Wind Energy Monitoring and Mitigation Technologies Tool

Brand et al. (2011) tested and compared multiple types of radars. Criteria included automatic tracking, sampling protocols, data streaming, data integration, and data fusion. The Accipiter AR-1 and AR-2 radars were installed at Seattle Tacoma International Airport in 2008 and 2007, and an AR-1 radar was deployed to NAS Whidbey Island in 2007. These sites were used in data streaming, data integration, and data fusion testing. Percentage of called targets confirmed by visual observers was between 52 and 65%.

Willmott et al. (2023) deployed two ATOM systems on two turbines in the Dominion Energy Research lease area off the Virginia (US) coast. The systems were deployed from 1 April to 15 June 2021, 15 August to 31 October 2021, and 15 January to 15 March 2022 and recorded bird and bat activity.

Willmott et al. (2015) analysed data collected by the ATOM system over 16 months (December 2011 to March 2013) at two turbines: one in Delaware (US) and one off the coast of North Carolina (US). Thermographic, ultrasound acoustic, and audio acoustic data were collected and used to evaluate system performance.

Willmott and Forcey (2014) summarize and discuss the deployment and use of the ATOM system off the coast of North Carolina (US) in order to monitor bird activity offshore.

Popper et al. (2022) identified seven research priority areas relating to offshore wind development in the United States. ADEON is identified as an existing source of monitoring data to build upon.

Miksis-Olds et al. (2021) compared backscatter relating to fish and zooplankton observed from three nodes of ADEON which contain multi-frequency echosounder systems. Data from these sites was collected from November 2017 to December 2020 and analyzed for baseline ecosystem patterns.

Miksis-Olds et al. (2018) detail the deployment, calibration, and use recommendations for ADEON. Experimental procedures relating to mobile platform data collection are described as well.

Eaton et al. (2024) described the design of an artificial whale blow and the Awarion camera-based whale blow detection system, as well as initial results of testing the detector on the artificial blow. The system was tested on Vineyard Wind 1, located 15 miles off the coast of Martha’s Vineyard, Massachusetts.

Lagerveld et al. (2020) evaluated various technologies developed to detect bird and bat collisions with wind turbines.

Przybycin et al. (2019) evaluates the first prototypes of B-Finder. Freshly dead birds and plastic objects were dropped with drones or rockets. B-Finder achieved 95% efficiency at distances from 50-100m. Tests were conducted in western Poland from November 1027 - November 2019.

Good et al. (2022) tested the effectiveness of curtailment combined with NRG Systems' Bat Deterrent System to reduce bat fatalities at the Pilot Hill Wind and Kelly Creek Wind Farms in Illinois (US) during fall migration (between 1 August and 15 October in 2018).

Weaver et al. (2020) quantified bat fatalities at the Los Vientos III, IV, and V wind energy facilities in Texas (US) from 31 July through 30 October in 2017 and 2018, and assessed deterrent effectiveness using generalized linear mixed models.

Bellman et al. (2020) determined the noise reductions achieved by three commercially available pile driving noise mitigation methods through a cross-project analysis of 21 project reports produced by companies involved in offshore construction in the North Sea and Baltic Sea between 2012 and 2019.

Dähne et al. (2017) analysed the effects of construction of the DanTysk offshore wind farm (Germany) on harbour porpoises from February to December of 2013 through acoustic monitoring of pile driving noise and harbour porpoise echolocation. Noise reduction was studied for the application of two types of bubble curtains.

Mercader et al. (2019) conducted tank experiments using Biohuts as artificial habitat to observe the relationship between juvenile survival rate and artificial habitat.

Bouchoucha et al. (2016) observed the effects of Biohut implementation on Diplodis species in marinas on the French Mediterranean coast between April and August 2013 and 2014.

Mercader et al. (2017) evaluated the ecosystem effects of 107 Biohuts installed at a large commercial port in the Northern Mediterranean between June and September 2014.

Clausen et al. (2023) Bioseco demand-based wind turbine shutdown was tested as part of a pilot study on automatic bird detection during 2022 to field test at a land based wind windfarm in the district of Segeberg(Germany).

Gradolewski et al. (2021) developed and tested a detection and deterrence system which drew on technologies from previous works (strobing light, sound-based deterrence, artificial intelligence tracking). The system was tested in northern Poland on a land-based wind turbine between May and July of 2020. Validation tests with a fixed-wing drone equipped with GPS and verifying observations by ornithologists have been used to determine the detection efficiency

Nilsson et al. (2018) compared radar systems aimed at bird tracking in southern Sweden from September to November of 2015. Migration intensity, flight direction, and flight speed were evaluated.

Hill et al. (2014) reviewed the various bird detection technologies utilized for bird monitoring at the offshore wind farm alpha ventus in Germany.

Neumann et al. (2009) developed the a fixed pencil beam radar system in order to quantify the migration intensity of birds. The system was developed from ship and military radar systems modified to have greater range and distinguish between avian and non-avian echo signatures

Zehtindjiev et al. (2019) discuss the findings of a year-long study (2018) of the Integrated System for Protection of Birds in Kaliakra, Bulgaria. The study area included 114 wind turbines and bird activity was monitored using three different radar systems: Bird Scan MS1, Deltatrack Radar System, and Radar System Robin.

Michev et al. (2017) observed nocturnal bird migration and anthropogenic bird mortality in Northeast Bulgaria in September, 2014 using the MS1 BirdScan radar system.

Skov et al. (2009) evaluated bird migration levels at the Horns Rev II Offshore Wind Farm, the Horns Rev 1 Transformer Station, and Blåvands Huk from September to November of 2008 using four radar technologies. Birdtracker software was used for flight track identification. Radar data and analysis was compared to visual observations made during the same period.

Hermans et al. (2020) reviewed add-on designs for ecosystem support in offshore wind development. The report provides design drawings for the Cod Hotel.

Degraer et al. (2020) discuss the effects of offshore wind farms on fish populations, particularly as they relate to the introduction of an artificial reef structure (turbine foundation).

Benhemma-Le Gall et al. (2021) observed the effects of construction on harbor porpoise occurrence at two offshore wind farms in Scotland throughout 2017 to 2019 . Harbor porpoise activity was monitored using passive acoustic monitoring (C-PODs) and calibrated noise recorders (SoundTraps and SM2Ms).

Jacobson et al. (2017) estimated the effective harbor porpoise detection area of C-POD passive acoustic monitoring sensors. Population estimates from passive acoustic sensor detection were compared against estimations made with visual observations and a Bayesian model.

Redden et al. (2015) evaluated the performance of different hydrophone technologies by surveying marine mammals in Nova Scotia, Canada from December 2013 to June 2014.

Cryan et al. (2021) applied UV light arrays to a wind turbine in Boulder, Colorado (US) between August 2018 and October 2019 and observed night flying animal behavior using thermal imagery.

Gorresen et al. (2015) illuminated trees with UV in the habitat area of the Hawaiian hoary bat in Hawaii (US) between September of 2009 and October of 2010 in order to observe the effect of the light on bat behavior.

Salkanovic et al. (2020) discusses how artificial intelligence can be used with monitoring technology to reduce wildlife collisions at wind farms in California and Denmark.

Hanagasioglu et al. (2015) data collected using the DTBird and DTBat systems at the Calandawind wind turbine in Switzerland between June 2014 and October 2014. Data collected were compared to data collected by bird and bat specialists.

Flowers (2015) investigated how different technologies including DTbat can integrated into a multi-sensor system to detect avian and bat collisions with turbines through field testing in New Mexico in December of 2013 ( North American Wind Research and Training Center) and in Colorado in October of 2014 (National Renewable Energy Laboratory Wind Technology Center).

Nicholls, A.; Barker, M.; Armitage, M.; Votier, S. (2022). Review of seabird monitoring technologies for offshore wind farms. Report by RPS group. Report for Offshore Renewables Joint Industry Programme (ORJIP).

Terrill et al. (2018) used fixed-wing UAVs to evaluate the performance of the DTBird detection and deterrent-triggering systems at the Manzana Wind Power Project located in Kern County, California (US) between December 2016 and August 2017.

Litsgård et al. (2016) monitored bird movement to evaluate the effectiveness of the DTBird system on a wind turbine near Lundsbrunn, Sweden from July to September 2015.

Hanagasioglu et al. (2015) data collected using the DTBird and DTBat systems at the Calandawind wind turbine in Switzerland between June 2014 and October 2014. Data collected were compared to data collected by bird and bat specialists.

May et al. (2012) evaluated the capability of the DTBird system in detecting birds near the rotor swept area of a wind turbine and in studying the flight patterns of birds close to turbines in Norway. Data were collected with the DTBird system between March and September of 2012 at the Smøla wind-power plant in Norway.

Alliant Energy (2024) In 2020 and 2021 from August to October a study was performed at nine wind project sites in Minnesota and Iowa to evaluate the effectiveness of the EchoSense system in reducing bat fatalities in order for future wind farms to receive permits.

Vallejo et al. (2023) The effectiveness of Echosense was studied at the English Farms Wind Project, located southeast of Montezuma, Iowa between 2020 and 2021. This study tested the system's ability to detect bats and curtail turbine activity accordingly.

Fritchman et al. (2022) EchoSense was used as part of a curtailment research study at the Crescent Wind Project in Hillsdale County, Michigan from May to October of 2021. The study aimed to compare the impact of different curtailment methods, such as blanket curtailment and smart curtailment, on bat mortality.

Corbeau et al. (2021) assessed the use of EchoTrack for tracking bird activity at Land-based wind farms in France.

Becker et al. (2019) used EchoTrack to observe bird activity at a proposed wind farm on the Cape west coast of South African.

Jenkins et al. (2018) utilized EchoTrack radar and software to observe great white pelican activity at a proposed wind facility on the Cape west coast of South Africa.

Sella et al. (2021) evaluated the structural and biological efficacy of the ECO Mat over two years from April 2017 to April 2019 in Florida (US).

Cinti (2021) compared the fish assemblage change associated with the placement of ECO Mat material and control material in Port Everglades, Florida (US).

Nehls et al. (2007) compared the costs and efficacy of three methods of noise reduction in pile driving: bubble curtains, modifications to the pile hammer, and pile sleeves. Bubble curtain technologies compared design, diameter, air supply, water depth, and noise reduction. The EGS Bubble Curtain was larger than other bubble curtains, with comparable noise reduction.

Würsig et al. (2000) developed a 25m radius bubble curtain using hose with 3mm holes every 0.3-0.4m through which air was emitted at 20m^3/minute. The sound reduction produced was evaluated for curtain application around a pile driving operation in Hong Kong in April 1996. Noise reductions ranging from 5 to 20 dB were observed, with the greatest reductions in the 1 - 6 kHz frequency range.