Wind Energy Monitoring and Mitigation Technologies Tool

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).

2025–2027 – National Offshore Wind Research & Development Consortium System-level development and validation of a bio-inspired uncrewed underwater vehicle for benthic surveys and offshore wind environmental monitoring.

2024 – U.S. Department of Energy SBIR Phase I Laboratory accelerated life testing and early-stage field deployment of water metering systems with energy harvesting capabilities are being conducted to evaluate durability, reliability, and integration under operational conditions.

2023 – U.S. Department of Defense Navy SBIR Extreme shallow-water (<3 ft) pico-marine hydrokinetic (pico-MHK) testing was conducted at forward operating bases to de-risk system performance at higher output levels.

2022 – Los Angeles Cleantech Incubator Stakeholder engagement and private investment activities supported technical validation and commercialization strategy development. While not a laboratory test, this phase advanced system readiness through industry interface and market positioning.

2022 – NOAA Ocean Observation Challenge Wave basin testing was conducted at the U.S. Navy Carderock facility to evaluate ocean instrumentation integration and data collection performance.

2021 – U.S. Department of Energy TEAMER Program Computational fluid dynamics simulations and controlled flume testing at the Stevens Institute were performed to validate an autonomous underwater vehicle concept with integrated energy harvesting capability.

2021 – California Energy Commission Laboratory validation of piezoelectric energy harvesting performance under large cyclic mechanical stresses was conducted to evaluate power generation efficiency and durability.

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.

Mellor et al. (2007) trialed the HiDef aerial survey technique for seabirds at windfarm sites. They found the system provides sufficient detail to enable reliable identification of birds in most cases and that operating at altitudes in excess of 1 km are feasible, although cloud-base would be a limiting factor. Despite higher wind speeds than would be tolerated on a conventional survey, all birds were observed on most transects with a high degree of confidence.

Elmer (2018): With a Hydro Sound Damper (HSD) in place, sound was measured at a distance of 6m from the pile, 4m above ground, to record sound levels during pile driving in the German Baltic Sea. Results (a 23dB reduction in noise level) indicated 99.5% of the whole sound energy was damped out by the HSD net.

Elmer et al. (2014) evaluated the noise reduction capacity of the Hydro Sound Dampener during the installation of offshore wind turbines at several locations including the London Array wind farm (Great Britain) and the Amrumbank-West wind farm (Germany) in the North Sea.

Delprat et al. (2011) presented the concept of the ID stat system at the Conference on Wind energy and Wildlife impacts in Norway in May 2011. A small scale study of the technology was scheduled for March 2012 at an Land-based wind turbine.

Delprat & Alcuri (2011) presented at the Conference on Wind Energy and Wildlife Impacts on the 2nd-5th of May 2011, in Trondheim, Norway.

Duerr et al. (2023) analyzed the effectiveness of IdentiFlight system's ability to identify different bird species at the Manzana Wind project, in Kern County, California (US) from June 2018 - 2019.

Huso & Dalthorp (2023) assessed Identiflight's ability to reduce eagle mortality at Campbell Hill wind farm in Wyoming (US) from August 2018 - 2022.

Rogers (2022) evaluated the efficacy of the Identiflight Avian Detection System at the Castle Hill Wind Farm in Tasmania from August 2020 to February 2022.

McClure et al. (2022) evaluated IdentiFlight's ability to mitigate collision mortality of bald and golden eagles at a wind facility in Wyoming (US).

Rolek et al. (2022) evaluated Identiflight at Top of the World Wind Power Facility in Wyoming (US) from May 2018 to March 2019 and at The Manzana Wind Power Project, in Kern County, California (US) from June 2018 to March 2020.

Aschwanden et al. (2020) monitored bird movements to assess the effectiveness of the IdentiFlight system at the Wind Energy Research Cluster South in Stötten, Germany between April and May 2020.

McClure et al. (2018) used human observation to test and compare the ability of IdentiFlight to detect, classify, and track birds at the Top of the World wind farm in Wyoming (US) from August to September 2016.

Deng et al. (2021) designed a animal tracking transmitter with the goal of reducing weight and increasing transmission range. Drones were used to assess the effective range of the transmitter near Richland, Washington (US) in December 2021.

Deng et al (2019) implemented three designs of animal tracking transmitters aimed at tracking bats for applications in wind energy. Lab scale testing and algorithm validation were undertaken in 2018.

Koschinski & Lüdemann (2020) discuss the first commercial application of the Integrated Monopile Installer in 2012 at the German OWF Riffgat in the North Sea. Since then the Integrated Monopile Installer has been used on over 450 piles. Noise reduction was decreased to a range of 13 to 16 dBSEL.

Rose et al. (2019) analyzed data collected during the construction of Gescha 1 & 2 from 2010 to 2016 to investigate the effects of different types of noise mitigation on harbour porpoises.

Booth et al. (2013) illustrate how the iPCoD protocol can be used to consider the potential effects of constructing two hypothetical wind farms off the Aberdeenshire coast on the five priority species over two years in their relevant management units. Additionally, they investigate the cumulative effects of the simultaneous operation of a hypothetical tidal energy installation.

McKay et al. (2024) described bat community dynamics at a Norwegian wind farm located in boreal forest. They used Kaleidoscope Pro to process bat acoustic data collected between July - September in 2020. They found evidence to suggest possible direct and indirect effects to bat communities.

Peterson et al. (2021) investigated whether acoustic bat data collected at wind farms can provide accurate measures of bat fatality risk. They used Kaleidoscope Pro to analyze bat acoustic data collected at the New Creek wind farm in West Virginia in September 2011 and May 2017. They found that measuring exposure of acoustic bat activity provided a quantitative basis for designing, evaluating, and adaptively managing curtailment strategies.

Richardson et al. (2021) assessed bat activity at paired turbine and control locations at 23 British wind farms. They used Kaleidoscope Pro to process bat calls and classify calls to species level. P. pipistrellus activity was 37% higher at turbines than at control locations, which may explain why Environmental Impact Assessments conducted before the installation of turbines are poor predictors of actual fatality rates.

Hylkema et al. (2023) compared two types of artificial reefs in the Caribbean (2018) by examining fish assemblage, territorial behavior and grazing intensity between reef balls and layered cakes.

Hylkema et al. (2020) compared three types of artificial reefs in the Caribbean (2018) by examining the early fish colonization rates between reef balls, layered cakes, and piles of local basaltic rocks.

Loring et al. (2021) measured the movements and flight altitudes of 12 species of shorebirds using VHF transmitters, tracked using the Motus Wildlife Tracking System. The Motus Wildlife Tracking System has extensive coverage from automated radio telemetry stations distributed across Eastern North America and additional coverage at key shorebird sites from Arctic Canada to South America. This study aimed to provide information on offshore movements and flight altitudes of high-priority bird species in order to inform decisions on the development of offshore wind energy facilities in the Atlantic Outer Continental Shelf.

Loring et al. (2019) used digital VHF transmitters (NanoTags) to track the offshore movements of three bird species over Federal waters and Wind Energy Areas. Lotek tags were helpful in assessing collision risks in Wind Energy Areas by tracking frequency and extent of offshore movements of these bird species.

Robert et al. (2016) developed and experimentally tested an array of sensors that continuously monitors for interactions of birds and bats with wind turbines, including Allied Vision's Manta camera. They tested the Manta 201 - C and found the stereo visual Manta cameras had a resolution of 1624 x 1234 and sampled at 6 fps with a 52° field of view lens.

Coolen et al. (2025) evaluated the MGST at the Hollandse Kust Zuid offshore wind farm in 2023. The tool successfully collected 21 biofouling samples with high precision at depths of 4.5–20 m. The three scraper types tested (one metal, two plastic) showed no significant differences in sample quality, species richness, or abundance of scraped biofouling. All scraper types caused negligible damage to turbine coatings.

Guazzo et al. (2019) explored the use of Toyon Research Corporation's detection system to observe North Pacific gray whales. They used a combination of visual sightings, acoustic calls, and infrared camera data on blow detections to calculate the cue rates of migrating eastern North Pacific gray whales in January 2015

May et al. (2017) evaluated the detection ranges of the MERLIN Avian Radar by using an unmanned aerial vehicle to simulate various flight patterns and bird sizes. The study took place off the coast of Central Norway in August 2009.

Skov et al. (2016) utilized the MERLIN Avian Radar in a study of soaring migrants and their attraction to an offshore wind farm in Denmark during the autumn raptor migration in 2010 and 2011.

Fijn et al. (2015) implemented the MERLIN Avian Radar system at the Dutch offshore wind farm Egmond aan Zee from June 2007 to May 2010 in order to study bird flight intensity in the rotor swept zone (25m-115m) over the North Sea. The Merlin system was used to observe fluxes as well as flight altitudes and paths.

Krijgsveld et al. (2011) studied the collision risks and barrier effects of birds due to the Offshore Wind farm Egmond aan Zee in the Netherlands using the MERLIN Avian Radar System between April 2007 and June 2010.

Moron et al. (2018) recorded Clymene dolphin whistles in the Southwest Atlantic Ocean in 2016 using a Night Hawk III four-element towed array.

Verfuss et al. (2017) compared and discussed a variety of methods suitable for monitoring marine mammals in low visibility conditions during seismic surveys, including the Night Hawk system.

Ryu et al. (2024) tested the system on a dataset of over 800,000 images of bats, birds, insects, and non-biological objects. The system identified bats at a success rate of 93%, birds at a success rate of 94%, insects at a success rate of 83%, and non-biological objects at a success rate of 99%.

Elzinga et al. (2019) tested the Noise Mitigation System at the Butendiek and Luchterduinen Offshore Wind Parks in the Netherlands in the fall of 2018.

Wochner (2019) discussed the three approaches to reducing noise from pile driving: reducing at the source, breaking the transmissions path, and noise absorption.

Clausen et al. (2019) examined the performance of different passive acoustic monitoring filters and detectors in varying ocean noise environments. The PAMGuard system was used to analyse harbour porpoise clicks and ambient noise data collected in the spring of 2013 and summer of 2014 in the west of Denmark.

Sarnocinska et al. (2017) observed harbor porpoises in the Danish Great and Little Belts between June and November, 2015 with C-PODS and PAMGuard. The accuracy of both methods was compared.

Keating et al. (2013) describe the beaked whale detectors and classifiers used during beaked whale surveys in Southern California (US) in the summer and fall of 2012.

Yack et al. (2009) evaluated the efficacy of using PAMGuard software (version 1.0) to detect cetaceans in marine environments by comparing manual detections to those made by PAMGuard during a SWFSC dolphin survey conducted in the eastern tropical Pacific Ocean from 20 August to 28 November, 2007.