As is so often the case with buzzwords, since the term was coined by NASA researchers in the late 1990s it has been looked on with weary scepticism by some and with almost religious zeal by others.
But in the last few years, big data has made the leap from an interesting-but-vague concept to a very real part of the mainstream. The digital revolution has focused the attention of businesses and governments on the big problems - and even bigger opportunities presented by truly mind-bending amounts of information. So significant are the implications of big data that some observers have gone as far as to describe data as a third factor of production, alongside labour and capital.
Data and its analysis now plays a fundamental role in almost every industry, with wind energy no exception - and it is about more than just weather data. As well as influencing design choices by manufacturers and power system operators, operational data is particularly relevant to wind-farm owners seeking to wring the greatest possible value from their assets.
Volume, variety, velocity
Getting to grips with operational data means mining huge amounts of Scada (supervisory control and data acquisition) output alongside a host of other information, including condition-monitoring data such as gearbox oil samples, acoustic-sensor data and mechanical-loads measurements, along with operations-and-maintenance reports and end-of-warranty inspections.
"Big" data sets are considered to be ones that are large in three dimensions, known as the three Vs: volume, variety and velocity. Even a relatively small wind turbine can produce terabytes of information each month, from a wide range of sources, in real time. It is safe to call wind-turbine operational data "big" - and there is a growing understanding of how to put this data to use.
An excellent example of a profitable application of large volumes of operational information is the ability to make predictions about the economic life-expectancy of individual turbines or wind farms. When Portuguese utility EDPR performed a technical review of 153 of its wind farms in 2011, a component lifetime fatigue analysis did not result in any wind farms being repowered, as was expected. Instead, the study concluded that it was possible to extend the project life of the assets from 20 to 25 years, resulting in a $29 million positive impact on their bottom line.
Ownership is key
But making the most of wind turbine data is not as straightforward as it might seem. The first difficult question to ask is: "who owns the data?". As previously discussed in this column, (“uåX˜äŠÊ˜·³Ç July 2013, Owners Will Decide Who Wins Service Battle in US) a number of parties, including manufacturers, owners, system operators and service firms, may value access to the information, but the costs and benefits are not distributed evenly.
As well as the nature of the data being produced, the identity of the holder of the intellectual property (IP) is significant for the way the wind industry does business. If the manufacturer retains the IP generated by a turbine, it can be combined with similar data from around the world to improve turbine designs but this may limit the data the operator of a particular site has access to. Similarly, if the owner collects and keeps the data, it may allow them to make better operational decisions, but it might make life tough for third party services providers. A deeper understanding of wind turbines and wind-farm sites provides benefits for the wind industry as a whole.
By improving turbines and their operation, making sense of operational data will allow wind energy to take decisions that deliver lower cost of energy to end users - which is good for everyone. But, as we rush to put theory into practice, we should remember something that Albert Einstein and Frank Zappa both pointed out: "information is not knowledge". Realising the full potential of operational data will require collaboration and creativity. Fortunately, these are two strengths intrinsic to our wind energy industry.
Oscar Fitch-Roy is a senior policy consultant in the renewables advisory division of DNV GL
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