Litterbug: selling and ERoEI

I was surprised to read something nonsensical onTwitter yesterday morning only as it was put there by a fairly well respected renewables slogger, and (after a day of sanity away from social media) annoyed to see the poster claiming the nonsense was to illustrate some financial point.

“an ERoEI of 60 over 60 years and 25 over 25 years are identical!”

ERoEI is Energy Returned on Energy Invested. It’s an important metric in places. According to twittering huckster’s thread he was thought riffing on it as a public service:

“So next time some armchair nuclear power hero hails #ERoEI as the reason only nuclear can power the world, you can straighten them out. 

I haven’t seen many nuclear proponents hammering away on ERoEI. I did know the World Nuclear Association published an exploration of nuclear’s ERoEI, but I had interpreted that as defending itself from frivolous claims – which has long been made by travellers of the soft path. The first link I checked on when googling “ERoEI of nuclear was a 2013 article at the currently reputable Carbon Brief – which is apparently a huge change over just half a decade:

…the range of estimates for nuclear’s EROI is very large indeed, ranging from an estimated 40 to 60 – from the World Nuclear Association – to less than one. Inman tells us he used a paper that reviewed many studies, which puts nuclear’s EROI at five.

My own little thought experiment will revisit this 1970’s approach, using Germany’s history with renewables to explore the impact of Germany’s renewables surge on systemic ERoEI:

Many energy analysis studies done in the 1970s seem to have assumed that a rapid expansion of nuclear generating capacity would lead to a temporary net energy deficit in an overall system sense. However, this requires dynamic analysis of whole systems…

I won’t discuss the half-a-century of hammering nuclear on ginned-up claims, or the current carnival barker’s petty use of “60 over 60 years” – when the WNA essentially has 60 (59) over 40 years as a claim (and 79 over 60 years), but this idea of systemic ERoEI to demonstrate a far more relevant metric for value.

Two striking graphics from Germany, home of the Energiewende: the first shows annual generation by fuel/type:

Not shown, in the graphic or at that site, is the growth in net exports over the 2002-2018 period, but figures from elsewhere (AGEB) show those rising by about the same amount as generation – indicating little change in German demand.

The second graphic is annual generating capacity for the same country over the same period of time from the same data source:

In 2018 Germany had about 79% more capacity than in 2002, to produce only 8% more output – with the increase exported. 

How would you like you’re ERoEI analysis of capacity added after 2002 to be performed?

If you want to claim things like an ERoEI of “25 over 25 years”, you certainly don’t want a systemic approach.

The metric that is avoided in public discourse is “capacity credit/value”, which is complicated but essentially a measure of a generator’s ability to meet demand. Germany has added over 100 gigawatts (GW) of renewables capacity without being able to reduce the capacity provided by fossil fueled generators – in fact the increase in gas-fired capacity from 2002 to 2018 more than cancelled out the small reduction in coal-fired capacity.

That ERoEI metric is supposed to account for the energy in building a facility, as well as running it. The systemic value of generating facilities lacking capacity value is simply the avoided energy spent in extracting fuels to generate electricity from the remaining, firm, facilities. If one ignores the systemic impact the inflated ERoEI of the low/no capacity value renewables source comes at the expense of lowering ERoEI of the other generator that exist in the system in order to ensure demand can be met, but are less utilized when twinned with sporadic generators.

If this lesson seems familiar it is because of the same limitations of a myopic valuation of the levelized cost of electricity (LCOE, also known as LUEC), where the lower the value claimed for a sporadic source of supply, the higher the value has to be claimed for its needed firm supply caretaker.

The sellers of sporadics can find lots to quibble with in the German example, where improvements in solar panels are only pushing annual capacity factors, according to the data illustrated above, towards 12% (and wind is not much above 20%). This does indicate a use for ERoEI: one might figure out spending on panels in a region of poor solar resource, with a winter demand peak making the capacity value nil, is less intelligent than spending in an area with plentiful solar and a summer peak during warm afternoons.

Comparing sporadics to firm resources on any timescales without an understanding of metrics, and their situational value, doesn’t strike me as being very bright.

Arguing for unnecessary supply at the expense of trivial-emissions supply strikes me as arguing for littering, but I do understand the type: anything for a sale.

note: spreadsheet

4 thoughts on “Litterbug: selling and ERoEI

  1. Deep into the study of EROi etc is the study of capacity VALUE. Getting a capacity factor for wind is easy compared to understanding its capacity value. Capacity factors require measurement: capacity values require computation and assumptions and so forth. This report from MISO shows them trying to figure it out. The number they seek is ELCC (Effective Load Carrying Capacity), in other words, how much load can wind can be counted on to carry. I can’t follow it all, but two things seem clear: The capacity factor of wind is higher than its Capacity Value. The more wind on the grid, the less it is worth in terms of Capacity Value.

    Click to access 2018%20Wind%20Capacity%20Report89288.pdf


  2. Thanks for that interesting, but difficult read.
    I think that the complexity is one reason capacity credit isn’t discussed – a minor one compared to it’s not a favourable metric for wind.
    Working with data I find it easy to estimate: find the peaks in the demand, and then rerun the data set with the wind generators removed: divide the difference in the peak and the residual peak by the capacity of the removed wind generators and that’s a nice estimate of capacity value/credit.

    Liked by 1 person

    • Your method seems very reasonable. Some of these analyses strike me as overly complex (the one in this report for example) because a more straightforward analysis would not give anywhere near the results desired. In ISO-NE, wind can bid into the forward capacity market, so the question becomes: at what level does it bid in? What is its “capacity value”? Nobody knows the answer. With a lot of wind on a system, wind wouldn’t want to be considered “zero capacity”, but then again, plants can be fined for not-going online when the grid is stressed. So what to bid in?
      Oh what a tangled mess we weave when we set up wind as “dispatchable” and believe me, many groups do claim it is dispatchable. See slide 22 of this recent presentation at a New England meeting. Compare wind and nuclear, in terms of “dispatchable.”

      Click to access clg_meeting_littell_keynote_presentation_june_20_2019_final.pdf


      • That MISO document was about the share of wind’s capacity that could bid into the capacity market – by locational segments.
        I could get a good idea of the value in the NE-ISO if I had hourly data for generation. I do have 3 full years of hourly demand data (2016-2018) from the EIA site), so if you know of a source for hourly wind data I could run an analysis pretty quickly.

        As for the slide, it is nice to see wind (and solar) increase flexibility – but it only happens when they aren’t producing at maximum outputs. In Ontario we pay them, richly, for what they produce so that there’s little reason for wind to provide other services.
        As I understand it in the US nuclear is prohibited from providing some ancillary services – but that’s beyond my comfort level for discussion.

        Liked by 1 person

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