If I simulate a skewed sample using a very large n-value and the parameters align with my target parameters, I am guessing I can then shrink the n-value and assume the smaller sample is a realization of my target.

So I can test sample sizes for Wilcox on sign rank test, straightforward.

What about a one-sample ttest (vs 0) of differences of two lognormal variables, though 0's may be in the sample so log transformation may require use of a constant. Any advice?

When I backtransform I will be in the median realm, but how does the constant come into play?