“Michael Goggin says that attacking the validity of the CEMS data is a sure sign of desperation. But it can be argued that any possible desperation is on the other side.”
In my 2014 post Where Wind Studies Go Wrong: Cullen in AEJ (Part II) , Michael Goggin of the Amercian Wind Energy Association (AWEA) made a comment that recently came to my attention, which deserves a rebuttal despite the lapse of time. My 2014 post critiqued a paper by Joseph Cullen, Measuring the Environmental Benefits of Wind-Generated Electricity.
In summary, Goggin’s points were as follows:
Goggin concludes his criticism by offering three references rebutting a report by the Renewable Energy Foundation (REF) that showed low wind-turbine lifetimes.
These four points do not withstand scrutiny.
CEMS Data
I said the CEMS data was hourly based, which is correct. Cullen also said he used CEMS hourly emissions data.
With respect to the CEMS data, measuring every 15 minutes is subject to the same considerations as that described for load and wind production measurement at this time scale, described here in that it misses a lot of activity even within 15 minutes, and therefore it will not be taken into account.
Averaging these 15-minute measurements to be used for hourly reporting further reduces their value.
Also an IEA paper reports the questionable accuracy of emissions measurement systems (see page 35 here).
Apparent Contradiction
Regarding a contradiction between my posts and an article published by the IER re fuel consumption data, I followed Goggin’s link but found no contradictions or comments including such in the IER paper.
No matter. Any apparent contradiction might be explained on the basis that there are at least three ways to determine fuel consumption:
(1) exact measurement;
(2) a more general means of measurement, including some calculations, (like the CEMS approach to emissions); and
(3) back calculation from electricity produced using simplistic efficiency assumptions.
The first is the most difficult because of the nature of the generation technologies, and the other two are suspect because of likely errors in the assumptions and process used.
So it is possible to argue, without contradicting one’s self, that fuel consumption is suspect for the last two and good for the first. I would argue for exact measurement as the best approach, but admittedly not the easiest.
ERCOT and Texas
Turning to ERCOT, Goggin questions my analysis on the matter of interstate trade with reference to the difference between all-Texas and ERCOT. I introduced the term interstate to differentiate with imports/exports, which is often used for international transactions.
This has compounded the issue somewhat because ERCOT does not represent all of Texas, and it would have been better if I had left out this rather fine distinction in terminology.
ERCOT supplies 90% of the electricity consumption for Texas, and so my use of all-Texas data does introduce some imprecision. (Note I did introduce the analysis as ‘a quick test’.) The point was that outside electricity trade for ERCOT, although quite small (Cullen says less than 1%), is still about the same size as wind production (Cullen says about 2%), and these levels are similar to my analysis results for all-Texas as provided in Table 1.
In summary, the impact on emissions of such trade will be sufficiently comparable to wind that it should not be ignored in the analysis as Cullen suggests just because it is small. This level of consideration is often the case in other jurisdictions.
Goggin claims that to ask any Texas electricity regulator if ERCOT engages in interstate commerce in electricity will receive a forceful rebuttal. I think this shows how my introduction of the term ‘interstate’ compounded the issue. Such rebuttals may be based on the deceptively small levels involved, or simply by the use of the term ‘interstate’. All this aside, Cullen does speak to transactions with other jurisdictions, and that is what matters.
Wind Turbine Lifetimes
The issue of wind turbine life-times is more contentious. To start I suggest the reader go to my recent post and the cited Renewable Energy Foundation (REF) paper. (Note the link in my offshore wind post needs updating to that shown here and as indicated in Comment 3 of the that post.)
Goggin has attempted to rebut this with three references, which I have looked at. Those interested should read these three carefully for quality and clarity of analysis and then compare them to the REF treatment. I suggest that there is no absolute winner, and leave it to the reader to decide where the weight of evidence and its treatment lies.
Conclusion
In his lead off comment, Michael Goggin says that attacking the validity of the CEMS data is a sure sign of desperation. But it can be argued that any possible desperation is on the other side.
Because I spent years dealing with US CEMS data I am writing to verify your response to “EPA’s Continuous Emissions Measurement System (CEMS) measurement was on an hourly basis and thus understated the real cycling-related emissions from wind power as a result. (Goggin says CEMS takes emissions measurements every 15 minutes and reports hourly based on averaging these results.)”
You responded: “I said the CEMS data was hourly based, which is correct. Cullen also said he used CEMS hourly emissions data.“
Goggin is wrong to say that CEMS take measurements every 15 minutes. Actually the sampling time is in seconds and the base averaging time is one minute. The minute data are rolled up into different averaging time intervals depending on the parameter. Those sub-hourly data are used to determine the validity of the hourly average data. The key point is that only hourly data are reported. The only way to get the smaller time interval averages is to get it directly from the facility making the measurements and they have no obligation to provide that data so extracting the data is problematic.
While the IEA paper reports on the questionable accuracy of CEMS emissions keep in mind that there are also issues with other emissions calculation approaches. I believe it is the best of relatively weak approaches.
Ultimately I believe you are not attacking the validity of the CEMS data itself but the use of hourly CEMS data to try to determine sub-hourly effects. On that score I agree completely.
Good for Roger Caiazza as he returns Michael Goggin’s syrupy backspin of disinformation about CEMS’s measurement reportage. As AWEA’s chief public relations “reseacher,” Goggin has grown comfortable in his role of convincing the rank and file that the pigs of wind technology can fly, using the rhetorical equivalent of pixie dust–and the hope and trust of true believers throughout the land.
In many ways, however, Mr. Caiazaa and CEMS miss the real point about the problems of averaging wind performance over time (whether that duration is for a month, a day, hourly or even quarter hourly, then reporting their results in the form of a snapshot at a given point in time. For those results for wind performance are then compared with the performances of firm capacity generation taken at similar points in time. Casual readers then too often assume that wind generation is much like capacity generation; indeed, they’ve come to believe that wind is as respectable as any other energy source in the repertoire of electricity generations. Goggin has fastidiously nurtured this idea for much of the last decade. And too many people have played along.
The reality is that wind technology’s inherent volatility is relentless, persistent, unpredictable, unquenchable–except for when the wind is blowing at less than 8mph or when the wind turbines are intentionally shut down. Kent’s key finding, which he reported accurately in a recent MR post, is that wind output variations are much more frequent and widespread, even on a second by second basis, than people have been led to believe. Wind output is problematic not when the wind is blowing too much or too little; it is problematic because its fuel is intrinsically gusty. And there’s nothing short of shutting the turbines down that can be done about it.
No one really has to “extract” fine grained wind outpoint data from measuring sources unwilling to share that data (I’ve come to love the way the wind industry hides behind its proprietary data shroud, for it provides much material for satire). All one needs is to apply the basic formula that governs the way wind energy is converted into ancient power, which is w=1/2 rAv3, where w is power; r, air density; A, rotor density; and v is wind speed. The main driver in the equation is the V3, which dictates that any output must be a function of the cube of the wind speed at each wind speed interval throughout the windplant’s rated capacity. Consequently, if a wind plant rated at 200MW is generating 6MW when the wind is blowing at slightly over 10mph, it will generate about 10MW when the wind speed hits 12mph a few minutes later; or 10MW when the wind speed achieves 19mph, perhaps 15 minutes later; or 3MW when the wind slides down to 8mph in 10 minutes; or 0, when the wind speed becomes less that 8mph. This up and down outpoint is existential–and caused by the gusty nature of the fuel. All the reports I’ve read about wind speed performance at higher altitudes–altitudes above 400 ft–suggest that it’s even more volatile than at ground level.
Since variation in supply must be balanced at all times to keep it securely aligned with demand, dispatchable conventional generation (mostly fossil fired) must be continuously toggled (ramped up and back) to “integrate” the continuous wind flux. It is the emissions from this toggling–emissions that would not occur if there were no wind flux–that is the issue. How to measure this properly is the real question. It hasn’t been done yet, as Kent convincingly demonstrates.
Nonetheless, the FACT that there has not even been a clear correlation between wind output and declines in fossil fueled generation, even in high wind areas, should provoke some thought–and even a modicum of curiosity–about why this phenomenon continues to persist.
It’s irksome, at best, to see how the Goggin’s of the world use unscience and goofy technology to sell soap like the wind mess, with its crypto/techno flummery, its economists unctuously comparing fish with bicycles without regard for assessing functional value, and its engineers employed as magicians to make bullshit appear to walk and talk when the fact is that it’s sitting in a huge pile in the middle of the road, stinkin’ to high heaven….
I agree with your reply
I have a question you might be able to answer. The “solution” to intermittent wind is to make the turbines bigger or put them off shore. With respect to the bigger on-shore turbines I wonder if anyone has addressed the nocturnal boundary layer wind profile. When skies are clear at night, air temperatures near the ground drop after sunset and an inversion layer forms. In this inversion layer the air temperature rises as elevation increases and vertical atmospheric motions are suppressed. As a result friction decreases at the interface between this layer and the layer above it and wind speeds increase in the upper layer. This is called a low-level nocturnal jet.
When you build a big wind turbine the hub height might be above the inversion layer so the wind speed is high but anything below the inversion layer is in calm winds. Has the wind industry dealt with this vertical wind gradient? This is another nuance to the point of your post that the short-term variations matter. Just because the meteorological data, at say 100m, indicates that there is more wind available at that level does not mean a larger turbine necessarily works that much better because the wind profile at 100m during these conditions does not have as much value. Surely the fact that a portion of the turbine is in a layer with no wind would degrade performance. Just wondering.
Correction to my comment above. When the wind speed hits 19mph, the wind output will yield about 38MW for a 200MW wind plant.
Roger:
The issue with wind output is not its intermittence. All electricity generators are to some extent intermittent, almost all of which is due to operator choice: maintenance, load balancing, even operational design (e.g., open cycle gas turbines). Conventional generators are all dispatchable and controllable; if for some reason they are not, they are quickly removed from the system. By contrast, wind intermittence is unpredictable and utterly random: one can never know at any given future interval what a wind turbine will produce. If wind output’s intermittence produced a steady yield, it might actually do some good, even if it were unpredictable. The killer for wind is its output flux, which ranges throughout the entire arc of a wind plant’s rated capacity, from 0 to whatever. This variability is not the same as intermittence. Consequently, even if we could predict wind production with greater precision, wind’s relentless flux would still induce substantial inefficiencies on wind following thermal generators.
This is something not generally discussed. The reality is that wind output cannot be loosed on the grid by itself. Rather, it must always be accompanied–entangled–with conventional generation in hyper ramping mode. This is NOT a backup scenario akin to having a highly skilled understudy replace an ailing diva or a backup computer data drive. Rather, it constitutes a weird reversal of this concept wherein it is the backup that does all the important work for the system–such that wind becomes an encumbering supernumerary.
Thank you for sharing your thought-provoking commentary about the potential problems for wind performance at altitudes of 100m+ vis a vis nocturnal inversion layers and the low level nocturnal jet. I learned of this phenomenon some years ago in the context of identifying problems for migrating songbirds as they navigate on clear nights around tall structures like cell towers. But I hadn’t logically connected it to how it might affect wind turbine performance. One might think that wind engineers would be at work to assess and address the issue. But it’s not clear to me that this is so, in large part because the industry continues to install larger and taller turbines with even longer rotors. Perhaps they’ve developed sensors that would detect the inversion phenomenon and, for a time, instruct the rotors to be feathered.
In general, the larger the wind installation and the greater its capacity factor, the larger the wind flux and the wider the swings of output–all of which threaten grid reliability and security when the amount of wind output becomes a substantial portion of the grid’s fuel mix. Not to mention the quotidian attendant heat rate penalties that must accrue to keep wind in the mix at all.