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Risk? What risk? Photocredit.

Our abilities in predicting the future are very limited, but that does not stop people from trying. As a rule of thumb I would recommend not trusting those who seem most certain since they are most likely to hide risks and use their divinations for personal goals. In energy discussions one commonly occurring tool of divination is the “learning curve”. It tells that for each doubling of the capacity of some technology you get certain fractional change in unit costs (a bit more than 20% reduction in the photovoltaics module cost, for example). The message that is usually delivered is that even though something is costly now, it soon will not be… if we stay the course and double the capacity sufficiently many times. Very few acknowledge that the learning curve is not a law of nature, but rather a rule of thumb that might work…until it doesn’t.  Discussion about implicit risks is almost always non-existent. In this post, I will dig into this issue a bit deeper highlighting some of the hidden risks involved.

To do this I will choose one specific future scenario and one specific technology. I choose to focus on the PV module costs, assume that we will increase the capacity by a factor of 100 to around 50TW by 2045. This implies (unrealistic in my opinion) exponential growth of the installed capacity with around 17% yearly growth (see figure below). This is somewhat artificial in a sense that for photovoltaics most of the costs are not from the module anymore, but I do this in any case to illustrate the math of the learning curve. I take the historical module costs and assume that technology has now matured and the module cost will remain the same from now on until 2045. What happens to our learning curves?


Capacity of photovoltaics in this thought experiment

As we proceed to the future, I recompute the learning curve every year by fitting the data to the new, stagnant, cost. We start with the learning rate somewhat above 20% today and then…almost nothing happens! How very exciting.


Learning rate from least square fit as capacity raised to around 50TW without any cost reductions.

To illustrate this I show below the learning curve at 2045 after almost 30 years
without cost reductions while capacity increased by a factor of 100. Learning curve fit is almost insensitive to the future costs since data points decades ago dominate the fit. It can enable the narrative of rapid cost reductions even after a generation of exponential growth without any cost reductions. It seems to be a tool perfectly designed to hide risks. It cannot identity when technology has matured (which might even be useful for marketers or thought leaders looking for lucrative career around single grand narrative).

There are ways to fix this though and the other fit demonstrates this. In this fit I choose to weight the points with the yearly installed capacity with the thought that data from building 100GW of panels is more informative than data from building 1MW. Now the fit does care about recently realized cost and the learning rate collapses. Fit is no longer good for points decades ago, but from the 2045 perspective it reflects what happened recently better.


Designed to enable hype ad infinitum. (Black line aims to get a more useful indicator. In the fit data points are weighted with installed capacity that year. Typo on y-axis label…should be $/kW.)

What would this imply for the costs of building all those panels? The last figure shows the required capital as a function of learning rate. There is an uncertainty of around 15000 billion $. If one only uses the highest learning rate, there is a possibility of understating the capital required for modules by a factor of around 4.


Panel investments as a function of learning rate. Factor of 4 underestimate possible. Who carries this risk? (Maybe another 30-40 trillion or so from balance of system costs?)

Things to ask/look for in cost studies:

  1. What was assumed about the learning effects? Constant learning ad infinitum for some techs and no learning for others? Is there a floor cost or not? There should be.
  2. Was the sensitivity for the learning rate analyzed? If not, then there is an attempt to burden someone (public) with risks (which is a cost) they were not informed about. As I wrote this I found this very recent presentation by Carrara et al., but it is worrying that this is not standard. Presentation tells us (see figure for example) that in our old friend REMIND-model PV share collapses from dominant to 10% range if learning stalls. Sensitivity is also asymmetric so that the sensitivity is larger for decreasing learning rates.  Because of this one would imagine a need to be extra careful in identifying technology maturation.

    Screenshot 2019-01-24 at 16.23.35.png

    PV share in the IAM models is very sensitive to assumed learning.

  3. Was the same learning rate used even after cost structure changed? For example, learning rates for PV are computed for modules, but costs are nowadays dominated by balance of system costs which have different (lower) “learning rate”.  I have read countless of articles and publications where this change of the cost structure is casually ignored. Since the risk seems to be towards lower learning rates than assumed, there seems to be substantial risk of too rosy IAM scenarios in the literature.
  4. Are the costs prior to the imagined future costs discussed? It is bizarre, but some actually imagine costs for 2050 which they then use to make claims about economical options today. Cost comparisons become disconnected from the real world with this one handy trick.

In case you were wondering if obstinately sticking to a narrative well past its best before date could actually happen, see how the wind turbine costs have developed. Costs today are about the same as 15 years ago.


Cost of US wind turbines according to “Wind technologies market report 2017”. Costs today are about the same as 15 years ago.

Meanwhile for example IRENA (and many others) still use the learning curve as if nothing has happened. How come?

screenshot 2019-01-24 at 16.05.40

There is something funny going on on the right hand side don’t you think? Shouldn’t you be a bit more careful with those fits? “No there isn’t. No I shouldn’t.”: IRENA 2017


I have earlier expressed my dissatisfaction with the integrated assessment modeling in the context of climate change. Way too many modelers hide insane and poorly justified assumptions into models and then pretend the outcome is “science”. Recent Nature energy paper by Grubler et al. titled “A low energy demand scenario for meeting the 1.5 °C target and sustainable development goals without negative emission technologies” seems to provide another example of this. I read the paper with interest, but then noticed something in small print on the last page.”Estimates for present-day and mature technology  costs are from the GEA and World Energy Outlook. Assumptions for granular technologies, which include solar PV, small-scale hydrogen production, fuel cells  and heat pumps, and distributed energy storage, such as batteries or fuel cells,  were updated from SSP2 to reflect the more dynamic storyline of the LED scenario.

Hmmm…granular…dynamic storyline…sounds suspicious. Maybe I have to read the supplementary as well. Then from the page 80 of the 122 page supplementary I find the actual cost assumptions. Grubler et al. assume solar PV installed cost of 50$/kW post 2050! This is around 30 times lower than the current costs. (Who cares if its a factor 20 or 40?) Obviously if you wish to make a claim that scenario with lots of solar is economical it helps to invent your own costs so that you get whatever you desire as an outcome. To illustrate how extreme their assumption is, below I compare it with some other projections. (“Breyer” refers to numbers Christian Breyer, a solar advocate from Lappeenranta University of Technology, uses. Greenpeace report was written together with European Photovoltaic Industry Association.)  Grubler et al. assume costs that are an order of magnitude lower than even EPIA+Greenpeace project. Even Breyer’s (finnish equivalent of Mark Jacobson) most optimistic dreams imply around 6 times higher costs.

I am sorry. You assumed what?


To me the cost assumption does not even seem consistent with learning curves (which should be treated with caution in any case).

If one makes such extreme assumptions one would expect extensive discussion and justifications for this. Certainly one should present result with and without such assumptions to see how sensitive results are for those funny assumptions. However, in the Grubler et al. paper this was done quietly and hidden in the supplementary where it is justified with…”The technology portfolio choice in MESSAGE is informed by modifying particular granular and economies‐of‐scope technologies for the LED scenario (Supplementary Table 28) whose stationary cost trends in the original SSP2 scenario was judged non‐compliant with the LED scenario storyline. All other technologies not listed in Supplementary Table 28 have been retained at their original (quite conservative) SSP2 values (e.g. for the year 2050: wind 500 $/kW, nuclear 2600 $/kW, biomass power plants 1200 $/kW, etc.), an assumption in line with keeping LEDs emphasis on efficiency and demand, and granular, decentralized supply options and new organizational IT and digital economy models of combining supply and demand, e.g. in grid‐to‐vehicles but also vehicles‐to‐grids options or other distributed storage options (e.g. hydrogen based).”Cruise.gifSo basically there is no other reason than authors narrative desires. Adding buzzwords “granular”, “organizational IT” etc. does nothing to strengthen the argument. If someone would make a scenario where nuclear power in 2050 would cost 170$/kW (from about 5000$/kW today), he would be laughed at. Probably most outraged would be nuclear engineers with actual understanding of the matters. You do the same with renewables and instead facing ridicule you land your paper in Nature Energy. Hopefully this example does not reflect the intellectual standards of the IAM community.

P.S. I encourage you to have a look at the numbers in their database as well I do not understand those cost assumptions. Sometimes coal prices are negative, sometimes positive, sometimes they are positive in the south, negative in the north…sigh. Also, 4Gt sink seems to magically appear from afforestation. Big if true.

Added 19.10.2018: Bizarre, but this scenario has now become one of the four illustrative pathways in the IPCC Global warming of 1.5 degrees special report. If we were to use 20% cost reduction for each doubling of capacity, reaching 50$/kW level would require about 15 doublings. With current installation rate that would take approximately 100000 years. (If we use the 11% rate which is maybe more defensible as it contains also the currently dominant balance of system costs, it takes more than billion years.) The IPCC scenario database sadly doesn’t contain capital costs for most 1.5 degrees scenarios. Here it is hidden in the 122 page supplementary of the article.

Added 23.10.2018: Accidentally clicked also at the forestry section of the scenario database. What is going on with those residues? First collapse and then huge increase when underlying forestry production increased only by about 40%.


Modest increase throughout the century



In the earlier post I summarized my estimates on the limits to capacity utilization if production is done either with wind or solar power.  Here I will (over)think implication a bit further.  mthOn their own wind and solar power implied strong restrictions on achievable utilization rates. Overbuilding generation capacity (and associated distribution system) could increase utilization rates, but at the expense of ever increasing amount of wasted power and underutilized power lines. Storage could also help, but smoothing out the production profile would require large amount of underutilized storage capacity. There doesn’t seem to be away around this. Low capacity factor of variable power source has cascading effects elsewhere. If not fixed capacity utilization of end users would be strongly constrained and most likely too low to enable profitable business. On the other hand attempts to fix the problem would imply underutilized generators, power lines, and/or storage. Technical developments will not change this since the problem is not due to specific technology or costs.  Are there ways around these problems? Of course…

If you are planning to invest in a new plant producing for example solar panels and you find production to be unprofitable with utilizations rates implied by solar power, your first choice is simply not to invest. If economic preconditions do not exist, production never materializes even if we might find such production desirable or even critically important. Production would either not happen or move to a place where higher utilization rates are possible. Various shades of gray might also exists as they do today especially in the developing world. If production process is such that you could for example store some parts for later use, it might be possible to outsource only those phases which require reliable power elsewhere. Of course, this still opens up possibilities for those not saddled with the same constraints.

Another option is not to rely solely on variable renewables, but to have a fleet of dispatchable generators delivering the power services variable renewables cannot deliver. Today this most likely implies burning fossil fuels, but in principle hydro and nuclear power would work as well. This again implies overbuilding infrastructure and is unlikely to be economically optimal. However this fundamental reliance on existing infrastructure is the order of the day in the developed world.

Visions where variable renewables dominate are aspirational marketing material while on the ground unholy alliance seems to have quietly developed between many renewable and fossil fuel lobbyists. Cozy reliance on fossil fuels enables somewhat more variable renewables to be built before technical limitations become apparent. Supporting this modest buildup (with public money) buys fossil fuel industry social licence as well as removes long term threat of actual decarbonization. Petty about the climate, but the constituency for whom this is actually a priority is weak.  This is welcome also for many politicians who are only too happy to project an appearance of activity (at relatively low cost) while their policies imply changes which have a marginal impact on the actual problem. This relates to deep decarbonization in a same way as “champagne socialism” relates to revolution of the proletariat.

I recently read a very interesting book “Fossil Capital” by Andreas Malm on the history of industrial revolution in the United Kingdom. (Note: book is only worth reading until chapter 12. There the author got tired of thinking.)  Malm focused on the question of why coal and steam engine won over water power in the early decades of the 19th century. Remarkably coal did not win because water resource would have been insufficient. There was still plenty of untapped potential in the UK. Also coal did not win because it was cheaper. In fact, mechanical power from steam engines was more costly and many were of the opinion that it was also of worse quality. So what happened?

There were many overlapping reasons. For example, factories followed labour to the cities. In the early 19th century it was already clear from the demographics that labour was to be found in the cities. Water power was dispersed and getting meek labour to run the machines in the middle of nowhere was harder. In fact, owners of water powered factories were relatively more dependent on the apprenticeship system providing them with, what can apparently with some justification be called,  slave (child) labour. Water power was also more variable than steam, which made it even more important to have well behaved labour that would be willing to work long and irregular hours.

However, it turned out labour did not think their position was optimal (go figure) and started to make noise. This resulted in legal (and actually enforced) restrictions on working hours and gradual improvement on workers position. (It also induced technological change that made large number of especially troublesome workers redundant, but let us not talk about that here.) Owners did not of course like these limitations and lobbied against them, but relatively speaking those using steam found it easier to adapt. They could live with the shorter and more regular working week since reliable power could enable high productivity during working hours. Coal became the backbone of british industrial might and the road was opened for more broadly shared economic growth.

So can we learn something from this? I think we can since economic and social arguments for why coal won have not disappeared. If you listen to todays renewables promotion, you will be constantly bombarded with statements about how huge the potential energy resource is and how cheap it is…or is going to be any day now. Might it be a cause for concern that these two reasons were also promoted by water proponents in the 19th century Britain just when coal was taking over? Might there be a risk, we are discussing beside the point? If excessive reliance on variable renewables end up limiting capacity utilization, is there not a similar risk that water power faced in the 19th century? Who bears the cost of lower utilization? Labour? Lower salaries and/or more irregular working hours anyone? Vacations in the winter since solar power produces mainly in the summer?  If push comes to shove and such questions have to be asked, I am quite sure any techno-fetishes we might have, will evaporate.

To me conclusion seems clear. It is unlikely humanity will ever be primarily powered by variable renewables. If fuel etc. costs for dispatchable generators are high compared to the cost of electricity from variable renewables, wind and solar might be economically justified as a part of a more diverse fleet of generators. However, it is also possible that on economic grounds they will remain niche producers whose existence is dependent on subsidies and political good will. Future will tell.

This will probably be a fairly long post mainly summarizing findings from my simple toy model….so proceed at your own peril.  For a while I have been interested in how the properties of the power source affect the end user. For the consumer different power sources deliver very different value, but the public discussion is typically centered (more or less honestly) on costs. I think one issue of great relevance is the capacity utilization and the aim of this post is to record my studies on the matter. In particular I wish to explore the variable power sources such as wind and solar in the context of capacity utilization. My thoughts are in the end closely related to “capacity factor rule” discussed by John Morgan, but I approach the issue from somewhat different angle.

What is a capacity utilization  and why it matters?

Capacity utilization compares realized production with what could be possible. The concept seems to be somewhat fuzzy since theoretically maximum output could be defined in different ways. However, for an advanced economy capacity utilization is high, for example, in EU it is typically higher than 80% with a scary dip during last financial crisis. In an undeveloped country capacity utilization is lower, for example around 55% in Bangladesh. This makes sense, since things like poor infrastructure hamper production that might have otherwise happened. High capacity utilization is needed especially when lots of capital is spent since otherwise production could not cover capital costs. If high capacity utilization cannot be ensured, investments requiring large amounts of capital will not happen (unless one finds someone to pay for the losses).

In a developed economy capacity utlization is not really limited by the power supply. We get power from the plug whenever we need it. Capacity utilization is limited more by things like rising labour costs if one aims for maximum production or perhaps uncertainty on whether or not a buyer can be found for the product. However, our electricity production follows the demand and not all power sources can do that. Some view it desirable that consumers should in fact adjust their consumption according to weather. This raises the question: “How will this limit the capacity utlizations?”

This is a hard question and I can only scratch the surface here. I assume a “machine” or factory that can use certain amount of power and what is produces is proportional to its electricity consumption. I will then either use wind power or solar power as a power source and also add a storage to help even out the power variations. If there is excess power and storage is not full, we fill it. If power supply is lacking, we drain the storage. (I assume 80% round trip efficiency.) How much power machine can use, is a variable. It probably makes no sense for this to be higher than the wind or solar capacity, but if it is reduced utilization rate for the machine can probably be increased. It should be noted that the estimates below do not (of course) use the economists definitions for capacity utilization. This is more likely to give an estimate on the additional limitations on capacity utilization on top of all those other factors that are operating in any case.

So let me quickly summarize what I find…

Figure 2: Wind power source limited capacity utilization as a function of “machine capacity” (i.e. what fraction of power source capacity it can use) and storage (days at average wind production). Wind power data from UK 2013.

Figure 3: same as Figure 1, but using solar power as a source. (Production data from Germany 2015.)

Figures 2 and 3 show my rough estimates for the “capacity utilization” as a function of machine capacity and amount of storage (hours of average power production). If machine capacity is equal to the capacity of the power source, capacity utlization is limited by the capacity factor of the power source. As machine capacity is reduced and/or storage is added capacity utilization can increase. However it is very hard to get to a situation where power source would not be a factor substantially limiting the overall capacity utilization.

In terms of capacity utilization wind power tends to beat solar power which has strong seasonal production profile. Removing that is hard since it would require massive amounts of seasonal storage which would (by definition) be used only by about once a year.

As machine capacity is reduced, the “factory”can run at a higher capacity utilization, but then certain fraction of the produced power will be wasted although waste can be reduced somewhat by storage. If we aim for high capacity utilization, wasted fraction can unfortunately be substantial. The unit cost of useful energy will rise with increasing waste.

Figure 4: Fraction of wasted wind output.

Figure 5: Fraction of wasted solar output. (Once daily variation is covered it is very hard to change things by adding even more storage.)

Waste can be reduced with storage, but then the question arises that how efficiently this storage is being utilized? Figures 6 and 7 illustrates this. If we add so much storage that capacity utilization is high and amount of wasted power is low, we tend to have a large amount of under utilized storage capacity lying around. Storage that is combined with solar power tends to be more efficiently used because of regular daily variation.

Figure 6: How efficiently storage is being utilized with wind power. (Here the scale is more arbitrary. I assumed full utilization amounts to one full cycle a day.)

Figure 7: Same as figure 5, but with solar power.

I suspect that these estimates are in fact too optimistic. If I choose a point from figure 2 with relatively high “capacity utilization”, the power supply for the machine is still quite erratic as seen in Figure 8.

Figure 8: Example power input to the machines when machines powered by wind had a capacity of 0.26 of wind capacity and system had 36 hours of storage at average wind output. Still a mess.

Maybe there are processes that do not mind this, but there are  also plenty of industrial processes where steady power supply is needed and where abrupt power cuts will undermine the economics of the plant. (It would be interesting to have real world examples of production economics as one changes between power sources. Do you know any? I suspect that current way of delivering power to industries in developed economies is close to optimal for their needs.)

I think I will stop here and discuss later what I think this will imply. Main point here is that nature of the power source will affect the capacity utilization and have economic consequences that are not accounted for when myopically computing the “cost” of electricity for the power sources.

I have earlier discussed Deutche Bank and its less than stellar predictions. Due to recent news I will return to the topic briefly. Deutsche Banks reports and predictions on solar power have been breathlessly hyped in the renewables marketing web sites and links from there have polluted the discussion more broadly. It should be common sense that investment bankers should not be used as a credible source let alone on a matter which requires long term thinking extending over a century. Unfortunately, such common sense seems to be in short supply.

So now solar company SunEdison is on the brink of collapse. How did that happen when only a year ago Deutsche Bank was encouraging everyone to buy this company that was bound to be part of imminent solar revolution?

Deutsche Bank recommendations early 2015

I guess it happened the same way bubbles always pop. We had analysts optimistically predicting wonderful things… just open your wallets quickly and you can get part of the fun. That paper rubish banks had created had to be sold somewhere and surely you should do it to save the planet AND for profit. Here is a funny chart for those who believed the gospel.

Nailed it

All the while company imploded Deutsche Bank was recommending “buy”. This was going on still 4 weeks ago.

“Buy Buy Buy! God dammit, why aren’t you buying!” Few weeks ago. (Poor guy. The site)

Here is are few samples how things unfolded with scant warnings about risks. Sad really.

Screen Shot 2016-01-02 at 18.53.51

Mark Jacobson brought to you by Shell.

Finns have traditionally had a low self-esteem and have been very concerned what others think of them. Running into Mark Jacobsons 100% RES energy scenarios gave me a rare chance to come in touch with my inner Finn. For this I wish to thank him. His “visions” are visibly marketed online for example at website and National Geographic with a help from none other than Shell. (For the actual papers and associated pile of excel files see here.)  Reading his papers and excel files made me wonder, what have we done to deserve his wrath?

Let me elaborate. As a backbone of our energy system Mark Jacobson and his accomplices grant Finland 29 GW capacity of onshore windpower, 27 GW offshore, and almost 50 GW of photovoltaics. For reference notice that our maximum electricity demand is around 14GW in the winter and 9 GW in the summer. Total energy consumption is somewhat less than 400 TWh. In size we are about 1% of EU which has around 90GW of photovoltaics installed. So according to Mark on a windy sunny day production could be more than 10 times our demand and around 7 times the maximum (winter) demand. Our installed PV capacity would be comparable to whole PV capacity in EU today which has, after all, spent around 10 years constructing it. This all seems a bit intimidating.

Considering how off-scale this is it is noticeable that Jacobson spends very little time  spelling out the details of how exactly are we supposed to cope with implied massive swings in production. From his excel file I cannot find details on what he assumed for our grid and how much his assumptions end up costing. He also says there won’t be any new hydropower (we have 3.2 GW), but there might be pumped hydro storage. They tell us “…we restrict our calculations to assume each country can generate all of its annually-averaged power independently of other countries, since ultimately this goal may reduce international conflict.” So that water will be sloshing somewhere in Finland since otherwise we might invade Sweden and Norway (and Russia while we are at it). Makes sense. If I read this correctly our hydropower is supposed to be configured in such a way that it pumps water upstream at massively higher powers than downstream. Somehow I feel we need a 2nd opinion from someone with actual competence in engineering. (Maybe Mark meant that we were supposed to use hydrogen storage somehow? Well, no he didn’t. According to him just 1.24 GW, out of total average demand  close to 30 GW, or about half of the transport demand was diverted to electrolysis. Something very weird is happening behind the scenes and I have a nagging suspicion science fiction is involved.) Also note that our electricity demand is never less than about 6GW so potentially we are supposed to shut down the country for Mark. No problem!

Furthermore, why doesn’t Jacobson tell us where  those mythical pumped hydro storages are? If you have a look at the topographic map of Finland, you will quickly realize why this is a critical question.

We are a mountainous country…by dutch standards.

Finland is a flat country. If you drain our biggest lake Saimaa (the funny shaped water area between Lappeenranta and Joensuu) you might get around 5 TWh of energy. It feels unnecessary to point out that this cannot be done. Furthermore, you cannot even pump all that much water into the lakes since that would flood the cities, summer cottages, roads, and railways next to the lakes. Jacobson should probably add an army of goons into his employment figures to ensure the continuing happiness of our sad little country when his plan is being implemented.

Jacobson also suggests we get about 20% of our energy needs from photovoltaics. This made me laugh. Here is a picture from the moment when my power consumption for 2015 peaked.

20% of energy from photovoltaics.

20% of energy from photovoltaics. Sure Mark! Whatever you say

Picture is taken towards a calm lake (very little wind) when I was leaving a sauna during Christmas. Since lake was freezing the scenery was pretty, but too few photons of right energy hit my phone. Sauna was powered by bioenergy (aka trees) and consumed several tens of kW of power. In the heating stage probably closer to 100kW. (Sauna stove was emitting ridiculous amounts of particulate matter and all sorts of carcinogenic carbage. It was also very enjoyable and I warmly recommend it. We do it with kids.)

Of course a Finn would check the scenario not just for Finland, but also our dear neighbour Sweden. Sweden is about twice our size and has per capita GDP that is roughly comparable to ours. To remind you, according to Jacobson we are supposed to get around 20% of our energy from photovoltaics. Sweden on the other hand is inflicted just with around 1% share.


Mark lets us play on our strengths -- sunshine!

Mark lets us play on our strengths — sunshine!

According to Jacobson upfront capital costs for the electricity generators alone would be more than $225 billion. This is about the same as our GDP. What about Sweden? In Jacobson’s scheme Sweden will pay less than $170 billion in upfront investment costs. Less than us even though they are twice our size. Thanks Mark. What is it? IKEA? Nobel committee? ABBA?

In Jacobson’s vision employment in our energy sector grows from about 38000 to 130000. Doesn’t this mean massive productivity reduction in our energy sector? Isn’t that a bad thing?  In the topsy-turvy world of 100% RES discussions this is of course not so. Jacobson instead talks as if we are winning by spending more.  By inverting the logic of productivity increases that I suspect pretty much all economists (whether on the left or right) agree on, he talks of our $8.15 billion/year “earnings due to jobs” as if we are winning. Sweden would end up employing only about half what our energy sector would do (quarter on per capita basis) and they would get just 0.96 billion in earnings due to jobs. Take that Sweden!

How does Jacobson actually end up with the claim that his vision would make any economic sense? He gets this basically by estimating body counts from PM 2.5 emissions and then multiplying this by “the statistical value of life”. In this way he claims that in 2050 Finland emissions would kill 600-6000 people and cost us maybe more than $100 billion or about 30% of our GDP every year. Wow! This is crazy on steroids. First of all I think this is inappropriate use of the concept “statistical value of life” and 2nd it doesn’t pass the sanity check. Here PM emissions have declined drastically in past decades thanks to cleaner fuels, filters, centralized power plants replacing small scale burning etc. What am I supposed to learn from Jacobson’s figures? That in 80s when emissions were much higher, we lost basically all our GDP because of pollution? Also, is there someone who has a life insurance for 17 million. Isn’t maybe 100000-200000 more typical…1% of their claim? Jacobson and his friends assign pollution problems to the energy system as a whole and ignore that lot of it here is actually caused by small scale burning of bioenergy. They also deny the existence of alternative ways to address pollution concerns. History already tells they are incorrect in this assumption.

Small particle emissions from Finnish transport sector. Green for road transport, blue for water. (Lipasto, VTT)

In summary, thanks for dropping by Mark! Now don’t let the door hit you on the way out.

P.S. Jacobson’s work is a treasure trove of nonsense and since I seem to like poking on carbage, I will probably return to it later. I name this post with “Part 1” for that reason.

Added 4.1.2016: I realized that Jacobson’s plan also assumes we spend about $12 billion on wave devices (almost 2GW capacity). It is a wonderful source of energy especially on the time of the year we need energy most. (More on this theme from the article by Soomere and Eelsalu. I thank @alexharv074 for the link.)


Does that white stuff matter? Photocredit La Brionnaise

One of the more absurd phenomena in energy discussions is the reverence accorded to Wallstreet. If an investment bank says something nice about renewables this is treated as uniquely credible message. That it is often people with left wing sympathies who do this, makes the phenomenon even more absurd. This is how the process works. Bankers write non-peer-reviewed report on something. Then copy-pasters in environmental/renewables media credulously repeat what was said (minus conflicts of interests statements) without ever linking to the original report. Here is a recent example from UBS and Citigroup (also in Guardian). If you read the report there is not much. Strong claims are backed up mainly by hot air and some comparisons are so absurd as to be comical. For example, one talking point was that electric vehicle is already cost competitive  with a conventional car. What was not highlighted by the bankers, was that their “conventional car” was Audi A7, “an Audi limo for those who like to drive as well as waft about in luxury”

In recent years some of these reports have been written by Vishal Shah for the Deutsche Bank. He has told us, for example, how “solar will Dominate World Energy Supply in Just 15 Years” or in 2014 how second solar gold-rush was imminent.  Both reports had “important conflict disclosures” and readers were encouraged to read them elsewhere. (They disclose important financial stakes in companies whose stocks they recommend.)

But who is Vishal Shah? Googling him reveals that before being hired by Deutsche he contributed to the success of Lehman Brothers (and Barclays). Being a financial analyst he has left behind a trail of recommendations which help us to understand how clear his crystal ball actually is.

  • In 2008 Shah predicted that polysilicon prices will increase by another 20%. As if on cue, prices collapsed.
  • He promoted Evergreen solar stocks. The company promptly drifted to bankruptcy. Evergreen
  • He has been cheerleading First solar, whose stock collapsed. Firstsolar
  • He has also been cheerleading Suntech Power, which (this is getting boring isn’t it?) went bankrupt. Suntech
  • When the second gold rush was supposed to begin, solar stocks proceeded to drop substantially. Goldrush_begins

His ranking among the analysts is less than stellar. Poor guy. I don’t in fact think that Shah is worse than other analysts. He has the misfortune to work in a field that has been a lousy investment. He came to my sights only because he happens to generate very visible nonsense on a topic that I follow rather closely. It is a cause for concern when people base their faith on fighting complex long term challenges such as climate change on analysts whose work is, after all, about selling financial instruments during the next quarter. These people do not have a special crystal ball that makes them any wiser than random person from the street.
Photo 24.5.2015 8.57.20

I glanced at the IEA report “Energy technology perspectives 2012”. (There is also a 2015 version, but I didn’t have access to that. Annoyingly IEA charges dearly for these reports so that even though they are commonly referred to in discussions, they are not widely available.) In their baseline 2DS scenario IEA estimates cumulative saving (savings in fuel minus investment costs) over 6DS scenario of 26 trillion US dollars by 2050. Interestingly enough they also have a “high” nuclear scenario where they tolerate more nuclear power than in the baseline. In this scenario the savings are largest, 27.9 trillion. Strangely enough this result was buried to the page 384 of the report. Wouldn’t it have been useful to highlight this since there are plenty of people and (believe it or not) politicians who don’t know this? After all this ignorance might make them promote policies that are counter productive in fighting climate change.

IEA_ETP2012_TableOfScen 2015-06-02 12:42:18_mod

We can also look at the required investment level to follow the 2DS scenario. Here IEA assumes large cost reductions for renewable energy sources. This might or might not happen, but let us just accept this for now. I highlight some relevant numbers from the report in the following table.

IEA_ETP2012_NeededInvestments2015-06-02 12:34:38

Source Investment 2030-2050 per year (billion) Production 2050 (TWh) TWh/billion
Nuclear 119 7918 66.5
Wind 167 6145 36.8
Solar 232 5988 25.8
Wind+solar 399 12133 30.4


As you can see, even though IEA has baked in massive cost reductions assumptions into solar and wind by 2050, they still deliver less than half as much electricity per investment than nuclear (for which IEA didn’t seem to assume learning effects). IEA 2DS baseline is not a cost minimizing scenario, but presumably reflects sufficiently conventional wisdom that authors believe is more palatable for IEA funders.

What would happen if we were to simply divert investments spent from more costly decarbonization options to nuclear? That 399 billion for wind and solar would then enable about 14000 TWh/year more carbon free electricity than the 2DS baseline. This would be enough to eliminate coal, coal+CCS, natural gas, natural gas+CCS, biomass+waste, and biomass+CCS from the electricity mix at 2050 with more than 1000 TWh left over. As these sources of electricity disappear, more than 100 billion a year is also saved in investment costs and lots more in fuel costs. Based on the difference between IEA 4DS and 2DS scenarios, I estimate around 20 trillion additional cumulative savings in fuel costs. Not bad, I would say given the speculative nature of CCS technology, environmental and social impacts of bioenergy schemes, and the need to decarbonize also other sectors than electricity production. (Incidentally, it tells something of the absurdity of current energy discussions, that many celebrate large investments as a good thing. It doesn’t seem to matter what the investment actually buys. More expensive the better, because that means more investment and larger business opportunities in “cleantech”.)

Do I think this will happen in the near future? Of course I don’t. If there would be a wartime-like urgency, who knows, but as it stands such scale up is not going to happen. However, even if unrealistic this option is MORE realistic than the renewables-only party line. It is more realistic economically, technically, and in terms of material limitations. Since it is not going to happen, (as I have said many times before) we can look forward to much more than 2 degrees warming.

In its latest assessment report IPCC concluded that in order to get climate change under control world needs massive expansion of nuclear power, renewables, energy efficiency, and CCS. I am a numbers guy and therefore I was delighted when I found a useful database for many of the mitigation scenarios IPCC relied on in its latest report. There is a database for the scenarios and additional information and assumptions used on many scenarios can be found in another database. I found this very interesting since articles reporting on the scenarios often explain the underlying assumptions of the models poorly. I will focus now on how the modellers approached nuclear power. I didn’t have the patience to go through all scenarios and I focused on those with 450ppm CO2 target that contained all technologies optimally (allegedly). I found that quite a few modellers dealt with nuclear power in a way that left me wondering if their modelling is simply poorly disguised ideological propaganda.

Some main approaches used to influence how well nuclear power does in the models relative to variable renewables (wind and solar):

  1. In many models nuclear capacity increases massively. Hundreds and hundreds of reactors are constructed, but amazingly nobody learns anything! Capital costs for nuclear power are typically kept almost constant throughout the decarbonization pathways. On the other hand learning effects and technological evolution are assumed for other energy sources. For wind and solar power these are often assumed to be very dramatic and there are learning effects even for fossil fuels. So this tough love only seems to apply to nuclear power.
  2. Many models assume large cost reductions for wind and solar. In the end, this is not much more than a wishful guess.
  3. Some models assume anomalously large capacity factors for wind and solar. See for example, “Message Ampere2-450-FullTech-OPT” scenario. Capacity factors for wind are almost 40% while for solar power they use about 25-31% over the course of the century. Since real figures are more like half of the assumed figures, the model drastically underestimates the costs for wind and solar. (IMACLIM scenarios seem to do the same)
  4.  Some models (IMACLIM in particular) assume very low capacity factor for nuclear.  “IMACLIM Ampere2-450-FullTech-OPT” has a nuclear capacity factor of just 45% in 2100 while for wind and solar they have 36% and 38% respectively! This doesn’t just roughly double the cost of nuclear in these models, but also underestimates the costs for wind and solar.
  5. Some models (REMIND and MERGE-ETL) postulate a world running out of uranium together with no technology development for nuclear. This “peak uranium” then limits the role nuclear power plays in decarbonization.

Figure 1: Nuclear power in Remind Ampere2-450-FullTech-OPT scenario. Massive increase and then…

Let me discuss the sillyness of the last trick in more detail. Figure 1 shows what REMIND scenario got for nuclear power when all technologies were used “optimally”.  So massive increase in nuclear power until middle of the century and then rapid decline. Decline is caused by uranium supplies running out as soon as light water reactors with once-through fuel cycle have used 23 million tons of uranium. This is very strange for several reasons.

First, this number doesn’t seem to bear any clear connection to known uranium resources which are about third of this figure. Modellers probably felt that using known resources as an upper limit would have been too stupid to pass the laugh test.

Second, mineral resources have a habit of increasing together with demand since increasing demand stimulates increasing investment in exploration and technology development.  In the past one hundred years copper production has increased by an order of magnitude. All this time world has been “running out” of copper in about 40 years. Uranium is not especially rare element and there is no reason to believe we are running out of it anymore than we have for other metals such as tin which has about the same crustal abundance.

Third, from where does the assumption of no technology development come from? Wasn’t this supposed to be a scenario where all technologies are allowed? For nuclear power technologies that that improve the fuel efficiency by about two orders of magnitude are already known.

Fourth, why is there resource constraint only for nuclear power? The resource constraints are more severe for wind and solar power (and for bioenergy). In Figure 2 I show an image I picked up from a european study on critical metals for energy technologies. The elements with greatest supply risks are used in the construction of wind and solar power. (By the way, the only nuclear related element on the list is the low risk hafnium for control rods.) Figure 3 I picked up from a fairly recent Alonso et al. paper. Authors estimated that dysprosium (used in magnets) demand in renewables heavy mitigation scenarios is expected to be a whopping 2600% higher than projected supply already in 2035!


Figure 2: Critical metals for European “strategic energy technologies” according to European commission Joint research centre study.

Figure 3: Expected demand and supply for Dysprosium according to Alonso et al.

Figure 3: Expected demand and supply for dysprosium according to Alonso et al. (2012).

What would happen if we were to apply modellers approach for renewables? Let us just take silver as an example. Silver reserves are estimated at about 530000 tons. Let us assume that “real” resource is 4 times this (remember uranium resource was set at 3 times the known reserves) and that half of this can be used for photovoltaics. There are after all other uses for silver as well. Since 1GW of solar power requires about 80 tons of silver, this means that at maximum we can have about 13TW of solar capacity as opposed to almost 90TW cumulative capacity REMIND modellers extrapolated. Instead of being the largest contributor to the primary energy supply its contribution would fall into 5-10% range. The amount of silver required to construct the solar power in REMIND FullTech scenario is about 13 times larger than the estimated global silver reserves. Now can there be ways around these constraints? Probably there are and maybe we could use less silver, but using substitutes might imply higher costs and worse performance and furthermore, if one was not permitted to use already demonstrated technologies for nuclear power why should imaginary advances be permitted for other alternatives?

What might we get if we remove this silly constraint from the model? Obviously I cannot repeat the exercise with the tools I have available, but we can get a rough estimate. Lets take the growth rate (4.8%) for nuclear power REMIND modellers established between 2020-2050 and just let it grow with the same rate until the end of the century. This is not extraordinary in the context of this model since for wind+solar the growth rate through the century was 7.6% even though capital costs are such the nuclear power seems to have a lower levelized cost of energy (5% discount) throughout the decarbonization pathway. I show the result in Figure 4. Nuclear power would end up dominating the energy supply.

I have a feeling that resource constraint was introduced specifically for this reason. Modellers first did their calculations without the constraint and ended up with a result that they found distasteful. They did not want to go on record with the scenario that might “rock the boat” or give people funny ideas. By introducing the resource limitation for nuclear power they could clip its wings and keep it supposedly as an option while limiting its role to the margin. In fact that strange 23 mton uranium resource limit seems to suggest that over the century LWR:s cannot produce more than maybe around 5% of the primary energy. I suspect that modellers worked backwards and set the resource limitation based on the maximum share of the energy supply they were ready to grant for nuclear power. Not cool.

Figure 4: There, I fixed it!

Figure 4: There, I fixed it!

Then there is PRIMES…sigh. This is a model I encountered few years ago as I was reading EU:s 2050 energy strategy. I remember glancing at the referee report and being troubled by the brief remark on page 6. Referee had asked about rather optimistic cost assumptions to which response was that if capital costs for wind are set higher then the future learning curve can be steeper. To me this suggested that modellers were perhaps fitting model to the fantasy. In the AMPERE database PRIMES scenarios for EU are also included. I was naturally most interested in the Ampere5-Decarb-AllOptions scenario which according to authors is a scenario “with all technological decarbonisation options available and used according to cost optimality; this scenario provides the least cost decarbonisation pathway for the EU.” Sounds interesting! However, as you look at the actual results you notice something weird. The capital costs assumed are such that nuclear (again) has the lowest LCOE throughout the decarbonization pathway. Despite this modellers claim that nuclear generation in EU will decline by 20% by 2050. How is this even possible?

Then I noticed a strange footnote on page 15: “PRIMES assumes that nuclear development has been significantly affected in the aftermath of the nuclear accident in Fukushima in March 2011. Both PRIMES and TIMES-PanEu impose national constraints regarding nuclear, such as countries’ decisions not to use nuclear power at all…” Please tell me that I am reading this wrong. They didn’t just exclude nuclear power from large parts of EU in their “all options” scenario for political reasons and then sell it as the cost optimal one?

I have now outlined several ways in which scenario modellers seem to suppress nuclear power from their reference scenarios where all options and technologies are supposedly on the table. This has also consequences for the other scenarios and comparisons between them. Since modellers suppressed nuclear power already in “the tech neutral” scenarios adding additional anti-nuclear policy, can be presented as not really having major cost consequences.

Figure 2: The box on the left has nuclear power in it and the box on the right had it removed. Amazingly it looks almost the same as the other empty box!

Figure 2: The empty box on the left has nuclear power in it and the box on the right had it removed. Amazingly it looks almost the same as the other empty box!

Since I am a bad boy I will conclude with some rough estimates on what would it take to replace (gasp!) solar and wind power at the end of the model scenarios with nuclear power that generates the same amount of electricity. I simply estimate the required nuclear capacity (90% CF) and use modellers assumptions about capital costs. Required yearly outlay is roughly total capital required divided by the lifetime of the plant. I will use 30 year lifetime for wind and solar and 60 years for nuclear. (Numbers are in billions of 2005$…I think.)

Model Wind+solar capital Nuclear capital (Wind+solar)/year Nuclear/year
Remind 450-FullTech-OPT 74540 62753 2485 1046
Message 450-FullTech-OPT 40620 64150 1354 1070
IMACLIM 450-FullTech-OPT 5680 5765 189 96
Primes Decarb-AllOptions (EU) 1430 826 48 14
Primes HIEFF-NoCCS-NoNUKE (EU) 1555 900 52 15

In all models the required yearly outlay (at 2100 or 2050 for PRIMES) for energy supply is dramatically lower if we replace wind and solar capacity with nuclear power. This despite the fact that MESSAGE and IMACLIM assumed unrealistically high capacity factors for variable renewables. It is remarkable than even though this kind of chicanery was going on behind many models, IPCC still ended up concluding that nuclear power must expand massively. This is perhaps partly because not all scenario builders were intellectually dishonest about this issue and some models ended up, for example, with ten fold increases in nuclear capacity. On the other hand I am afraid that all 450ppm scenarios are utterly unrealistic….and don’t get me started on their absurd bioenergy projections.

P.S. I spent some time copying the data I was interested in from the database. Interface seems a bit uncomfortable for that. Here is a link to some of the data I extracted.

P.P.S.  For laughs you might want to check IMACLIM model with 550 ppm goal and CCS excluded. Since the original one was very strongly dependent on CCS one would imagine that ruling it out would have interesting consequences for the energy mix. See what modelers assumed for the capital costs of nuclear here to suppress that out of control (critical?) nuclear growth early in the century.



Note added 6.10.2019: It would seem that the capital cost data for the AR5 scenarios has been removed from the database. At least I cannot find it anymore. Can someone explain where is it now?

In case you have missed it, there is apparently amazing energy revolution going on in Germany. Photovoltaics are an in integral part of the associated hype. I checked the rates of monthly installations.

Figure 1: Monthly installations of PV in Germany 2009-2014.

Figure 1: Monthly installations of PV in Germany 2009-2014.

Installations increased rapidly from the early 2009. What caused this increase? I might of course be wrong (I don’t think I am), but this increase coincides quite nicely with the collapse in the German share of the photovoltaics industry and increasing Chinese dominance in the marketplace. Germans had adjusted their feed in tariffs based on German manufacturing costs. This attracted Chinese who could produce same thing far more cheaply and gave rise to investment bubble in Germany. Subsidies were sold  as buying Germans a large share of an exponentially increasing export market. Instead German producers of photovoltaics panels collapsed. Strangely enough silence on this has been deafening and and the same argument is used to sell similar policies in other countries as if nothing happened. (Does anyone know a country were subsidies are NOT justified by capturing export markets?)

Figure 2: Market shares of photovoltaic cells

What causes those spikes in installation rates? As has been demonstrated time and time again, installations are driven by subsidies and they tend to peak just when some form of subsidy is about to expire. Sure enough, if I check what has happened to feed-in tariffs in Germany I find a clear correlation with installation rates and FiT changes (see Figure 3).

Figure 3: Fractional change in the Feed in Tariffs

Figure 3: Fractional change in the Feed in Tariffs

Since the monthly data is more noisy I finally show the results over half a year periods. It is quite interesting that decrease in installations since the start of the Energiewende buzz has been exponential (to a good accuracy) with a half-life of about a year. The current rate of installations with 25 year lifetime, implies around 50GW of solar capacity which translates to less than 10% of German electricity consumption. We are saved!

Figure 4: Installations over half a year periods. For your convenience I makrk the start of the Energiewende hype with an arrow.

Figure 4: Installations over half a year periods. For your convenience I mark the start of the Energiewende hype with an arrow.

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