How to find anomalies in wind-sensor TimeSeries data?
Very broad question so this will be a generic/broad answer:
To define anomalies you'll need to think and define what you consider normal. 
Usually we consider two things in terms of (time series) data; 

data availability:
is the data there that you expect? Usually monitorred by looking at a row count over time (are you inserting more or less data than expected)
also counting null values could be used here, but this already leads into the question of data quality:
data quality: 
are the values in ranges you expect? are they in the type/format you expect, etc. 
you can use standard deviations/variance/normal distribution to monitor this. Or hard limit and define which values you accept/expect (min, max for instance)
I have time series data set which contain TimeStamp[hour base] and wind sensor value. I need to find anomalies from this data set.
What are the techniques to find out anomalies ?
How to find anomalies with only these two features ( TimeStamp, sensor-value ) ?