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Interaction betwen resource adequacy and security of supply task in the EPOC project.
Ideas to try:
For day 208, the minimum this limit can take appears to be ~0.925. Perhaps due to network constraints.
This is the results for the day selection (not that the load was multiplied by 1.5):
Clearly there is load shedding for day 285, 1,247 MWh to be precise. However, in my analysis of day 285 I don't observe this load shedding! See here for:
This could of course be due to the cyclic storage constraints, but still... suspicious.
The forecast error scenarios I generated using @asutera's code appear to be biased, both when aggregated and also at the nodal level. This is particularly clear for Wind (day 41, top is for node GOUY
, bottom is aggregated over Belgium):
This may be fine, if Antonio didn't correct for this (and we could / should), however it may also be an indication of something being very wrong. It is also so "bad" that there are certain hours (9 - 11) in which there are essentially no scenarios in which a negative imbalance occurs, which is unusual to say the least...
For the main_model_runs
and the run base_UC=true_DANet=true_RSV=0.0_L⁺=1:10_L⁻=1:10_AbsIm=true)
(opts_vec[39]
) I get infeasibilities. I have since added slacks to the absimb constraints to see what that does and it's feasible, but even after 800 seconds there's no solution. I will try a quadratic penalty now to see if that helps.
Again I'm getting feasibility issues, I just hadn't noticed them since the reserve shedding limit constraint isn't binding even for very low levels, i.e. it only becomes binding for values < 0.1.
Some thoughts:
This isn't really a bug but an observation:
This is just to highlight the sensitivity of the system to how storage is assumed to operate. I'm going to keep things as they are, i.e. state of charge is 0.5 at the start of the day and there's a cyclic constraint.
Email I sent to Efthymios:
The issues is that the last for the last hour of the day, load shedding is quite great. I originally thought this might be a unit commitment edge effect, but I'm not so sure anymore - at the very least the generation is within bounds:
julia> z_min = [sum(z[(g,n),Y[1],P[1],t]*NPC[g]*MSOP[g] for (g,n) in GN) for t in T]
24-element Vector{Float64}:
1769.88
1769.88
1769.88
1769.88
1769.88
1769.88
⋮
1745.8
1745.8
1745.8
518.0
1227.8
julia> q_sum
24-element Vector{Float64}:
6315.010836016901
6321.0
6321.0
6321.0
6321.0
6321.0
⋮
1745.8
1745.8
1745.8
518.0
1227.8
Probably need to ask Efthymios for his results file, because it's currently hard to debug.
Brief description of issue:
We initially decided to select 3-4 days, in which there were varying levels of scarcity. I did this initially by inspecting the residual load (RL) duration curve. However, after fixing many bugs (mostly data input issues), I realised that the RL is not a good indicator of scarcity, since scarcity occurred due to congestion, unit commitment and reserve requirements as well as high RL (see Table 2 here, where inclusion of operating reserves network leads to load shedding).
At that point I was choosing days which led to load shedding for a full year economic dispatch model. While it led to the results shown in the above pdf, I noticed more bugs, and when I solve the full year model now I don't get any load shedding at all (again, because I need UC + operating reserves to trigger load shedding, and including both in a full year model would be computationally expensive). So I went back to selecting based on the RL, but I have the same problem that the "most scarce day" doesn't display any scarcity at all (see #11, where I realised that .
That there is no scarcity is problematic mostly for me, since I want to look at the tradeoff between reserve shedding and load shedding. If there's no load shedding, there's no tradeoff. For interacting with ULiege, it's perhaps less problematic, because in any case my schedule will likely have operational security issues anyway, and their main goal is to train their machine learning algorithm.
Solutions:
So I'm going with the last option. Hopefully it leads to load shedding...
This could be due to excessive renewable curtailment, i.e. renewables are being curtailed just to ensure grid feasibility. To be verified.
It is feasible if storage dispatch is not included. This means that somehow the storage dispatch is leading to infeasibilities obviously, but why...
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