WWind turbine data analysts who have spent any time thinking about power curves will know how wonderfully versatile they are, with so much information distilled in two dimensions: power and wind speed.
I challenge myself with a quick brainstorm to think of ten types of analysis where a power curve can be used. So here goes:
...further suggestions welcome! So there really is power in the curve. But as with many things in life, things are not quite as simple as they might first seem. The main problem can be found on the x-axis. Limited sensor accuracy and complex flow effects both in front of and behind the rotor mean that it is extremely difficult to measure the value of wind speed equivalent to upstream, undisturbed, homogeneous and stable conditions.
However, a quick check against my list above reveals that the majority of these methods can be applied effectively using an only an estimate of local flow conditions. In most cases, what we are interested in are relative rather than absolute trends. We can consider our wind turbine as a large sensor, placed in the flow to see how much energy can be extracted. The response of the rotor is a good indicator of the relevant flow conditions seen by the turbine.
This is great news for the pragmatic analyst looking to extract maximum value from the information available. So I conclude that in the land of operational data analytics, the power curve is king!