If you want to make the best possible predictive model, you should (1) identify the largest source of uncertainty that you cannot include in your model and (2) include in your model everything that has a larger effect than this. Including things in your model which have a smaller effect than your largest source of uncertainty is unnecessary and can cause you to be overconfident in your model. Unfortunately, you typically don’t know what the largest source of uncertainty is beforehand. So you include too many things in your model, and then do a sensitivity analysis to figure out which form of uncertainty is most important and which details you can safely ignore.
My model is not designed to be the best possible model. It is designed to be a simple model.
The goal of a simple model is to identify a few of the most important features of the problem and provide numerical estimates for them. I am optimizing for accessibility as well as for accuracy. The goal is to better inform the debate for people who are not going to read the more accurate models.
I think I struck a pretty goal balance between accessibility and accuracy. I should have linked to some more complete models for people who want to see them. For example, the Net Zero America project from Princeton.
Figuring out how much it currently costs to build new capacity is surprisingly difficult.
The estimates I used from the EIA. They were for overnight cost: the cost if the new capacity could be built overnight. It is common to use levelized cost of electricity (LCOE) instead, which has the capacity factor and longevity of the plant included in the cost.
There is significant uncertainty in the LCOE for both solar/wind and nuclear.
The main uncertainty in the LCOE for solar & wind comes from the capacity factor. Solar and wind projects built at different locations can have dramatically different capacity factors. Taking a national average involves making assumptions about how that capacity is or will be distributed. If most of the solar capacity for the US is in the deserts of the southwest, then it will have a higher capacity factor than if the solar panels are distributed more evenly across the country.
The main uncertainty in the LCOE for nuclear comes from small numbers. The ongoing expansion of Plant Vogtle in Georgia is the only construction of new nuclear power in the US that has begun since 1978. This is not enough data to draw conclusions from, especially since Vogtle is over budget. We could do international comparisons, but there is huge variation in cost between countries.
Fig. 1: Overnight construction cost for nuclear power in various countries, by time the construction began. My estimate corresponds to 6000 on this graph. Source (Fig. 12).
The source I used was unusually favorable to nuclear, compared to solar/wind. It has the overnight cost of nuclear at 4 times the overnight cost of solar/wind. This would make the LCOE for nuclear lower than the LCOE for solar/wind. Other sources, such as Lazard (relevant figure on page 4/21), have the LCOE for nuclear significantly higher than the LCOE for solar/wind.
Using different estimates would have impacted my conclusions.
In particular, the numbers I used implied that building nuclear over capacity would be cheaper than building solar/wind over capacity in the long term. Other estimates imply the opposite. Building nuclear with batteries would still be cheaper, especially because …
This model vastly underestimates the number of batteries needed.
I figured that 36 hours of storage for solar/wind to deal with lulls was an underestimate, but I didn’t realize how much of an underestimate it is.
Here is a two week period in the winter[1]So there’s less solar power. when the wind hardly blew in the entire northwest US. There is reason to think that climate change will make lulls longer,[2]Wind speeds are typically proportional to temperature differences. As the Earth warms, the poles warm more than the Equator, reducing the global range of temperatures. With slower winds, especially a … Continue reading but this is still an active area of research and we don’t know how strong this effect will be. Vox estimates that between 7 & 15 weeks of energy storage would be needed to get to 100% renewables. This would vastly increase the cost of this strategy. Energy storage is by far the biggest challenge for this strategy.
Technological development changes things.
There are several versions of this argument:
Increasing number of electric vehicles will change the shape of demand curves.
The cost of solar/wind has fallen dramatically in recent years, so we can expect it to fall farther.
New nuclear designs could make it cheaper or make it on demand instead of baseload or reduce its regulatory burden. Existing nuclear designs could also be made on demand.
If fusion is going to be available in the foreseeable future, how does that change our considerations?
I explicitly decided to not include future technological development in my model. I should explain more.
(1) My model is primarily intended to inform current discussion, rather than to predict the future. This goes along with my explanation for why I made a simple model.
This is a gears-level model, which means that, if you change the inputs, then the outputs change in predictable ways. If you think that the price of solar panels will fall by another factor of 10 in the next decade, or if you think that we could build nuclear at South Korea’s costs, then you can put that in the model and see what changes.
To make this easier, I have put the model together into a Google Sheet. I have the estimates from the EIA and the low and high estimates from Lazard. If you want to change it further, I encourage you make a copy and so you can mess around with it. Inputs have yellow backgrounds and everything else is calculated from them.
(2) Technological development is not a law of nature. It’s a choice.
It may not be a choice that you personally get to make, but it is a collection of choices made by people. If we were to make different choices, technological development would be different.
Solar and wind have overperformed expectations in recent years. Why? Because lots of brilliant people have worked to improve them and they have received significant government support recently.
Nuclear has underperformed expectations in recent years. Why? Because it faces significant political headwinds, especially after each crisis.
This is a good thing.[3]Not the particular example of irrationally closing nuclear plants. More generally. Human choices impact the world.
When you predict technological development, you are also predicting what choices people will make. I hope that I can influence at least a few people’s choices. Assuming what they choose beforehand is circular.
Wind speeds are typically proportional to temperature differences. As the Earth warms, the poles warm more than the Equator, reducing the global range of temperatures. With slower winds, especially a slower polar vortex, there is less to push away the lulls.
Highlights from the Comments on Generating Electricity without Fossil Fuels
My post series on Generating Electricity without Fossil Fuels has gotten some interesting comments, especially on r/energy and r/nuclear. I would like to respond to them here.
Prerequisites: My post series on Generating Electricity without Fossil Fuels.
Originally Written: February 2022.
Confidence Level: Hopefully improving.
The model would be more accurate if it included more.
e.g. BPP1943 or Engineer-Poet.
Yes. It would.
If you want to make the best possible predictive model, you should (1) identify the largest source of uncertainty that you cannot include in your model and (2) include in your model everything that has a larger effect than this. Including things in your model which have a smaller effect than your largest source of uncertainty is unnecessary and can cause you to be overconfident in your model. Unfortunately, you typically don’t know what the largest source of uncertainty is beforehand. So you include too many things in your model, and then do a sensitivity analysis to figure out which form of uncertainty is most important and which details you can safely ignore.
My model is not designed to be the best possible model. It is designed to be a simple model.
The goal of a simple model is to identify a few of the most important features of the problem and provide numerical estimates for them. I am optimizing for accessibility as well as for accuracy. The goal is to better inform the debate for people who are not going to read the more accurate models.
I think I struck a pretty goal balance between accessibility and accuracy. I should have linked to some more complete models for people who want to see them. For example, the Net Zero America project from Princeton.
The estimates of construction costs are off.
e.g. Hedgie04 or nebulousmenace.
Figuring out how much it currently costs to build new capacity is surprisingly difficult.
The estimates I used from the EIA. They were for overnight cost: the cost if the new capacity could be built overnight. It is common to use levelized cost of electricity (LCOE) instead, which has the capacity factor and longevity of the plant included in the cost.
There is significant uncertainty in the LCOE for both solar/wind and nuclear.
The main uncertainty in the LCOE for solar & wind comes from the capacity factor. Solar and wind projects built at different locations can have dramatically different capacity factors. Taking a national average involves making assumptions about how that capacity is or will be distributed. If most of the solar capacity for the US is in the deserts of the southwest, then it will have a higher capacity factor than if the solar panels are distributed more evenly across the country.
The main uncertainty in the LCOE for nuclear comes from small numbers. The ongoing expansion of Plant Vogtle in Georgia is the only construction of new nuclear power in the US that has begun since 1978. This is not enough data to draw conclusions from, especially since Vogtle is over budget. We could do international comparisons, but there is huge variation in cost between countries.
The source I used was unusually favorable to nuclear, compared to solar/wind. It has the overnight cost of nuclear at 4 times the overnight cost of solar/wind. This would make the LCOE for nuclear lower than the LCOE for solar/wind. Other sources, such as Lazard (relevant figure on page 4/21), have the LCOE for nuclear significantly higher than the LCOE for solar/wind.
Using different estimates would have impacted my conclusions.
In particular, the numbers I used implied that building nuclear over capacity would be cheaper than building solar/wind over capacity in the long term. Other estimates imply the opposite. Building nuclear with batteries would still be cheaper, especially because …
This model vastly underestimates the number of batteries needed.
e.g. Engineer-Poet.
I figured that 36 hours of storage for solar/wind to deal with lulls was an underestimate, but I didn’t realize how much of an underestimate it is.
Here is a two week period in the winter[1]So there’s less solar power. when the wind hardly blew in the entire northwest US. There is reason to think that climate change will make lulls longer,[2]Wind speeds are typically proportional to temperature differences. As the Earth warms, the poles warm more than the Equator, reducing the global range of temperatures. With slower winds, especially a … Continue reading but this is still an active area of research and we don’t know how strong this effect will be. Vox estimates that between 7 & 15 weeks of energy storage would be needed to get to 100% renewables. This would vastly increase the cost of this strategy. Energy storage is by far the biggest challenge for this strategy.
Technological development changes things.
There are several versions of this argument:
Increasing number of electric vehicles will change the shape of demand curves.
The cost of solar/wind has fallen dramatically in recent years, so we can expect it to fall farther.
New nuclear designs could make it cheaper or make it on demand instead of baseload or reduce its regulatory burden. Existing nuclear designs could also be made on demand.
If fusion is going to be available in the foreseeable future, how does that change our considerations?
I explicitly decided to not include future technological development in my model. I should explain more.
(1) My model is primarily intended to inform current discussion, rather than to predict the future. This goes along with my explanation for why I made a simple model.
This is a gears-level model, which means that, if you change the inputs, then the outputs change in predictable ways. If you think that the price of solar panels will fall by another factor of 10 in the next decade, or if you think that we could build nuclear at South Korea’s costs, then you can put that in the model and see what changes.
To make this easier, I have put the model together into a Google Sheet. I have the estimates from the EIA and the low and high estimates from Lazard. If you want to change it further, I encourage you make a copy and so you can mess around with it. Inputs have yellow backgrounds and everything else is calculated from them.
(2) Technological development is not a law of nature. It’s a choice.
It may not be a choice that you personally get to make, but it is a collection of choices made by people. If we were to make different choices, technological development would be different.
Solar and wind have overperformed expectations in recent years. Why? Because lots of brilliant people have worked to improve them and they have received significant government support recently.
Nuclear has underperformed expectations in recent years. Why? Because it faces significant political headwinds, especially after each crisis.
This is a good thing.[3]Not the particular example of irrationally closing nuclear plants. More generally. Human choices impact the world.
When you predict technological development, you are also predicting what choices people will make. I hope that I can influence at least a few people’s choices. Assuming what they choose beforehand is circular.
References[+]