The sum of normally distributed random variables is also a normally distributed random variable.
Given [tex]n[/tex] random variables with [tex]X_i\sim\mathrm{Normal}(\mu_i,\sigma_i^2)[/tex], their sum is
[tex]\displaystyle\sum_{i=1}^n X_i \sim \mathrm{Normal}\left(\sum_{i=1}^n \mu_i, \sum_{i=1}^n \sigma_i^2\right)[/tex]
i.e. normally distributed with mean and variance equal to the sums of the means and variances of the [tex]X_i[/tex].
In this case, each of [tex]X_1,X_2,X_3[/tex] are normally distributed with [tex]\mu=4[/tex] and [tex]\sigma^2[/tex] = ... I'm not sure what you meant for the variance, so I'll keep it symbolic. Then
[tex]V = X_1+X_2+X_3 \sim \mathrm{Normal}(12, 3\sigma^2)[/tex]