graph, when actually it is.
This is about as much as I’m going to go into RMI’s so-called numbers and sources. The rest of my posts will focus on the following themes from RMI: centralized vs. decentralized energy; big plants versus small plants; energy efficiency and “negawatts;” nuclear and grid reliability; and costs.