Bats and yield loss

The target of 6000 MW onshore wind in the Netherlands in 2020 will result in a rapidly increasing amount of wind turbines over the next six years, with possibly serious implications for the conservation status of bats. These small flying mammals often travel or feed at hub height. Due to their low reproductive rate, mortality caused by wind turbines could have a serious impact on overall populations.

Wind farm owners must make sufficient effort to prevent adverse effects on bats and their immediate surroundings. Part of this could be that wind turbines have to be curtailed during high collision risk periods in the operational phase. It is unclear what impact this uncertainty has on the business case.

Ecofys conducted an analysis to determine the possible loss of revenue for a small Dutch wind farm, based on assumptions about the behaviour of bats. We calculated the loss in production (% and GWh)  due to possible turbine curtailment during bat active periods. Firstly wind yield information was gathered and weather data was obtained from the Royal Dutch Meteorological Institute (KNMI). With this information we could determine the bat active period (<7bft, >7°C, no rain). It was assumed that the percentage of bat activity equals the percentage production loss caused by curtailment. The percentage production loss could then be offset against the net energy yield.

Based on this quickscan we concluded that the annual loss in revenue caused by bat activity and turbine curtailment could be significant. We therefore advise wind farm owners to investigate this in more detail, early in the project development phase, in combination with wind resource measurements and bat surveys. With this cost-effective approach the wind speed criterion can be better defined, after which the yield reduction can be modelled based on annual LiDAR wind measurements at different heights. With such a time series model, it is also possible to simulate different strategies for the control system and to validate the national bat prediction model. It is likely that this will reduce the expected yield loss.


Huygen van Steen
Energy Systems and Markets
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