ORJIP Bird Collision Avoidance Study. Sonja Pans (DHI Water Environments UK Ltd)

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1 ORJIP Bird Collision Avoidance Study Sonja Pans (DHI Water Environments UK Ltd) 1

2 Consenting risk is a major issue for offshore wind The challenge Before a wind farm can be built, developers must be awarded consent but Consenting decisions depend on the risk of environmental impact Developers to prove that the risk is acceptable Two most notable environmental impacts Birds fatalities due to collision, and population displacement Marine Mammals injury from high levels of underwater noise due to construction, and population displacement Due to a lack of empirical scientific data, consenting authorities are very cautious when making their decision 2

3 Offshore Renewable Joint Industry Programme (ORJIP) Reducing the Risk of Consent The Solution ORJIP set up in 2012 by DECC, The Crown Estate, Marine Scotland and 16 offshore wind developers Objective: to reduce consenting risk for offshore wind farms through: funding research projects to better inform consenting authorities on the true environmental risk of offshore wind Based on the good reputation of OWA, in 2013 Carbon Trust was contracted to manage the ORJIP programme Four initial key research projects to reducing the risk of consenting to offshore wind A programme open to all countries 3

4 Bird collision avoidance study Objective: To improve the evidence base informing bird collision avoidance rates to inform consenting decisions 15 Participants: DONG Energy, EDF, Eneco, Fluor, Mainstream Renewable Power, RWE, Scottish Power Renewables, Siemens, SSE, Statoil, Statkraft, Vattenfall, DECC, The Crown Estate and Marine Scotland Approach: Niras and DHI contracted to install state of the art monitoring equipment at Vattenfall s Thanet Offshore Wind farm to monitor micro, meso and macro bird avoidance behaviours. Duration: 2.5 years, starting March 2014 Benefits: Study outcomes accepted by SNCBs Empirical evidence to improve collision risk models Greater certainty on the true risk of bird collisions 4

5 Project Aims Select suitable equipment to measure: Macro avoidance behaviour Meso avoidance behaviour Micro avoidance behaviour If appropriate, collision impacts Outputs: (1) robust evidence on rates of avoidance and collision for 5 key species (2) Determine how these data can be applied to support consenting applications Location: one or more offshore wind farms 18/05/

6 Monitoring System SCANTER 5000 radar LAWR 25 surveillance radars Thermal Animal Detection System (TADS) digital/ thermal camera systems Vectronix 21 Aero laser rangefinders with Observer Deployed: 1 Deployed: 3 Deployed: 2 Deployed: 2 Range: 12km Range: 8km Radar to be used to direct camera onto target Targets identified to species by person back in lab Operator can fire at target every seconds to record distance and altitude (accuracy of 0.2 ) logged automatically via GPS 18/05/

7 Thanet Site Layout Design 18/05/

8 Step 1: Test and validate monitoring system Avoidance behaviour measured Macro Meso Micro Change in flight direction & altitude indicating avoidance of wind farm perimeter Change in flight direction and altitude indicating avoidance of rotor swept zones within the wind farm perimeter flight behaviour indicating responses to single blade(s) within 10 m of rotor swept zone Two types of radar Rangefinders with observers Two types of radar Rangefinders with observers Automated radar-camera tracking Automated radar-camera tracking 18/05/

9 Step 2: Baseline analysis and applicability of project outputs Goal To provide context, maximise the usefulness of the data to be gathered and to inform a more detailed understanding of the assumptions that would be made when applying the findings of this study to other wind farm proposals. Outcome The Study Design has been refined to maximise the usefulness of the data to be gathered. When applying the findings of this study to other wind farm proposals, the following assumptions should be applied: Seabird abundance data is known/available Modelled weather data is known/available Data on turbine characteristics are known/available 18/05/

10 Step 3: Installation of Equipment and Data Collection All equipment installed and commissioned in August 2014 Performing at, or above, expectations 18/05/

11 LAWR radar and Camera in situ 18/05/

12 Examples of Rangefinder use Images not taken at Thanet 18/05/

13 Radar tracks recorded Species names Number of tracks Combined radar tracks from the two observer platforms G01 and G05 Period: August- November Northern gannet 37 Herring gull 2 Lesser black-backed gull 3 Great black-backed gull 4 Black-legged kittiwake 8 Gull unid. 3 Red-throated diver 1 Black-throated diver 2 Brent goose 1 Pink-footed goose 2 Cormorant 1 Wigeon 1 Common gull 1 Black-headed gull 1 Common guillemot 1 Large auk unid 2 Thrush unid 1 Total 72 18/05/

14 Laser rangefinder tracks Species names Number of tracks Tracks from the two observer platforms G01 and G05 Period: July- November Northern gannet 142 Herring gull 61 Lesser Black-backed gull 79 Great Black-backed gull 74 Black-legged kittiwake 19 Gull unid. 11 Red-throated diver 1 Fulmar 1 Brent goose 4 Pink-footed goose 2 Common scoter 1 Cormorant 6 Wigeon 1 Great skua 1 Common tern 10 Arctic tern 2 Comic tern 1 Sandwich tern 9 Common gull 8 Black-headed gull 1 Common guillemot 1 Razorbill 1 Total /05/

15 TADS and Radar combination Tracks obtained by both TADS cameras and LAWR radars Period: 24 October 25 November Species names Number of tracks Gannet 10 Kittiwake 86 Large gull 578 Small gull 56 Gull 70 Sea duck 5 Divers 1 Fulmar 1 Unidentified 1 seabird Total /05/

16 Summary of progress Data collected for all key species Macro Meso Micro Northern gannet Herring gull Lesser blackbacked gull Great blackbacked gull Black-legged kittiwake 18/05/

17 Next steps Full programme designed to run until early 2017 Periodic interim reporting of results built into project Focus monitoring effort during the period of peak abundance of species Focus on providing robust sample sizes (Timetable reviewed regularly) Options within the project programme for further data collection if required 18/05/

18 Thank you NIRAS Tim Norman Ian Ellis DHI Sonja Pans Henrik Skov DOF Mark Desholm 18