| > It's not about being difficult to grasp, it's about whether they are the right tool for the job. Which they aren't, because the temporality of the phenomenon disappear, while it is the single most crucial factor when talking about storage: 24 hours without wind in a row have a dramatically different impact from 24 days each without wind for one hour. I don't see how this changes anything. The difference between the two approaches is not the difference between assuming multi-day troughs in wind power vs. not assuming them (both Zerrahn and Sinn assume their existence) -- it's a difference between blindly modeling storage for all generated power so that it never goes to waste vs. modeling a grid with minimum total cost of all components included that still satisfies expected electricity production demands in all parts of a year (= that does not exceed the capabilities of any component of the system in any part of the year). The latter approach (the feasible set of which is a superset of the feasible set of the former approach) will converge to the former ONLY IF storage costs are disproportionately low. If storage costs are substantial, the optimum will likely lie in the part of the expanded feasible set that lies outside of the original feasible set, with the consequence that the old optimum was very much local, and formed a huge red herring. > In the first case you need enough storage for an entire day, while in the second case all you need is one hour of storage! (And that's where the two orders of magnitude come from: «several days» being ~100 times as long as «1 hour». No, that's NOT where the difference is, and I'm dismayed that this is your takeaway from all this even after reading TFA by Zerrahn. The difference is that Sinn assumes that if there's 1 GWh to be fulfilled in the middle of January and there's a matching 1 GWh of PV overgeneration in the middle of July, then it's perfectly reasonable to say "fine, let's store that 1 GWh for half a year until we need it in the middle of January, regardless of how expensive it is" -- because THAT is what you necessarily end up with if you're going for 0% curtailment like Sinn did. And it turns out that economically, this is terrible idea, and once you realize it and include economics in your models, they will steer you away from the idea of zero curtailment. > The storage you need is strictly superior the sum of consecutive hours with a positive residual load ...and Sinn makes that positive residual load artificially high compared to the economic optimum because of striving for 0% curtailment for no good reason. > Sinn doesn't take economics in account, because it's not relevant to the discussion here, it's all about physics here. (And Sinn being an economist, he really deserves credit for focusing on the physics aspect). Which makes it all the sadder if he first constructs a straw man and then sets fire to it, especially if it's a straw man from his own department. > It would be easier to just grab the German data used by Zerrahn to reproduce Sinn's findings (because they claim them to be easily accessible). But...that's what Zerrahn did? It's mentioned in the paper that they replicated Sinn's findings with their own data as a validation that they're calculating with comparable data. |
No, that's Zerrahn's take on Sinn's paper, but you should not take it for granted. And the cheap shot about the «Non-robustness» of Sinn's paper should serve as a warning that Zerrahn is not really giving Sinn's paper a fair treatment.
> But...that's what Zerrahn did? It's mentioned in the paper that they replicated Sinn's findings with their own data as a validation that they're calculating with comparable data.
Yes, and now I want to re-use the same dataset, but with a proper time-based methodology so I can find a specific time period for which Zerrahn's-level of storage would lead to a network collapse (Like I did for the French data above).