BUG: to_datetime with utc=True for Series
#### Code Sample, a copy-pastable example if possible

```javascript
In [2]: ts = 1.4884427244831782e+18

In [3]: pd.to_datetime(ts, utc=True)
Out[3]: Timestamp('2017-03-02 08:18:44.483178240+0000', tz='UTC')

In [4]: pd.to_datetime([ts], utc=True)
Out[4]: DatetimeIndex(['2017-03-02 08:18:44.483178240+00:00'], dtype='datetime64[ns, UTC]', freq=None)

In [5]: pd.to_datetime(pd.Series([ts]), utc=True)
Out[5]: 
0   2017-03-02 08:18:44.483178240
dtype: datetime64[ns]
```
#### Problem description

The argument ``utc=True`` in function ``to_datetime`` is not working when passing a ``Series``, differently from other case, e.g. when passing a list or a scalar Unix timestamp.

#### Expected Output
The expected output is the same as the one given by

```javascript
In [6]: pd.to_datetime(pd.Series([ts])).dt.tz_localize('UTC')
Out[6]: 
0   2017-03-02 08:18:44.483178240+00:00
dtype: datetime64[ns, UTC]
```

#### Another example: `tz_convert`
It is straightforward to convert to another time zone from a Unix timestamp or list:
```javascript
In [7]: pd.to_datetime(ts, utc=True).tz_convert('Europe/Paris')
Out[7]: Timestamp('2017-03-02 09:18:44.483178240+0100', tz='Europe/Paris')

In [8]: pd.to_datetime([ts], utc=True).tz_convert('Europe/Paris')
Out[8]: DatetimeIndex(['2017-03-02 09:18:44.483178240+01:00'], dtype='datetime64[ns, Europe/Paris]', freq=None)
```
whereas for a `Series`:
```javascript
In [9]: pd.to_datetime(pd.Series([ts])).dt.tz_localize('UTC').dt.tz_convert('Europe/Paris')
Out[9]: 
0   2017-03-02 09:18:44.483178240+01:00
dtype: datetime64[ns, Europe/Paris]
```

#### Output of ``pd.show_versions()``

<details>
INSTALLED VERSIONS
------------------
commit: None
python: 3.5.2.final.0
python-bits: 64
OS: Linux
OS-release: 3.13.0-113-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: ca_ES.UTF-8
LOCALE: ca_ES.UTF-8

pandas: 0.19.2
nose: 1.3.7
pip: 8.1.2
setuptools: 27.2.0.post20161106
Cython: 0.24.1
numpy: 1.11.1
scipy: 0.18.1
statsmodels: 0.6.1
xarray: None
IPython: 5.1.0
sphinx: 1.4.6
patsy: 0.4.1
dateutil: 2.5.3
pytz: 2016.6.1
blosc: None
bottleneck: 1.1.0
tables: 3.2.3.1
numexpr: 2.6.1
matplotlib: 1.5.3
openpyxl: 2.3.2
xlrd: 1.0.0
xlwt: 1.1.2
xlsxwriter: 0.9.3
lxml: 3.6.4
bs4: 4.5.1
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.13
pymysql: None
psycopg2: None
jinja2: 2.8
boto: 2.42.0
pandas_datareader: 0.2.1
</details>
