As it approaches an obstacle (i.e. the blockage), wind flow slows down and diverts around it (a blockage effect). A similar slowdown occurs upstream of a wind turbine. This is also a blockage effect, but it is more often referred to as turbine induction. This effect has been well-known since the start of the wind industry.

There are many blockage-related effects that occur in a wind farm. Some are addressed in longstanding wind energy practices, but others are not. It is the unaccounted-for blockage effects that have led to bias in commonly used energy prediction methods.

An accurate prediction of a wind turbine’s energy production requires knowledge of how that turbine operates in isolation and an accurate estimate of how that production changes when the other wind farm turbines are present. Unaccounted-for blockage effects likely cause prediction bias in both areas.

Traditionally, when calculating these turbine interaction losses, the industry has used what’s known as the “wakes-only” approach. In this approach, a turbine can only affect turbines located downstream — any influence on turbines upstream or to the side is almost always ignored. In other words, the front row of turbines at a wind farm, collectively and individually, are assumed to produce the same amount of energy as they would operating in isolation.

Measurements and high-fidelity simulations, however, indicate that front row turbines very likely produce less energy than they each would in isolation, due primarily to wind-farm-scale blockage effects — and the related prediction bias extends to the entire wind farm.

The above is an extract from an article written for Recharge by Stefanie Bourne of DNV GL, which can be read in full here.

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