The number of states explodes due to non-determinism, which is the key to your question.
If you take an NFA, where each transition is uniquely determined, i.e. a deterministic NFA, then it is nothing but a normal DFA. However, once you have a state where two transitions are possible it differs from the DFA.
Consider the conversion algorithm and look at what happens if you have two or more transitions with the same label for a state. This is where you need those new states that correspond to sets of states.
So the question comes down to finding out how many of these superset states are actually reachable. Of course you could invent a fancy algorithm for that, but to get the correct number, simply run the normal conversion algorithm and remove unreachable states.
As for an NFA with n states for which the equivalent DFA has 2^n states think about exploiting non-determinism. The first idea would be to label all transitions the same, however, that doesn't work out too well. Instead remember that you need to be able to somehow reach all subsets of states with some label each.
If you do not count the starting state, then you can do the following construction: create n nodes and for each set out of 2^n create a unique label and in the NFA add a transition with this label to each node of that set. This gives you a NFA with n+1 states (1 being the starting state), where the DFA requires 2^n +1 states. Of course, it gets trickier, once you want to have 2^n DFA states after minimization.