Batteries are a bit of a red herring. The combination of pumped storage plants, overgeneration, and demand response already has you covered for at least two decades even in Germany. The minimal cost solution calculated for Germany assumes 1.6 GWh of storage for your 1000 MW nuclear equivalent for a 60% RE penetration scenario, only some of which needs to be batteries (Germany is currently at ~45% or so, many other countries are considerably behind). At the expense of extra costs, lower storage could be compensated for by higher overgeneration (= by not consuming all the power you produce).
However, this was all calculated for current grid conditions. Spread of BEVs would likely put dedicated grid storage needs lower, since in Germany, for each of your 1000 MW nuclear equivalents, there's 700k cars which already have ~600 MWh of storage capacity even just in form of lead-acid batteries, and even replacing just 10% of these cars with 40 kWh BEVs would give you a whopping 2.8 GWh of capacity per your 1000 MW nuclear equivalent, necessitating higher overgeneration to provide the vehicles with motive energy and lowering grid storage capacity because of demand response ("smart charging"). For reference, a 100% replacement of ICE cars with BEVs in Germany would require a ~25% increase in average power generation - by around 250 MW of average power per your 1000 MW nuclear equivalent.
Electrolytic hydrogen production would do exactly the same thing to grid storage - require more generators, and with demand response, lower grid storage capacity. Just replacing German ammonia with "green" ammonia using electrolysis would necessitate another 60 MW of average power generation per your 1000 MW equivalent that could be subject to demand response.
This is a bit of a nitpick, but this is a physical impossibility. On a AC electric network, if the power input is higher than the power output, the frequency of the current goes up quite quickly, until the grid collapses (because there are security to avoid frequency deviation). You cannot “not consume all the power you produce”, all you can do is not producing as much as you could.
Btw, I'm interested by the sources of your “1.6 GWh of storage for your 1000 MW nuclear” because it sounds really low to me. I did a simulation[1] a while ago based on French data, for a 100% RE scenario and my calculation arrived at around 250GWh per GW of installed capacity. For sure it's not the same country, and a 60% vs 100% RE is a huge step, but the differences between those two results is a lot more than what I would expect.
A mistake I've frequently seen with people discussing wind power storage, is taking the average capacity factor and calling it a day. The storage need for wind-based power generation is enormous because (at least in France, but given the geography of Germany I'd expect it to be even worse there) you can have severe wind deficit which can last for weeks!!
> This is a bit of a nitpick, but this is a physical impossibility. On a AC electric network, if the power input is higher than the power output, the frequency of the current goes up quite quickly, until the grid collapses (because there are security to avoid frequency deviation). You cannot “not consume all the power you produce”, all you can do is not producing as much as you could.
I probably should have said "all the power you could produce", since for example with photovoltaics you can produce at any moment any amount of power from zero up to the MPPT point on the I/V curve, depending on how much charge you remove from the panel. I hope this clears it up.
> Btw, I'm interested by the sources of your “1.6 GWh of storage for your 1000 MW nuclear” because it sounds really low to me
> I did a simulation[1] a while ago based on French data, for a 100% RE scenario and my calculation arrived at around 250GWh per GW of installed capacity.
Maybe you've just taken Sinn's approach instead of Zerrahn's? That number would seem to fit it.
> Maybe you've just taken Sinn's approach instead of Zerrahn's? That number would seem to fit it.
I wasn't aware of that paper (thanks again!), but from skimming Sinn's paper, our methodology seems to be pretty similar. I'm even more excited to read Zerrahn's paper now!
Ok so I read Zerrahn's paper, and I have to admit I didn't expect to be that shocked by the methodology. Of course I'm a bit biased because my own work is really close to Sinn's which is criticized in this paper, but this paper really makes me think the author didn't even try to understand what Sinn studied in their paper: Zerrahn seems to believe that Sinn's scenario stores all the energy because they don't want to waste electricity, but it doesn't occur to them that Sinn's stores all that electricity because at some point the grid will needs it!. In fact, I think the culprit is just using RLDCs (residual load duration curves) instead of time series, because this way you just erase the temporal dimension of the problem, which is − unfortunately − the most important one.
For instance, in my own data (France, year 2017, for the record the scenario was 100% RE) from the first of January 12am, to the 3rd at 3pm the wind capacity factor barely exceed 10%, three days in a row. For this period only you'd need 3TWh of storage[1]! No reasonable level[2] of curtailment is gonna help here.
[1]: of course it doesn't have to be storage, you just need 50GW of controllable power and any fossil fuel would work (and that's what the Danish do for instance) but this is outside of the scope of this discussion, which is about how storage allows you to avoid pairing RE with fossil sources.
[2]: I assume that nobody would consider something above 90% curtailment to be reasonable.
> but it doesn't occur to them that Sinn's stores all that electricity because at some point the grid will needs it!
I'm pretty sure that they understand that. What they don't understand (and what I don't understand) is why is Sinn making the amount artificially high by ignoring the economics. I immediately understood what Zerrahn was getting at, and even before I knew how different authors approached this problem in literature, I would have myself intuitively gone for an approach like Zerrahn's. MRTS is surely not a difficult concept to grasp.
> For instance, in my own data (France, year 2017, for the record the scenario was 100% RE) from the first of January 12am, to the 3rd at 3pm the wind capacity factor barely exceed 10%, three days in a row. For this period only you'd need 3TWh of storage! No reasonable level[1] of curtailment is gonna help here.
I can't tell you what Zerrahn's approach would tell you for the French grid. You can't really extrapolate that from German results. You'd have to pretty much re-do the whole work, including getting equivalent data for the French grid.
However, this was all calculated for current grid conditions. Spread of BEVs would likely put dedicated grid storage needs lower, since in Germany, for each of your 1000 MW nuclear equivalents, there's 700k cars which already have ~600 MWh of storage capacity even just in form of lead-acid batteries, and even replacing just 10% of these cars with 40 kWh BEVs would give you a whopping 2.8 GWh of capacity per your 1000 MW nuclear equivalent, necessitating higher overgeneration to provide the vehicles with motive energy and lowering grid storage capacity because of demand response ("smart charging"). For reference, a 100% replacement of ICE cars with BEVs in Germany would require a ~25% increase in average power generation - by around 250 MW of average power per your 1000 MW nuclear equivalent.
Electrolytic hydrogen production would do exactly the same thing to grid storage - require more generators, and with demand response, lower grid storage capacity. Just replacing German ammonia with "green" ammonia using electrolysis would necessitate another 60 MW of average power generation per your 1000 MW equivalent that could be subject to demand response.