EV Market Share

[jhm]

The not-so-encouraging news is stealing share from hybrids and PHEVs won't get you very far.

CA's mild climate, $4 gasoline, social mores and various incentives (tax credit, HOV, etc.) all encourage hybrid/EV purchase. Yet combined hybrid/EV market share only grew from 9% to 12% in six years! Look at this consumer adoption curve EV fans like to tout. Adoption rate was almost vertical by the time these new technologies reached 10% share. If you consider CA BEVs separately, the trend best matches air travel in 1950, with 5% share and close to 1%/year share growth rate. 20% share took another 15 years. And the recent CA BEV surge was almost entirely due to Tesla Model 3, which was a one-time event.

The way I like to think about this is through evolutionary biology. Each model is like a species and will evolve and give rise to newer species over time. When a new species comes into existence, it competes with the others. So any nee species that is able to take substantial share from other species is simply a more fit and competitive species. So for the Model 3 to knock off some PHEV, just means that the field is taking an evolutionary step forward. The mix of species left in the field is even more capable of taking market share from ICE. So pushing hybrids out of the market may seem like a step backward numerically, but it is a huge evolutionary step forward to having the kinds of EVs needed to displace ICE. So longer term it is a critical step forward. If hybrids were good enough to drive traditional ICE out of the market, we'd already be much further down that path. Over the last 20 years hybrids have not been competitive enough to take significant market share. Hybrids do have opportunities to evolve their technology, but they really need to step up their game if they want to survive.

 

[jhm]

The global growth curve for EVs is consistent and not really affected by minor burbles in individual markets. 40% - 50% annual growth; doubling every two years. Very simple.

So far, Tesla has tracked the global growth curve quite closely. Production problems may have Tesla low one year, and then they catch up the next year. Make no mistake, Tesla is still strictly production limited.

I fully expect Tesla to slow down and be unable to match the global EV growth rate at some point; arguably this has already happened; but they're closer to matching the growth of the total EV market than any other company is; everyone else is falling behind faster. (The total growth is partly made up of new companies entering the EV market.)

We now know something about how the adoption curve will look after it reaches 50% market share, thanks to Norway essentially reaching 50% last year. It keeps going exponentially the next year, right up to 75%. In 2020 we will probably find out how the rest of the back half of the adoption curve looks in Norway -- I doubt it will go up to 112.5% market share, so it'll be a very interesting number to look at. California will follow the same curve, obviously, though it is many years behind Norway.

Actually, there could be a case for a 112% market share, if you use the expected size of the new vehicle market rather than the actual size. In other words, the availability of EVs coupled with substantial pent up demand could allow the new car market to grow much faster in a year than historical growth rates. For example, total new car sales could surge 20% instead of nominal 2% growth. This overshoot would allow EV exponential growth to continue an extra year or so.

I think we are seeing the flip side of this now as a lack of EV supply is causing total auto sales to shrink. The so-called Osborning of ICE. But this phenomenon also sets the auto market up with pent up unmet demand. If there were an abundance of compelling EV product coming onto the market (or rather a surplus of battery supply), we could see a surge in total auto sales.

It will be fascinating to see these dynamics play out.

 

[jhm]

I was hoping for a funny rating on my mention of 112% market share. :-(

Oh, I thought you were serious.

 

[ItsNotAboutTheMoney]

Carbon tax just hurts the poor. See France.

Only way to deal with climate change is to implement a grand scheme like the new green deal. You need to make everyone involved and cared for.

If the only thing you do is carbon taxation you'd hurt the poor. But carbon taxation should have a knock-on impact on minimum incomes and benefits, because it changes cost of living.

It's people on fixed incomes that get hurt by carbon taxation, because their income has been determined before the realignment.

 

[mspohr]

EV disruption is getting serious
Rumor Mill Goes Into Overdrive — GM/Ford Merger On The Horizon? And What About Tesla? | CleanTechnica

The Market Watch story is just that, a story. But it demonstrates how shaky the ground is under the car business these days. Even Tesla has been drawn into the rumor mill activity. Because Apple considered buying Tesla three years ago, some think it could still be interested in its Silicon Valley neighbor today.

Market Watch goes further with its predictions. “While GM may have a future as a standalone car company over the next decade, Ford does not. Its market cap is down 42% over the past five years, while GM’s is close to flat. The savings in a combination would be well into the billions of dollars. A marriage of the two also could compete effectively with Toyota, VW and perhaps the new Fiat Chrysler and Renault combo.”

Here’s a fun exercise. List the top 10 car companies in the world. In 5 years, half of them will probably be out of business. That’s the power of the EV revolution.

 

[canoemore]

The way I like to think about this is through evolutionary biology. Each model is like a species and will evolve and give rise to newer species over time. When a new species comes into existence, it competes with the others. So any nee species that is able to take substantial share from other species is simply a more fit and competitive species. So for the Model 3 to knock off some PHEV, just means that the field is taking an evolutionary step forward. The mix of species left in the field is even more capable of taking market share from ICE. So pushing hybrids out of the market may seem like a step backward numerically, but it is a huge evolutionary step forward to having the kinds of EVs needed to displace ICE. So longer term it is a critical step forward. If hybrids were good enough to drive traditional ICE out of the market, we'd already be much further down that path. Over the last 20 years hybrids have not been competitive enough to take significant market share. Hybrids do have opportunities to evolve their technology, but they really need to step up their game if they want to survive.

The concept of frequency-dependent selection provides a useful extension of the evolution analogy. This is when the fitness of a phenotype increases as the frequency of that phenotype increases. This phenomenon is well documented in nature, particularly with traits that involve signalling, such as warning coloration.

Analogies to EVs (and other technologies) are pretty obvious, and boil down to the notion that as adoption becomes more widespread, the utility of a technology increases for one reason or another. For example, as the frequency of the EV "phenotype" increases, the network of charging stations to serve them increases in density, thereby increasing the "fitness" of EVs still further: ergo, positive frequency-dependent selection. You can see that the converse can also be true. ICE vehicles will eventually experience negative frequency-dependent selection: as they fall in frequency, filling stations will start to close, reducing their "fitness" (i.e. utility). These obviously aren't novel observations, and are discussed (sans evolutionary metaphor) at length in various threads here.

However, a return to the original comment about stealing market share from hybrids with this context may offer a more novel observation. At first glance, I don't see a reason why hybrids should experience similar positive density-dependent selection. As the frequency of hybrids goes up, what intrinsic feature of a hybrid, or what accompanying infrastructure, would increase their "fitness"? They still fill up at gas stations, so contribute to positive frequency-dependent fitness of traditional ICE vehicles. I don't think the experience of owning a hybrid has appreciably changed since the first generation Prius, at least not as a result of the much higher frequency of hybrids in the market today. I suppose you could argue that larger market share has produced economies of scale that have driven down costs of hybrid components, but I'm not sure that really counts - hybrids still typically cost more than their ICE counterparts.

Meanwhile, as EV market share has grown, the ownership experience has gotten dramatically better, and the "fitness" of EVs has increased in step with their frequency. We see the results of this when members of this forum share anecdotes about how they've convinced friends and family who aren't "early adopters" to buy a Tesla.

Another interesting application of this evolutionary thinking would be to predict the fates of the morass of charging standards.

 

[canoemore]

The concept of frequency-dependent selection provides a useful extension of the evolution analogy. This is when the fitness of a phenotype increases as the frequency of that phenotype increases. This phenomenon is well documented in nature, particularly with traits that involve signalling, such as warning coloration.

Analogies to EVs (and other technologies) are pretty obvious, and boil down to the notion that as adoption becomes more widespread, the utility of a technology increases for one reason or another. For example, as the frequency of the EV "phenotype" increases, the network of charging stations to serve them increases in density, thereby increasing the "fitness" of EVs still further: ergo, positive frequency-dependent selection. You can see that the converse can also be true. ICE vehicles will eventually experience negative frequency-dependent selection: as they fall in frequency, filling stations will start to close, reducing their "fitness" (i.e. utility). These obviously aren't novel observations, and are discussed (sans evolutionary metaphor) at length in various threads here.

However, a return to the original comment about stealing market share from hybrids with this context may offer a more novel observation. At first glance, I don't see a reason why hybrids should experience similar positive density-dependent selection. As the frequency of hybrids goes up, what intrinsic feature of a hybrid, or what accompanying infrastructure, would increase their "fitness"? They still fill up at gas stations, so contribute to positive frequency-dependent fitness of traditional ICE vehicles. I don't think the experience of owning a hybrid has appreciably changed since the first generation Prius, at least not as a result of the much higher frequency of hybrids in the market today. I suppose you could argue that larger market share has produced economies of scale that have driven down costs of hybrid components, but I'm not sure that really counts - hybrids still typically cost more than their ICE counterparts.

Meanwhile, as EV market share has grown, the ownership experience has gotten dramatically better, and the "fitness" of EVs has increased in step with their frequency. We see the results of this when members of this forum share anecdotes about how they've convinced friends and family who aren't "early adopters" to buy a Tesla.

Another interesting application of this evolutionary thinking would be to predict the fates of the morass of charging standards.

Slight correction to the above. Instead of negative frequency-dependent selection, I meant to say that positive frequency dependent selection cuts both ways, and the decrease in ICE frequency will produce a concurrent decrease in fitness. Negative frequency dependent selection describes the inverse relationship between fitness and phenotype frequency, i.e. the more common a phenotype becomes, its fitness decreases.

 

[jhm]

The concept of frequency-dependent selection provides a useful extension of the evolution analogy. This is when the fitness of a phenotype increases as the frequency of that phenotype increases. This phenomenon is well documented in nature, particularly with traits that involve signalling, such as warning coloration.

Analogies to EVs (and other technologies) are pretty obvious, and boil down to the notion that as adoption becomes more widespread, the utility of a technology increases for one reason or another. For example, as the frequency of the EV "phenotype" increases, the network of charging stations to serve them increases in density, thereby increasing the "fitness" of EVs still further: ergo, positive frequency-dependent selection. You can see that the converse can also be true. ICE vehicles will eventually experience negative frequency-dependent selection: as they fall in frequency, filling stations will start to close, reducing their "fitness" (i.e. utility). These obviously aren't novel observations, and are discussed (sans evolutionary metaphor) at length in various threads here.

However, a return to the original comment about stealing market share from hybrids with this context may offer a more novel observation. At first glance, I don't see a reason why hybrids should experience similar positive density-dependent selection. As the frequency of hybrids goes up, what intrinsic feature of a hybrid, or what accompanying infrastructure, would increase their "fitness"? They still fill up at gas stations, so contribute to positive frequency-dependent fitness of traditional ICE vehicles. I don't think the experience of owning a hybrid has appreciably changed since the first generation Prius, at least not as a result of the much higher frequency of hybrids in the market today. I suppose you could argue that larger market share has produced economies of scale that have driven down costs of hybrid components, but I'm not sure that really counts - hybrids still typically cost more than their ICE counterparts.

Meanwhile, as EV market share has grown, the ownership experience has gotten dramatically better, and the "fitness" of EVs has increased in step with their frequency. We see the results of this when members of this forum share anecdotes about how they've convinced friends and family who aren't "early adopters" to buy a Tesla.

Another interesting application of this evolutionary thinking would be to predict the fates of the morass of charging standards.

Ah, this is really nice. It seems the frequency-dependent selection would relate the economists not of economy of scale and experience or learning curves. Specifically the experience curve seems dependent on sufficient opportunities to cut costs as a supply chain scales up. If scale increases do not actually lead to unit cost reductions, then the experience curve wont work. But empirically we see that some technologies or products have faster experiences curves than others. For example, solar has a faster learning rate than wind. (I don't recall specific numbers off the top of my head, but a simple web search should find it quickly.) So there seems to be something inherently different between solar and wind. But this learning rate is very important to understand how wind had reached grid price parity and scaled up sooner, but that solar looks to surpass wind both on low cost and scale. I think it may have something to do with the physical scale differences. Wind turbines get performance gains and lower unit cost mostly by increasing the size of the turbine. But going big makes turbines more difficult and costly to produce and install. Solar, however, realized performance gain by improvements at scales approaching the nanoscale. So I think this has something to do with the differences, but maybe there are frequency-dependent factors at work too.

 

[winfield100]

Ah, this is really nice. It seems the frequency-dependent selection would relate the economists not of economy of scale and experience or learning curves. Specifically the experience curve seems dependent on sufficient opportunities to cut costs as a supply chain scales up. If scale increases do not actually lead to unit cost reductions, then the experience curve wont work. But empirically we see that some technologies or products have faster experiences curves than others. For example, solar has a faster learning rate than wind. (I don't recall specific numbers off the top of my head, but a simple web search should find it quickly.) So there seems to be something inherently different between solar and wind. But this learning rate is very important to understand how wind had reached grid price parity and scaled up sooner, but that solar looks to surpass wind both on low cost and scale. I think it may have something to do with the physical scale differences. Wind turbines get performance gains and lower unit cost mostly by increasing the size of the turbine. But going big makes turbines more difficult and costly to produce and install. Solar, however, realized performance gain by improvements at scales approaching the nanoscale. So I think this has something to do with the differences, but maybe there are frequency-dependent factors at work too.

@jhm
Statistical Review of World Energy | Energy economics | Home

 

[winfield100]

log scale looks like PV is overtaking tho
data only thru 2017 , no new data until a month or so

 

[canoemore]

Ah, this is really nice. It seems the frequency-dependent selection would relate the economists not of economy of scale and experience or learning curves. Specifically the experience curve seems dependent on sufficient opportunities to cut costs as a supply chain scales up. If scale increases do not actually lead to unit cost reductions, then the experience curve wont work. But empirically we see that some technologies or products have faster experiences curves than others. For example, solar has a faster learning rate than wind. (I don't recall specific numbers off the top of my head, but a simple web search should find it quickly.) So there seems to be something inherently different between solar and wind. But this learning rate is very important to understand how wind had reached grid price parity and scaled up sooner, but that solar looks to surpass wind both on low cost and scale. I think it may have something to do with the physical scale differences. Wind turbines get performance gains and lower unit cost mostly by increasing the size of the turbine. But going big makes turbines more difficult and costly to produce and install. Solar, however, realized performance gain by improvements at scales approaching the nanoscale. So I think this has something to do with the differences, but maybe there are frequency-dependent factors at work too.

@jhm, I think you’re really onto something with the link between the physical scale of these two technologies and the speed at which they change. After mulling it over, I have these thoughts.

In biology, there is a strong correlation between physical size and generation time. For example, in the time it takes for a single generation of elephants to be born, reproduce, and die, a population of bacteria associated with those same elephants will go through hundreds of thousands of generations. At each generation, all the variants composing the population will experience selection and other evolutionary forces - some variants will die, some may reproduce more quickly than others - and the next generation will have a different pool of variation than the last, perhaps better adapted to prevailing conditions. This means that organisms with short generation times can evolve much more quickly than organisms with long generation times: beneficial variation can spread very quickly while harmful variation can be purged very quickly. Kind of a similar idea to the Silicon Valley ethos of “Move fast and break things”.

I think a good analog of “generation time” for solar pv and wind might be the duration of individual project timelines for each technology. I did a cursory search and found some evidence that seems to confirm our suspicion that wind takes longer to get up and running than solar. I imagine there’s a ton of variation based on project size/specific technology deployed, but this source suggests wind project timelines on the order of a year or several years, and this CleanTechnica article cites NREL data for solar pv showing a median of 53 days (with a lot of variation). If that’s even close to accurate, I’ll channel Elon by observing that there’s a gap of at least one order of magnitude (and perhaps two) between the project timelines for these two technologies. I’d bet solar’s faster descent of the cost curve than wind can be partly explained by that difference in project timeline length. With shorter project timelines, new innovations in pv technology can be introduced and evaluated by the market more quickly. With the market imposing such strong selection for the lowest possible $/kwh lessons learned from each project can spread very rapidly.

More individual solar projects than wind projects?
I couldn’t find data on this in a quick search - most of the information about both solar and wind capacity is reported in terms of total installed GW installed - but I would bet that there are more individual solar projects installed each year than individual wind projects, and I would bet it’s also linked to the physical scale of each technology. If that’s true, it may also help explain the faster learning rate in solar relative to wind. As the data @winfield100 presents illustrates, wind may have deployed more GW of capacity, but from an evolutionary perspective, the number of independent projects for each technology may matter more than the total number of installed GW.

Selection is more efficient in larger population sizes than in smaller population sizes (well, technically effective population sizes, but I don’t think the distinction is critical for this analogy). The basic idea is that in small populations, evolutionary mechanisms other than selection (such as migration, or random effects like a natural disaster) make a larger relative contribution in determining what traits are passed on to the next generation than they do in large populations. This means that small populations may respond to selection less strongly than expected or even evolve in the opposite direction of selection. Imagine two populations of birds, one with 10 individuals and one with 1,000. The individuals in each population are 50% blue and 50% red, and selection favors red birds (i.e. red birds have more offspring on average). Say a storm randomly kills half of each population. Color frequencies in the larger population will probably still be in the neighborhood of 50-50, but in the small population it’s not improbable that say, 4 red and 1 blue bird die, leaving you with 80% blue and 20% red. Similarly, if you introduce 5 blue migrants to each population, it won’t appreciably change the color frequencies in the larger population, and the addition will probably get drowned out by selection for red birds. But in the smaller population you end up with 2/3 blue and 1/3 red. In both cases, despite selection for red coloration, the smaller population evolves in the opposite direction towards a higher frequency of blue birds.

For solar and wind I can imagine a number of extrinsic factors that may run counter to selection imposed by the market for the lowest $/kwh. Corruption, natural disasters, unexpected tariffs, counter-productive policy decisions, etc. A larger “population size” of solar projects may minimize the impact of these factors, allowing selection solar pv down the cost curve faster than wind. Come to think of it, this line of reasoning may also help explain why technologies like nuclear generation seem to get more costly over time. Evolution produces sub-optimal outcomes pretty regularly, often related to the reasons discussed above.

Both of these attributes - shorter project timelines and larger number of individual projects - also introduce more opportunities for “mutations” to arise. Every time someone starts a project, they might try something new or do things a little differently, either intentionally or as the result of a mistake. The more independent projects in total, the more variation can arise. Very rarely these mistakes or little experiments might result in Eureka! moments that are analogous to a beneficial mutation in some biological population. I don’t have any specific examples for solar pv in mind, and perhaps that’s not how it really works with these projects, but it seems like reasonable speculation.

So, yeah, I agree that there are definitely some fundamental differences between these two technologies that end up really favoring photovoltaics over wind when it comes to how quickly each improves.

A tangentially related side-note to a discussion about wind vs. solar technology that I find interesting: I can think of a lot of indirect ways that organisms have evolved to harvest wind energy: birds gliding on air currents, dispersal of seeds and pollen, spiders catching wind-driven prey in their webs, etc., but I don’t think there’s a single example of an organism that has evolved a mechanism by which to directly convert wind energy into chemical energy. That’s in stark contrast to photosynthesis, which is obviously the foundation of (nearly) every food web on earth. Maybe there’s a lesson there.

 

[jhm]

View attachment 413979
log scale looks like PV is overtaking tho
data only thru 2017 , no new data until a month or so

For my money, log scale is the best way compare exponential growth. It also helps to look at incremental volume (differences) as opposed to cumulative volume (levels). So it look like solar is nearly beating wind in incremental volume. Wind of course has a substantial lead in cumulative volume, but I do believe solar will eventually catch up on that basis.

Thanks for the nice charts!

 

[EVNow]

If the only thing you do is carbon taxation you'd hurt the poor. But carbon taxation should have a knock-on impact on minimum incomes and benefits, because it changes cost of living.

It's people on fixed incomes that get hurt by carbon taxation, because their income has been determined before the realignment.

If carbon is toxic for the earth it needs to be banned. You can't put a tax to stop murder.

 

[jhm]

@jhm, I think you’re really onto something with the link between the physical scale of these two technologies and the speed at which they change. After mulling it over, I have these thoughts.

In biology, there is a strong correlation between physical size and generation time. For example, in the time it takes for a single generation of elephants to be born, reproduce, and die, a population of bacteria associated with those same elephants will go through hundreds of thousands of generations. At each generation, all the variants composing the population will experience selection and other evolutionary forces - some variants will die, some may reproduce more quickly than others - and the next generation will have a different pool of variation than the last, perhaps better adapted to prevailing conditions. This means that organisms with short generation times can evolve much more quickly than organisms with long generation times: beneficial variation can spread very quickly while harmful variation can be purged very quickly. Kind of a similar idea to the Silicon Valley ethos of “Move fast and break things”.

I think a good analog of “generation time” for solar pv and wind might be the duration of individual project timelines for each technology. I did a cursory search and found some evidence that seems to confirm our suspicion that wind takes longer to get up and running than solar. I imagine there’s a ton of variation based on project size/specific technology deployed, but this source suggests wind project timelines on the order of a year or several years, and this CleanTechnica article cites NREL data for solar pv showing a median of 53 days (with a lot of variation). If that’s even close to accurate, I’ll channel Elon by observing that there’s a gap of at least one order of magnitude (and perhaps two) between the project timelines for these two technologies. I’d bet solar’s faster descent of the cost curve than wind can be partly explained by that difference in project timeline length. With shorter project timelines, new innovations in pv technology can be introduced and evaluated by the market more quickly. With the market imposing such strong selection for the lowest possible $/kwh lessons learned from each project can spread very rapidly.

More individual solar projects than wind projects?
I couldn’t find data on this in a quick search - most of the information about both solar and wind capacity is reported in terms of total installed GW installed - but I would bet that there are more individual solar projects installed each year than individual wind projects, and I would bet it’s also linked to the physical scale of each technology. If that’s true, it may also help explain the faster learning rate in solar relative to wind. As the data @winfield100 presents illustrates, wind may have deployed more GW of capacity, but from an evolutionary perspective, the number of independent projects for each technology may matter more than the total number of installed GW.

Selection is more efficient in larger population sizes than in smaller population sizes (well, technically effective population sizes, but I don’t think the distinction is critical for this analogy). The basic idea is that in small populations, evolutionary mechanisms other than selection (such as migration, or random effects like a natural disaster) make a larger relative contribution in determining what traits are passed on to the next generation than they do in large populations. This means that small populations may respond to selection less strongly than expected or even evolve in the opposite direction of selection. Imagine two populations of birds, one with 10 individuals and one with 1,000. The individuals in each population are 50% blue and 50% red, and selection favors red birds (i.e. red birds have more offspring on average). Say a storm randomly kills half of each population. Color frequencies in the larger population will probably still be in the neighborhood of 50-50, but in the small population it’s not improbable that say, 4 red and 1 blue bird die, leaving you with 80% blue and 20% red. Similarly, if you introduce 5 blue migrants to each population, it won’t appreciably change the color frequencies in the larger population, and the addition will probably get drowned out by selection for red birds. But in the smaller population you end up with 2/3 blue and 1/3 red. In both cases, despite selection for red coloration, the smaller population evolves in the opposite direction towards a higher frequency of blue birds.

For solar and wind I can imagine a number of extrinsic factors that may run counter to selection imposed by the market for the lowest $/kwh. Corruption, natural disasters, unexpected tariffs, counter-productive policy decisions, etc. A larger “population size” of solar projects may minimize the impact of these factors, allowing selection solar pv down the cost curve faster than wind. Come to think of it, this line of reasoning may also help explain why technologies like nuclear generation seem to get more costly over time. Evolution produces sub-optimal outcomes pretty regularly, often related to the reasons discussed above.

Both of these attributes - shorter project timelines and larger number of individual projects - also introduce more opportunities for “mutations” to arise. Every time someone starts a project, they might try something new or do things a little differently, either intentionally or as the result of a mistake. The more independent projects in total, the more variation can arise. Very rarely these mistakes or little experiments might result in Eureka! moments that are analogous to a beneficial mutation in some biological population. I don’t have any specific examples for solar pv in mind, and perhaps that’s not how it really works with these projects, but it seems like reasonable speculation.

So, yeah, I agree that there are definitely some fundamental differences between these two technologies that end up really favoring photovoltaics over wind when it comes to how quickly each improves.

A tangentially related side-note to a discussion about wind vs. solar technology that I find interesting: I can think of a lot of indirect ways that organisms have evolved to harvest wind energy: birds gliding on air currents, dispersal of seeds and pollen, spiders catching wind-driven prey in their webs, etc., but I don’t think there’s a single example of an organism that has evolved a mechanism by which to directly convert wind energy into chemical energy. That’s in stark contrast to photosynthesis, which is obviously the foundation of (nearly) every food web on earth. Maybe there’s a lesson there.

Cool. That's some really elegant thinking. Generation cycle length and project size differences become even more pronounced looking at other generation technologies. What I've seen as some stylized figures is that PV solar and battery storage project take less than a year to develop, wind about 2 years, natural gas 6 year, coal 8-10 years, and nuclear 12 or more years. Nuclear and coal are very large scale projects requiring large scale grids for distribution, while solar and batteries can be exceedingly small serving nanogrids, like small cabin in the woods small. In the time, it would take for a new nuclear project to start generating power, solar and battery storage could be 90% cheaper. The larger scale projects generally require much more political engagement and public commitment, which of course create much more opportunity for political corruption to emerge. So the scale and glacial pace of nuclear I believe are principle drivers of what appears to be a negative experience curve. Basically in real dollars nuclear has become more expensive as it has scaled. The Vogtle 3&4 project in Georgia is looking at the levelized cost of around $230/MWh. This is in a time when natural gas is under $60/MWh and integrated wind+solar+battery PPAs are pushing below $50/MWh. The only way to put such ghastly expensive power on market is to use political power to force the public to pay for it. So, you bet, there is some pretty gamey politics at play. I suppose evolutionary biology has seen this too, large established species that mostly defend territory from competitors.

 

[jhm]

If carbon is toxic for the earth it needs to be banned. You can't put a tax to stop murder.

Carbon is only "toxic" at sufficiently high levels of concentration. Murder is "toxic" at any level of concentration. So with carbon the challenge is how we scale back quickly and in a way that poses minimal cost to the economy. Banning carbon before there is an economic alternative will put the economy at risk and for this reason engender political back lash. It does little good for one government to impose bans in one election cycle only to find their members run out of office by the next election cycle. The replacement government can come in and do more policy damage than the earlier government was able to put into place. This is also the chief vulnerability of a carbon tax. It is not so much that it is regressive, but that political opponents can use the alleged harm to poor people, labor, or whatever as a political wedge issue dismantle political support for any sort of strong policy response to the climate crisis. Australia is a poster child for a carbon tax that was quickly dismantled within the next election cycle. So the really tough problem is how do you put forward meaningful climate policy that does not run your party out of office in the next election cycle. Whether you ban it or just tax it out of the market, you still need to stay in power long enough for it to do some real good.

 

[EVNow]

Carbon is only "toxic" at sufficiently high levels of concentration. Murder is "toxic" at any level of concentration. So with carbon the challenge is how we scale back quickly and in a way that poses minimal cost to the economy. Banning carbon before there is an economic alternative will put the economy at risk and for this reason engender political back lash.

Think of Carbon as DDT. When you ban something, you don't need to ban right away. You give it time - 10 years. For eg., coal power plants are being banned, ICE is being banned - all with some sunset date. Much more direct and clear policy than putting some tax and hoping that will reduce emissions enough.

 

[jhm]

Think of Carbon as DDT. When you ban something, you don't need to ban right away. You give it time - 10 years. For eg., coal power plants are being banned, ICE is being banned - all with some sunset date. Much more direct and clear policy than putting some tax and hoping that will reduce emissions enough.

I see. But the ban still has to be a credible threat. I'm not sure how a ten-year ban that has a good chance of being revoked before it ever takes effect is supposed to make much of difference. You can at least count on your opposition chipping away at it for the next ten ye
I know this is how these ICE bans out in 2030 or later are supposed to work today. But it seem that the man thing that makes this a credible threat is that EVs are becoming incredibly competitive. So long as car buyers are turning on to EV you can expect growing support for such a policy. But if car buyers just never become energized about EVs, the policy would become incredibly unpopular.

This is why I've never been all that enthusiastic about ICE bans. They only have staying power if EVs keep taking substantial market share from ICEVs. In this case, the policy itself does little more than simply allow a competitive market forces run their course.

 

[EVNow]

I see. But the ban still has to be a credible threat. I'm not sure how a ten-year ban that has a good chance of being revoked before it ever takes effect is supposed to make much of difference. You can at least count on your opposition chipping away at it for the next ten years

You need to pass the required laws either way. It’s not like carbon tax can’t be removed. Politics of both are similar. Finally you need a large majority of people who want to do something and policies that help a vast majority. Otherwise it’s not politically sustainable.

 

[Dr. J]

If carbon is toxic for the earth it needs to be banned. You can't put a tax to stop murder.

Carbon is not toxic for the earth. Carbon-based life - Wikipedia

To paraphrase a 1970s Dow Chemical commercial, "Without carbon, life itself would be impossible."

 

[EVNow]

Carbon is not toxic for the earth. Carbon-based life - Wikipedia

To paraphrase a 1970s Dow Chemical commercial, "Without carbon, life itself would be impossible."

Green House gases are toxic to ecosystems above certain levels.

To give an oft used example, even water is toxic above certain levels.

Anyway, I think we are getting OT.

ps : an interesting example of a change over that happened only because of a regulation, but people finally embraced with little problem was change over from analog to digital transmission for ota TV.