Posters

Abstract

Increasingly, bat and bird detection technologies are installed on operating wind turbines in order to protect wildlife. Preventative measures include switching turbines off for periods of time or increasing the cut-in speed of the turbine. Both measures result in reduced annual energy production (AEP). In order for such losses to be factored into the revenue projections of the project proponent, consultants need to be able to simulate the likely losses due to curtailment. In order to run said simulations, field data is needed as well as a methodology for turning those measurements into a robust loss calculation.  Dynamic wildlife detection, and even deterrence using sound propagation, is an applied solution for operational wind farms. However, estimating its impact during the pre-construction phase is a relatively new area. Current tools effectively address static plans, such as calendar-based turbine stops or those triggered by wind speed and temperature thresholds. In contrast, dynamic solutions detect flying wildlife and stop turbine operation based on predefined protocols. The intermittency of real-time data requires careful modelling to accurately reflect its impact.  Throughout this work, monitoring data similar to that which would be collected at a greenfield site, is used to simulate the losses for a built wind-farm equipped with bat detection and wildlife protection solution. The simulated losses are then compared with the energy production and shutdown data from the wind-farm.  This study is the result of a collaboration between renewable energy advisory engineers, who contribute expertise in wind energy estimation modeling and analysis, and wildlife monitoring technology experts, who provide bat detection systems for pre-construction sites. Real bat detection data from a wind farm located in the Netherlands has been integrated into wind farm design and optimization software to simulate the impact of three turbine shutdown protocols.