$12B of US ratepayers' money wasted on a modeling mistake in PJM(newsletter.semianalysis.com) |
$12B of US ratepayers' money wasted on a modeling mistake in PJM(newsletter.semianalysis.com) |
That was not clear in the article.
And ISOs/RTOs/TSOs operate in complex political environments and have to ensure reliability in adverserial markets. They are often constraint in what they can/can't do.
What I will say is that their modelling should absolutely be open and transparent, and typically it's not. That would make necessary discussions around modelling assumptions, potential improvements and political constraints much much easier and more fruitful.
[1] That said, my intuition is that current outages are probably not due to supply insufficiency, but due to transmission system failures.
This is anti-scientific woo. Both theoretically and empirically market-based electricity systems are much more efficient, that's why even China is adopting one: https://www.enerdata.net/publications/daily-energy-news/chin...
Whilst these sorts of analyses are informative, they lack answers to the who profits? question.
The intention of the payments is to increase revenue for that kind of power generation capability to encourage more such plants be constructed.
The argument in the article is dubious to me. Of course the higher price isn’t leading to more generation today, that’s not the point, the point is to reward developers that build and built capacity CA needs in winter. The disagreement then becomes which model is correct about how much capacity is actually needed.. but the fact that a tiny move in demand moves the price so substantially seems to me to undermine the entire premise of the blog post, clearly supply is severely constrained?
https://inthesetimes.com/article/the-excel-error-heard-round...
It also reminds me of the flaws in the London epidemiological model about how to respond to covid.
It just may be that these things should be reviewed a little closer by people who are obsessive about correctness
That one was fun. I got into an argument with a scientist who was (IIRC) working with or for the specific professor that made that mess, and he blamed the entire software engineering/computer science industry for making C++ too hard to use, and said it should never have been released if mistakes like this could be made. And then accused me of gatekeeping when I said perhaps they should get an expert to look over this stuff before submitting results to governments to form a policy basis.
The attitude seemed to be "I am a scientist and am clearly very smart, and therefore anything you do must be trivial in comparison. If I can't pick up in seconds what takes you years to learn and more years to perfect, you've clearly done it all wrong and it's your fault."
I’m not a quant, and I’ve worked energy trading desks long enough to know there is a lot I don’t understand.. but I don’t see how separating auctions by plant age does anything other than move numbers around while keeping the total bill the same. Plants still need the same lifetime revenue to make investment decisions pencil out; whether you front-load payments or spread them evenly, the total in current value needs to be the same.
So it can matter how we distribute that revenue as to whether or not the business responds in the desired way, eg, actually investing in new capacity by linking payments directly to new capacity.