While I cannot give you any hard estimates, there are a number of points that can be addressed in your question.
First, this is going to be a huge calculation, no matter what, even a single point with a super simple non-hybrid DFT functional like PBE is going to be very demanding.
Second, while you specified Orca as your software of choice, most of the points I make should be fairly generic across the various state-of-the-art linear-scaling CC implementations in Orca, Molpro, MRCC, etc.
With that in mind, using DF/RI (and also probably integral-direct) methods will be unavoidable. Using AutoAux would be a bad idea, it generates large unoptimized auxiliary basis sets that generally should only be used if there is no optimized aux basis for the main basis you are using. I have not checked, but I would think that def2-TZVPPD is popular enough that aux basis availability is not a problem.
I am not familiar with wB97X-2-D and a brief google search had no relevant hits, but "except that the relaxed density be used for the "-2" part" suggests it might be a new double hybrid. This raises more problems, as computing regular RI-MP2 would not be feasible, so you would need to use DLPNO-MP2 or whatever linear-scaling MP2 implementation you have available to compute the PT2 contribution, which might be technical a problem as some implementations might not support using non-HF references.
Either way, trying to use a relaxed (DLPNO-)MP2 density in your double hybrid is probably not going to be feasible, even if it is implemented (which I doubt), computing the relaxed MP2 density is somewhat expensive. But IIRC many double hybrids perform just fine without relaxed MP2 density, so if wB97X-2-D really demands the use of relaxed densities, you would probably want to consider using a different functional that does not require the relaxed MP2 density.
The CC calculation is going to be an enormous challenge to complete. Forget hours, we are deep in the months and years territory. But there is some hope with bleeding edge software and hardware coming in the next 10 years. Take a look at this paper from the MRCC developers, where they have completed a single point LNO-CCSD(T)/def2-QZVP for a protein of 1023 atoms.
One of the most interesting observations they make, is that past ~500 atoms the post-HF part of LNO-CCSD(T) starts getting close to linear scaling, while the DF-HF step has cubic scaling and overtakes LNO-CCSD(T)! Indeed, for their 1 kiloatom LNO-CCSD(T)/def2-QZVP calculation DF-HF took 38 days while after that the post-HF steps were done in just 18 days, all on an old 6-core CPU from 2013 (!!!) and ~100 GB of RAM.
Napkin math time!
Assuming your protein is made out of CH2 units (ie. UHMWPE), you will have ~70k atoms. The post-HF part is easy to estimate if we can assume linear scaling, 18 * 70 = ~1300 days (~3.5 years) on their hardware.
The DF-HF part is a real fly in the ointment: 38 * 70^3 = ~13 megadays or ~36 thousand years.
Now, before you despair, of course we have much faster CPUs today, and in fact we will soon (~2 years) reach 100x the CPU performance that the paper used (256 cores, ~10 TFLOPS FP64). They claim to have pretty good parallel scaling, so assuming that holds, if you were to buy the fastest server that money can buy in 2025, then start the calculation, you may be able to finish it in 2027.
That is of course, assuming no algorithmic improvements or GPU implementation, both of which may make this much more feasible in the meanwhile.
So if you are an undergrad now, a single point CCSD(T)/CBS for this protein might become (barely) feasible by the time you finish your PhD, on something like a then-brand-new supercomputer node.