Multi-sensor Monitoring System for Determination of Bird Behaviour in Wind Farms

Compliance with regulatory requirements increasingly demands clear evidence on how birds behave within and around wind farms. To meet this demand, a consortium of research institutes and innovation firms engaged with... [ view full abstract ]

Compliance with regulatory requirements increasingly demands clear evidence on how birds behave within and around wind farms. To meet this demand, a consortium of research institutes and innovation firms engaged with environmental monitoring technologies is developing a multi-sensor monitoring system designed to provide robust data on real life bird behaviour at and within a wind farm. In the past, monitoring of bird behaviour in wind farms has been focused on the application of single sensors, like bird radars, used by observers or as an automated operation detached from the wind farm control system. Using a network of state of the art technology such as high definition radars, thermal imaging cameras, bird lidar and acoustics in digital communication, bird behaviour can be monitored more efficiently over parts or entire wind farms. The sensors involved are currently at different technology readiness levels. A camera system in digital communication with one or more radars has been tested in an offshore wind farm since July 2014, and is fully prepared for application in onshore and offshore wind farms. Depending on air space coverage (2D/3D) needed, the radar solution may be both in the form of a single radar and as a network of medium- and long-range radars. The digital communication with the cameras allows coverage and species identification day and night in real time. The integration of bird lidar with the radars and cameras is being tested in a wind farm during 2016-2017, and capitalises on development of novel lidar application for bird monitoring. The addition of lidar to the sensor system will enhance the potential for achieving long-range identification of bird targets at the species group level. The addition of acoustics will enable identification of bat species approaching the wind farm in real time. The multi-sensor system is controlled by a FPGA based Data Aqusition and Preprocessing System and software for controlling the data stream, automated tracking, geo-referencing and interfacing. The speed of advancement of the next generation multi-sensor system providing automatic recordings of 3-dimensional track data at species level will depend on available R&D funding and support and collaboration from industry.