Open datejada opened 8 months ago
I couldn't agree more.
From my experiences with I-ELGAS and COMPETES, this has been in the center of the results, i.e., where does this price come from?
It is barely manageable by playing with dual prices if you don't consider inter-temporal constraints. But as soon as you have them, I see the way to go is to derive the analytical solution. I did something similar in my PhD and I can see a great academic contribution (I've seen papers already going crazy by playing with duals from storage). So to me, this is a research project for an MSc student (?) or a PhD student.
This can probably be addressed by students from TU Delft. (Maybe Matthijs)
@g-moralesespana, can we get a Master's student from TU-Delft for this?
The people from TU Graz have proposed something that will help us with this issue (see paper below). They can determine the marginal when the problem is linear and has ramping, network congestion, and storage constraints. It doesn't work yet for MIP or DC OPF, but it is a good start.
https://www.sciencedirect.com/science/article/pii/S037877962400155X?via%3Dihub
@greg-neustroev This is the issue that a master's student can pick up to work in Tulipa
Description
When analyzing the results of energy models, one key answer is to determine who the marginal plant (an asset in Tulipa) is.
The solution is not straightforward for several reasons. For example, storage assets can be marginal assets, and their marginal cost depends on their efficiency and the marginal cost of another asset at a different hour. Moreover, ramping constraints can also distort the concept of who the marginal asset is. So, it is a tricky calculation.
It will be nice to research beforehand to see the best way to get the information. The solver can give some useful information about the pivot columns and rows. This might be a good research project for a PhD student, too.
It will be nice to have it as an option in Tulipa for the users.
Related Issues
No response