The FFT decomposes the signal in frequency, generating a complex spectrum with both positive and negative frequencies, depending on both amplitude and phase relationships. We are now not interested in the phase.
Fixing a frequency, the absolute amplitude for positive frequency is the same of that in the negative part. So, in order to recover the amplitude, we can consider just the positive spectrum. In this case we will have the amplitude divided by 2. Furthermore, if the FFT is taken over N points the amplitude at the output of the FFT will be N times the actual amplitude for the considered frequency.
Then considering the positive spectrum of a N points FFT we will have to multiply by 2/N in order to recover the peak amplitude.
Then the peak amplitude of a given frequency, considering the complex spectrum, will be:
2/N*sqrt[re(V)^2+im(V)^2]
Now applying this to all, let's suppose K, frequencies we have to sum them in power, that is:
\[2/N*\sqrt{\sum_{n = 1}^K [{Re(Vn)}^{2}+{Im(Vn)}^{2}]}\]
since we want the RMS we have to divide by \[\sqrt{2}\], then:
\[\sqrt{2}/N*\sqrt{\sum_{n = 1}^K [{Re(Vn)}^{2}+{Im(Vn)}^{2}]}\]
With respect to your second equation, in my derivation, the square root and the sum are exchanged: are you sure to have written them in the correct order ? Furthermore the maximum index of the sum "K" and the number of points of the FFT "N" have not to be confused.