I might know what's going on. The Z-score is defined as 
$$
z = \frac{x-\mu}{\sigma}
$$
where $\mu$ is the mean
and $\sigma$ is the standard deviation(SD).

In your example, $\mu = 30$, $x = 60$ and $\sigma = 2$. 

Using the formula directly, the Z-score of your observation is 

$$z = \frac{x-\mu}{\sigma} = \frac{60-30}{2} = 15$$ 

In another words, $x = \mu + 15\sigma$. Directly interpreting this formula, you can say that your score, $x$ is 15 SD away from the mean. 

On the other hand, you can expand the Z-score formula in this way: 
$$
z = \frac{x}{\sigma} - \frac{\mu}{\sigma}
$$

By putting your numbers, you get 

$$
\begin{align}
\frac{x}{\sigma} & = z + \frac{\mu}{\sigma} = 15 +\frac{\mu}{\sigma}
\end{align}
$$

With this formula, you can describe your score as your score per SD is 15 away from the mean per SD. 

They are different ways of looking at the same Z-score.