ECC: application of multiple multiplicative inverses
Your analysis is pretty much on point. The cost of batch inversion is only justified if we have a computation involving a relatively large number of simultaneous point additions. In a project I work on, we set a threshold of 70 additions based on our benchmarks. Our code is here if you're interested.
To generalize your example a bit, a single summation involving $n$ points could be reduced to one involving $\lceil n/2 \rceil$ points by simultaneously adding pairs of points. So we would need a rather large summation (140 terms in our case), or several simultaneous summations, to justify the cost of inversion. Even then, we would eventually fall back to projective formulas after this reduction shrinks the problem size below our threshold.
In practice, the cost of inversion isn't likely to be justified for single multiplication problems, at least assuming ~256 bit scalars. The affine formulas are quite useful in the multi-scalar setting, though. We use a multi-scalar variant of Yao's method, which involves computing a summation of precomputed points for each digit in $1 \dots 2^w - 1$. Not only are these summations potentially large, they are also independent of one another, so the whole first (and most expensive) phase of the algorithm can be viewed as $2^w - 1$ simultaneous summations.