Posts Tagged ‘virtual met mast’

Wind farms are still fairly new technology. In resource assessment, you see this when you look back at the sort of analysis that was done about 5-10 years ago, on older wind farms. To generalise, at the beginning of our industry we greatly underestimated the variability and complexity of the wind. This mostly resulted in an overestimation of the yield.

Differences compared to current best practice include having too few masts; making masts too small and then vertically extrapolating the wind flow to hub height; underestimating uncertainty on the whole procedure and the output prediction; a lack of understanding on how the landscape features would interact with the turbines.

The trouble is that this means that the wind farms which have been designed according to current best practice are pretty new. If it takes 4-5 years to get a wind farm from the stage of measuring the wind through all the technical and non-technical surveys, calculations and checks that have to be done and then through construction, then the best practice of 4 years ago is only just becoming operational. This makes it challenging to compare the actual output with the prediction and thus demonstrate that the current best practice works.

Of course, there are improvements that can be made, and there are several interesting developments of the last few years which are feeding back into best practice.

  • Lidar technology: This is based on radar technology and can measure wind speed using a laser pulse rather than a physical device actually sitting in the wind. That means you can put a lidar on the ground and measure up to 200m up (some models go further than this). While this technology has been around for decades and has been used in the wind industry for at least five years, it’s only relatively recently that the wind industry has really taken the opportunities this presents to heart. The reason for this, to my mind, is about understanding. Lidar measures the wind in a completely different way, averaging over a large area rather than at a tiny point the way previous anemometer technology did. This is a very fundamental difference on what the data are telling you, and frankly none of our tools really understand how to make best use of this. The difference gets most notable as the terrain gets more complicated — so hills and forestry; both of which are often found near proposed wind farms.
  • Computation Fluid Dynamics. Lay English considers a “fluid” to be a synonym for “liquid” but in fact gases are also fluid and therefore the movement of air is best described by fluid dynamics. Computational fluid dynamics or CFD is a way to solve the predictions for the movement of air in an environment which takes in as much information as we can manage about the complexity of the real world. This has become much more important with the rise of offshore, where, we discovered, the wakes of wind turbines behave very much differently than they do on land. Previous models, which were extrapolation and approximation to limit computing time (and which, I should add, do fairly well most of the time and are still both relevant and extensively used), couldn’t provide a reasonable approximation of wind farm wakes offshore. I don’t think CFD is being used much onshore at present, but given how complex the newest wind farms are it won’t surprise me if we begin to see CFD models being performed more often for onshore sites over the next few years.
  • Models: Virtual Met Masts created by meteorologists seem to be very popular at present. These use large scale climate measurements, such as satellite data, to feed into local models and provide detailed predictions of various aspects of the local climate such as wind speed and direction. What I’ve seen of these has been very positive, generally these predictions align well with mast measurements. Still, no scientist worth their salt would ever suggest that real world data could be removed in favour of model outputs: especially with weather and climate the world is complex and the only way to really see what happens out there is to be there measuring it. Where these models come into their own is in trying to establish what the long term climate is like. Anemometers degrade over time, and the landscape itself changes around a mast which has been there for decades. These two facts mean it’s hard to get long term wind measurements with the sort of accuracy the wind industry demands that can give confidence in how the wind at a particular site is likely to be over the lifetime of a proposed wind farm. Models have the potential to be perhaps more consistent.

I suspect that when we look back in five or ten years on the industry now we’ll still see it as a teething period when a lot of initial problems in analysis, measurement, modelling and prediction, let alone actually operating large scale wind farms, still had to be resolved. I don’t know which of these technologies, or perhaps something else entirely, will become the normal face of wind analysis in ten years time. And I find that uncertainty rather exciting.

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