How a recent attack on 100% renewable models might end the trench warfare and benefit our climate

Or why bickering over facts is a step in the right direction

Thursday evening (July 27, 2023) Seaver Wang of the Breakthrough Institute published an attack on 100% renewable papers and took specific aim at the group at LUT University in Finland lead by prof Christian Breyer. The attack states 100% RE models are “bunk” because they use unrealistically low prices for renewable energy and are overly simplistic.

My rebuttal to Wang’s attack shows Wang’s criticism contains errors and applies to most energy models (not just those from LUT or 100% Renewables research). But I had a very respectful and honest exchange with both Wang and prof Breyer before publishing this text that makes me hopeful. I think the attack stresses that ecomodernists and renewable energy (RE) proponents increasingly have a shared reality which may enable an evidence-based debate instead of mud-slinging ad-hominems. The next step is joining forces to provide the world with more progressive scenarios for tackling climate change. (What can I say: I’m an optimist.)

The article is built up like this:

  • Introduction of both sides: who are they?
    Full disclosure: I like Seaver Wang and was approached to read the first draft of his attack but I make 100% renewable models at the Eindhoven University of Technology and have published on this with prof Christian Breyer. I sent the draft of this paper to both of them and incorporated their feedback.
  • What are the criticisms and what is the defense?
    I will show the criticism is flawed because it contains errors, applies to most energy models (not just those from LUT or 100% RE), and doesn’t help new nuclear.
  • Why advances in modelling can lead to an end to trench warfare around renewables and nuclear.
    The spectacular cost decreases in renewable technologies like solar photovoltaics (PV), wind power and batteries needed more advanced models that could deal with intermittency to show their potential. But nuclear fits into these models just fine.
  • How ecomodernists and the 100% RE community can come together.
    This evidence based attack is possible because the new models created a shared reality for both the ecomodernists and the 100% RE community. So instead of mudslinging and ad-hominems we can focus on science, which makes the debate more constructive. And together both camps could help to provide the world with positive, doable and scientifically proven scenarios to combat climate change.

The 100% RE community is growing

When we talk about 100% renewable papers, we mean papers that make energy systems work without any fossil or nuclear fuel. Not just electricity but all energy. You might argue (as Wang does) that it is just wrong to take nuclear off the table. But the 100% RE community will reply that they simply show the previously unthinkable is possible and cost-effective and that this in itself is important news and gives society a wider set of options (next to fossil fuels and nuclear).

I co-authored a paper (prof Breyer was lead author) showing the community making 100% RE energy models is growing quickly and wrote a thread about it here. The five leading research teams in 100% RE systems research and several key topical experts authored that 100% RE community paper.

As you can see the field is young. I would place the first real 100% RE model for Europe at 2005 and for the US at 2011. Core methodological improvements during the 2000s enabled solid research in the 2010s and forms the evidence basis as of today, while methods, data and computational improvements are continuously improving.

But as you can see the field is growing fast (at around 30% per year) and there where almost 150 papers in 2021 alone. Most importantly it’s not just Jacobson (in the US) or Lund or Breyer (in the EU) anymore. In total there are now more than 1500 authors and over a dozen serious modeling groups, several of them with more than 10 years of experience in the field.

Prof Christian Breyer’s group has published the most 100% renewable papers and he might also be the most mainstream as the IPCC report cited over 30 of his papers. The two other leading 100% RE teams (in terms of number of publications and citations) are lead by prof Mark Jacobson and prof Henrik Lund. They all have their own modelling environment but they cooperate on some papers. I know Christian as soft spoken and with an aversion to conflict, especially when it’s uncivilised. He told me he actively decided not to be against something but for something and that his papers show the various facets of a potential future, based on highest sustainability standards. For him that means avoiding fossil fuels (CO2 emissions, air pollution), bioenergy based on energy crops (biodiversity, food), hydropower (biodiversity), and nuclear power (cost, risk, proliferation). Regarding claims that his work is being used by activists, prof Breyer emphasized that he works with all stakeholders interested in very high shares of renewables, from NGOs, to companies, to governmental bodies, to political parties. He was extremely unpleasantly surprised by the attack that was just published by Wang and sees it as an attempt to smear him personally, as a leading representative of the 100% RE community. He considers the fact that he wasn’t able to correct it for errors beforehand as a sign of bad faith. His conclusion is based on the simple fact that the last two years of publications had been ignored in the analysis and that this sloppy working style led to massively erroneous conclusions. Given the massive attack such low quality standards are not acceptable, in the view of prof Breyer.

The Breakthrough Institute and ecomodernism at large is changing

You might know the BTI from the Ecomodernist manifesto that I would summarise as “Developing in harmony with nature is possible through technological innovation.” I do like that overall perspective and Christian Breyer told me that he considers this the core of his research.

To be honest I think co-founder (and celebrity) Michael Shellenberger is… let’s say the opposite of a sane, objective and evidence-based scientist. And in my opinion ecomodernism/TBI used to be simplistically in favour of all things nuclear and against solar and wind (often more so than against fossil fuels). Many still characterise the BTI as a nuclear lobby group to me.

But I think this is overly simplistic. As Shellenberger became more extreme the BTI has distanced itself from him (he is also no longer a member) and Seaver assured me that the BTI is no longer opposed to solar and wind. People like climate scientist Zeke Hausfather (now at Stripe but still a senior fellow) and “oceanographer turned solution seeker” Seaver Wang are giving the BTI a much more “palatable” character for people like me since they like solar and wind and like all ecomodernists they are focused on showing how we can solve the climate crisis instead of being stuck in doomerism.

And I’ve personally become more entwined with the ecomodernist movement because I want to focus more on technological solutions in food that allow us to bypass farm animals and free up most agricultural land for nature. (Agriculture takes up 50% of habitable land while other human activities take up just 1 or 2 percent.) Here the ecomodernist force is strong, also within the BTI.

Over the course of writing the attack and this rebuttal I’ve come to know Seaver Wang a bit better as well and I think he’s as passionate, honest, and open to learning as they come. I picture prof Breyer and Wang sitting at a bar and Wang pointing his finger at prof Breyer and saying: “You can’t be sure that 100% RE provides people in emerging economies with all the options they need to climb out of the poverty trap and defend themselves against climate change. You should at least let people know that your models are still a work in progress. Because your research will be used to take other options away from them!”.

His message to me has never been that prof Breyer is a bad scientist but that he thinks 100% RE claims aren’t as final as my tweets sometimes make them seem and that people need to be aware of that before they ban options for emerging economies. His emotion is that emerging economies didn’t cause climate change and they need access to all tools in the toolbox. He wants emerging economies to be able to prioritise electrification and adaptation over mitigation. An example he gives that you can probably relate to if you read the novel “Ministry of the Future” is that areas with heat waves should have access to air-conditioning as soon as possible.

Regarding solutions, Wang is interested in a lot. The painting (he made himself) on his twitter profile says a lot: a nuclear powered ship placing offshore wind turbines. He sees solar and wind as the prime movers but dreams about small nuclear reactors being produced on assembly lines. He is fascinated that Allam-cycles (a type of CCS) does so well in Jesse Jenkins models (although he admits to not liking CCS much). And much more. This is clearly someone who doesn’t like excluding options.

Regarding cherry picking Wang claims (and I believe him) that he simply took the papers on Asia because that’s what he focusses on (as he has said since February 2022) from the 100% RE paper that I co-authored and paraded on twitter after he learned people were using the work of prof Breyer to try and phase out nuclear in Asia. He then added Africa at the request from his colleague Dr. Vijaya (former World Bank) who noticed that gas projects in Africa were increasingly opposed by activists arguing Africa could simply leapfrog to renewables. He admits it would have been better to also study papers on Asia and Africa published in the last two years but that that he stuck to the papers in the 100% RE review because that was already 86 papers.

To me the fact that he responded to criticism on Twitter by admitting he made a mistake (that he thinks doesn’t invalidate his analysis, but still), that he has refrained from any ad-hominems, and the honesty of the feedback he gave on this document you are reading now, gives me hope that we can keep/make this discussion civilised and fact-based.

Criticism and defense

Criticism: most renewable studies are done by just one organisation: LUT

Answer: that’s not even remotely true

What bothers me the most is that Wang seems intent on singling out LUT and attacking their model. I can imagine how that feels like a smear campaign against one person. He has taken an area (Asia and Africa) that is new and badly represented. Here LUT is a relatively large player in terms of number of papers. The reason for this is simple: every time he’s given the chance, Christian Breyer mentions that he is intentionally doing less 100% RE research for Europe and North America as other teams are already doing a great job there. But for the two most populous regions in the world, Africa and South(east) Asia, very little research in this field is done. And these regions are the fastest growing ones in the world, with the highest lock-in risks and highest relevance for a successful climate reaction strategy. The composition of his team reflects this focus.

So, I think LUT is simply ahead of the pack here. I think it’s commendable, and not a hook for a “100% RE is just one team” criticism.

This hook becomes even more problematic when we look at the world as a whole (see pic below): Breyer and Bogdanov (first author on various and co-author of many articles in Breyer’s team) are big fish but they only published around 8% of papers in 2021.

This attack rings even more alarm bells in the 100% RE community because it is how many people still disqualify 100% RE in the US. Many people in the US think only prof Mark Z Jacobson makes 100% RE models and they discredit 100% RE with ad-hominem arguments against prof Jacobson or by referring to a rebuttal to one of Jacobson’s first 100% RE studies. In that light it seems prof Christian Breyer is now about to get the same ad-hominem treatment. Wang replied to this that his focus on these papers in Asia and Africa wasn’t cherry picking but just happened to be his research focus (see above under the BTI for stuff that backs up this claim).

Criticism: LUT makes overly optimistic cost inputs for renewables

Answer: they use independent authorative sources and are similar to other groups

This is actually where Wang admits he went wrong: he took predictions for 2030 and labelled them as 2020 and concluded they were nonsense. But if you take them as 2030 values they are pretty mainstream. In his answer Wang still claims that other papers that he read were too optimistic too, but the results are less extreme.

Wang also claims that storage for H2, CH4 and CO2 is not taken into account by LUT for e-fuels production and delivering fuels when needed but in the Africa paper that Wang mentions these costs for storage are included.

More importantly, LUT is always extremely transparent about what their exact assumptions are (more so than most other papers I dare say) and what sources they used. They never simply make these inputs up but always cite authorative sources. See e.g. tweet that I already linked to.

Still, having an argument on inputs and learning for different technologies is a good argument to have. It’s actually what made me get into solar, wind and electric vehicles 15 years ago: if you don’t see their costs as fixed but as a result of learning, you could see they would be less expensive than fossil fuels. I have often said that nuclear misses this dynamic and that only a switch to SMRs could introduce it. I also complain about nuclear assumptions a lot in the sense that you should take into account that most nuclear projects end up being at least twice as expensive as originally budgeted. So by all means: let’s talk costs.

And I would say that Christian Breyer’s team at LUT often picks better authorative sources on wind and solar than most mainstream studies by the way. Maybe because his knowledge on wind and (especially) solar is deeper and more up to date since that is their specialisation. And I don’t have the impression that he is that optimistic. For example: for electrolysers he told me that he decided not to use the lowest cost projections (see IRENA) in order to be more conservative.

There’s one thing Wang and Breyer agree on: renewables will be a huge part of energy in Africa and Asia because they are so cost effective. And prof Breyer points out that authors outside the 100% renewable community come to similar conclusions as his team and gave me two links. This article in Nature shows how renewables dominate if you don’t exclude fossil fuel and nuclear and are otherwise similar to the work of LUT (but less detailed on renewables). And this article in Joule (by economists outside of the 100% RE modeling community) even claims that investing in nuclear is bad for the climate due to costs. So that excluding nuclear doesn’t increase costs is not a fringe position anymore.

P.s. Just before publishing this piece Wang claimed prof Breyer used unduly pessimistic numbers on nuclear with prof Breyer responding (in great detail using lots of references) that it was Wang who used unrealistically positive numbers. And I’m just thinking: “Wouldn’t it be nice if they did some joint factfinding?”

Criticism: LUT inputs don’t take differences between countries into account

Answer: they actually do that to a larger degree than most energy models

If you look at the (hundreds) if IAM studies that the IPCC uses, you will see that they seldomly distinguish costs between countries. If you look at most 100% RE papers and most other papers that make global calculations you will see the same. The reason is simple: it’s a lot of work and often there is no funding for that. So in so far as this criticism is correct it’s not a criticism to LUT but to energy modeling in general that I (and I think prof Breyer) agree with. I think we should get better (open source) databases with prices for energy system components per country that all scientists (and other researchers and policy makers) can easily use, critique, and improve. Ideally this database would also take into account that emerging economies such as India and China bring down costs more than developed nations. As more emerging economies join in this has the potential to reduce prices further. Interesting stuff!

Again, LUT is probably better than average here. For example: if you look at recent LUT papers on Japan, Indonesia, and India you will see that they do take country specific prices, something that is ahead of the curve. It’s a pity Wang didn’t notice or doesn’t mention that. In his response to me he stressed that this wasn’t out of malice: he simply read the Asia and Africa studies cited in the big 100% RE review and that were already 86 papers. (I think we can all relate that if you have to read 86 papers in between projects you sometimes stop looking for more. However, it seems to me that some of the erroneous conclusions in his harsh attack on prof Breyer could have been avoided, had he contacted prof Breyer to let him read the draft of his attack in advance.) Wang told me he agrees not taking country specific numbers is a general problem and not a LUT specific one.

Criticism: the capital costs that LUT uses are too uniform and too low

Answer: that’s not true, and IF it were true it would be detrimental for nuclear and not renewables

The cost of capital (often abbreviated WACC for Weighted Average Cost of Capital) is often higher in developing countries because of increased risks and lack of financial infrastructure and locally available funds. Wang claims the WACC that LUT uses is too low (he worries that this makes the energy transition seems too easy) and should be different for different countries. But if I look at this LUT paper I see a WACC of 12% for Africa, and here they use 11% for India, and here 10% for Indonesia. All this apparently after checking with local organisations. So the claim of Wang is only true for older papers and LUT has since upped it’s game (and I daresay many non-100%RE models still have to follow their lead) which Wang would have known, had he read these papers or contacted prof Breyer.

Moreover this isn’t the “gotcha” that Wang seems to imply. Because if the WACC is too low, it is too low for all sources of energy. And especially in countries where there is less legacy energy system infrastructure that just means that all energy sources get more expensive, not that solar and wind specifically get more expensive.

Finally, if you want to defend nuclear the last thing you want to do is make the WACC higher in your model, because nuclear is extremely capital intensive over a long period, and due to its high perceive project risk (as many projects are aborted halfway through due to cost overruns) their WACC will usually be higher – not lower – than renewable energy.

Criticism: LUT excludes nuclear from analysis

Answer: that is what defines all 100% RE and not an error

This is the heart of the problem. Wang is convinced leaving out nuclear means we disqualify one of the most important sources of low carbon energy. It’s the reason he wants to warn people away from the LUT models that are used by opponents of nuclear energy in Asia.

Here it is clear that his criticism cannot logically be aimed at LUT specifically, because all 100% RE models by definition exclude nuclear.

Prof Breyer told me that for him avoiding nuclear is mainly about cost but he also worries about risks, waste disposal and proliferation. For Africa they compared to a nuclear plus fossil fuel model and it came out much more expensive (see paper here). He said that in recent (not yet published) models they have intentionally unlocked nuclear but due to price considerations it simply “didn’t do anything”. One of the PhDs in my NEONrearch program recently did make a low carbon model for Northern Europe that included nuclear (a contract of the consultancy firm he also works for from the Ministry of Economy and Climate) and he did see a (limited) amount of nuclear but he didn’t take cost overruns into consideration.

For me personally: I don’t expect a lot of nuclear. It’s far less popular than wind and solar (although Wang claims that’s different in Asia), it is very hard to get off the ground, people in heavily polluted cities will die from air pollution for another decade (since nuclear takes longer to build), it can lead to nuclear weapons (see Iran), it’s a magnet for worries about terrorism (look at Ukraine), and most of all it doesn’t get cheaper the way wind and solar do. I will probably include it in models in the future, but more to pre-empt the criticism that I disqualified it than because I expect it to play a significant role.

I do however like Wang’s idea to model keeping them open longer in 100% RE models (and many of the other ideas he mentions in his critique), and I do acknowledge that nuclear needs less space (although not as much as many people claim if you include mining uranium and the safety radius surrounding the power plant), is less visible, and requires less material (although that is not a show stopper for renewables as I showed in this thread).

But who am I? I fervently support any nuclear proponent that want to model it. Go for it! And if you want to combine renewables and nuclear you will find that the 100% RE community has already done most of the heavy lifting. Which leads us to our next chapter.

Advances in modeling and an end to trench warfare

Learning curves to anticipate future prices

The driver that leads to the 100% RE models is undoubtedly the price decrease in renewable technologies that can be projected using learning curves. One of the best articles detailing that is by Way et al. I’ve been using this method for 15 years now and it’s what got me into this field because for me it was clear that it would lead to wind and solar cheaper than fossil fuel.

It goes better with small modular technologies like solar PV, batteries, electrolysers, chips, and phones and slower with technologies that require a few large projects like coal, nuclear and hydro: there is simply less learning if you only try to produce something a couple of times and practice makes perfect.

Incorporating estimates based on learning curves simply gets you much more realistic results than assuming the price doesn’t change. And people who realized this early on got interested in renewable energy.

Finally we have simulations that give 100% RE a fair shot

Hourly modelling

For models that use fossil fuels or nuclear, it isn’t necessary to deal with intermittency. But for wind and solar you have to know what to do when the sun doesn’t shine or the wind doesn’t blow. So you need models for an entire energy system that do hourly modeling for at least a year. IAMs and other traditional energy transition models usually didn’t do that. (I don’t know if there are IAMs with hourly modeling now.) So people like prof Breyer (and me) had to develop models that could do that. I work with grid operators a lot and then the time steps are often 15 minutes.

(Of course there are also models that takes transients into account that can go down to the millisecond level. But these kind of models are only needed at the last step of the process when you are about to order a specific transformer dig up a specific street. The experience in South Australia with the Tesla battery showed that in the millisecond scale batteries are superior to the classical approaches for grid stability, and in future we will have a lot of batteries in the energy system.)

Grid modelling

I already mentioned grid operators. They are becoming increasingly important as more solar and wind means higher loads for the grid. So if you do more detailed models for a certain area you could use models such as I make (here some examples in Dutch) and if you want a model for a larger area you could use models like PyPSA by prof Tom Brown et al. (for Europe) or models like the ones developed by Prof Breyer and Prof Jacobson.

Now you have hourly modeling and a simplified grid! We are on our way to a model to calculate energy systems with. We expect that the mantra will be “electrify everything” and that more and more energy sources will become electric, which makes the grid more important.

Infrastructure costs have to be estimated in these models using estimates per kW of grid upgrade and this can add substantially to the overall system costs.

Demand response and smart charging

A lot of models (especially outside 100% RE but also inside) are bad at estimating demand-response while that can a big impact on system costs. I dream of a future where electric vehicles not only charge at the moments when solar and wind make electricity cheap and the grid isn’t overtaxed (that’s already happening at scale) but where we also use V2G (vehicle to grid) to use electric vehicles as batteries on wheels. That could go a long way towards stabilising daily fluctuations in the grid while giving solar and wind a better price and lowering grid infrastructure costs.

Most models that conclude that electric vehicles will overtax the grid or that daily fluctuations are a problem miss this.

Sector coupling

A lot can be achieved by taking a more integral perspective. E.g. your neighbourhood could have a heat pump that heats a heat buffer in the summer at moments of excess solar power and uses that heat in the winter. Tricks like that are needed in a 100% RE system and if you leave them out the overall system costs are much higher than they would be in reality.


I already sang the praises of smart charging of electric vehicles. But grid batteries and home/business batteries will also play a part to smooth out electricity flows.

This is also the reason why 100% RE models don’t have to model the electricity grid in detail: more batteries means more abilities to take care of transients, voltage peaks, and frequency deviations. You only have to estimate a cost and figure out the exact battery algorithm when you implement the system. I’ve had multiple discussions with electrical engineers (that want to model the grid in excruciating detail) about this but it was never clear how their models would alter my 100% RE estimates. Sometimes you can have too much detail.


PtX stands for power (=electricity) to something else than electricity. Usually the X is some sort of synthetic fuel or synfuel for short. Just like hydrogen has a “hydrogen ladder”, prof Breyer has a “PtX ladder”: heat; clean water; fuels; chemicals; materials; DAC (for negative CO2 emissions); and reforestation. Models that come up with ridiculous estimates for storage costs and resource use because they estimate e.g. a battery that can store a month of energy try to use batteries for seasonal storage. (See my thread here.) That is a big no-no in a model that deals with solar and wind realistically.

Chemical storage is a better option. In practice this first means that you can bridge the seasonal gap by using a fraction of your current natural gas. E.g. 10%. Together with electrification that already eliminates 90% of emissions and could even make the system cheaper. The last 10% or so is harder but this is where synfuels come in. E.g. green hydrogen (green meaning: produced from renewables), methane from green hydrogen and CCS, and gasoline and kerosine from renewables.

This is where the technology is youngest and renewable models need to invest the most. Prof Breyer recently coined the term “Power-to-X Economy” of which the well known “hydrogen economy” is a an important part (with hydrogen as the energy carriers) but renewable energy is the motor.

Just add nuclear

I would say that the previous models are not a threat to nuclear proponents but an opportunity. Energy experts all agree by now that solar and wind will play a prominent role and these models make it easier to model them correctly. Adding nuclear to such models could show that nuclear is a valuable addition. Not just to a traditional energy model but also to one that knows how to handle renewables.

So if I wanted to prove that nuclear was a good option, I would be very happy with 100% RE models. Especially open source ones. (But the most work is coming up with an exact plan of how it will work and that can be copied from papers.)

Again: I don’t expect nuclear will do much. But maybe I’m wrong! Maybe replacing part of the synfuels with nuclear makes the system cheaper. Maybe nuclear will be the preferred option for PtX because it can keep the electrolysis running almost 24/7. I honestly don’t know yet and especially if we manage to make new nuclear better (e.g. an inherently safe thorium SMR) I for one would be all for it.

Yes we can: ecomodernism and 100% RE can go hand in hand

So there you have it. I think I’ve shown the attack by Wang on prof Breyer missed the mark, but at least it’s an example of an evidence-based discussion using a shared reality. And I think that’s new, especially in the US where ad-hominems and ignoring of each other was prevalent (at least in my twitter feed). Prof Breyer still thinks this personal attack was uncalled for and contains error-prone cherry-picking that ignores his recent work of the last two years and that Wang could have avoided that by simply contacting him. But Wang convinced me that it wasn’t out of malice and that his motive is not to smear people but to keep options in emerging economies open. Above all, I am happy that Wang took the time to study papers written by prof Breyer instead of dismissing him out of hand.

In my ideal world ecomodernists and the 100% RE community would show more mutual tolerance and would join forces with room for different perspectives and a fair competition of ideas. And we certainly aren’t there yet. But compared to ad-hominems and dismissing each other out of hand, bickering over facts is a step in the right direction.

Updates to the article

August 1st: at the request of Seaver Wang I included the fact that Michael Shellenberger no longer part of the BTI.


3 responses to “How a recent attack on 100% renewable models might end the trench warfare and benefit our climate”

  1. wim fleuren Avatar
    wim fleuren

    TLDR: The whole ecosystem of expertise around LUT, makes it neccesary that LUT updates its model to 15 min data (especially so for dense high powered regions, like all countries around the North Sea) so country or region specific models would be next step.
    Adding Nuclear to this model would be least effort.

    1> we assume a lot of prices. We need real world data e.g. offshore wind+connectors+cables?
    2> If optimising is a goal, then it’s neccesary include NE, also CCS.
    3> I doubt the continuous exponential downward price curve of RE. E.g it’s not cell price alone, its cables, frames, manhours. And even cells have a bottom price.
    4> robustness of an electricity system is hard to grasp in a price
    5> land use and public acceptenace is a key exponent, without a price
    6> production price is not the same as the price we pay
    7> infrastructure, firming costs are widely unknown
    8> resources and manpower are an issue
    9> 2050 is not the end of our zeal. even 2100 is not> RE needs to be repowered more often than NE. this has major cost/benefit consequences, long term
    10> what is the real price of PtX? Incl. full cycle losses (The hydrogen Cycle is extremely vulnerable for losses) even LiIon is only 75% in winter.

    Until 2030 /35 all efferts are okay, at wharever cost.
    RE is the right way to go, right now there is enough robust Fossil/Hydro backup to a stable system
    after 2035 this robustness wil dwindle but also be needed harder (more RE intermittency)

    I would say: yes we should join hands. And having a model 100RE is a good base to built upon. In itself it is simply not good enough, for the task that lays ahead of us.

  2. Arturo Rodrigo Avatar
    Arturo Rodrigo

    The discussion / cat fight has been enlightening – good to see the issues surface.

    With Australia now working on a target of 82% RE the nuclear issue has been raised as a political football with not always honest intentions. It would be great to see more analysis of the cost of nuclear (including WACC) for Australia specifically. We’d be at a standing start – nuclear currently banned, no industry, no expertise and future security issues limiting potential choice of vendors. Additionally the newest modular paper models have had no opportunity for learning curves, with no reference installs. Offshore Wind is now blowing out costs too – though materials costs increases apply across all the technologies. Australia now has a plan and is implementing it – the obstacles are many but the direction is greatly improved due to the fairly recent change from an obstructionist government.

  3. Dear Auke,

    First, if you claim – as you do – that your modelling “demonstrates* that excluding nuclear energy is the cheapest way to eliminate fossil fuels, then you can’t blame people for assuming that you are using *current* cost information, especially if you bury these important details in the small print.

    Second, you excluding nuclear energy from your model by disallowing it as an option is *not* equivalent to your model freely and independently returning economically optimal pathways to net zero that exclude nuclear only because it would not improve the economics.


    ir. J.E. van Dorp, MSc, MEng