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At least 19 records

Technology Acceptance Workshop Meeting Proceedings, April 20-29, 2022

The Renewable Energy Wildlife Institute and the National Renewable Energy Laboratory convened a virtual workshop facilitated by the Consensus Building Institute in April 2022 to identify recommendations on how to accelerate the rate of research and development, evaluation, and adoption of technologies for monitoring or minimizing wildlife impacts from wind energy. The workshop drew on expertise from stakeholder groups including technology developers, federal agencies, conservation nonprofits, and the wind industry. Over the course of four sessions, participants discussed incentives and barriers to technology development beginning with early field testing and validation, through full-scale experimental deployment, and finally broad-scale acceptance and commercial deployment.

17 WIND ENERGY↗

Chapter 6: Wind Energy: Effects on Bats

Utility-scale wind energy facilities require no fuel, consume no water, and produce no greenhouse gas emissions or other pollutants during energy production. Wind power currently supplies approximately 6.4% of the electricity consumed in the United States (U.S.), with continued growth expected in the coming years. Although further expansion of wind power is anticipated to provide environmental and economic benefits, there are increasing concerns about bat fatalities occurring at wind energy facilities across North America. Recent estimates place the number of bat fatalities in the several hundreds of thousands on an annual basis, and that number is projected to rise. As a result, population-level impacts of wind turbine-caused mortality are of increasing concern. For example, modeling efforts for a widespread species, the hoary bat (Lasiurus cinereus), indicate that the population could decline by 90% within 50 years, assuming no growth in installed wind power capacity and no significant implementation of conservation measures. Given increasing demand for wind energy and increasing evidence suggesting that bats are attracted to wind turbines, the need to develop cost-effective and practical impact minimization strategies is a high priority. Current strategies include siting restrictions and operational minimization, both of which limit wind power generation. Potential solutions that do not limit power generation include broadcasting ultrasound from wind turbines or using ultraviolet (UV) light to deter bats from approaching and entering the rotor-swept area where fatalities occur. Another possible solution is the development of turbine-surface materials that reduce the relative attractiveness of wind turbine towers to bats. In this chapter, we provide a succinct summary of known impacts of wind energy on bats and present current and future research priorities. We also describe the challenges and opportunities associated with developing and implementing effective solutions to minimize wind turbine-caused bat fatality.

17 WIND ENERGY↗

New frontiers in wind-wildlife monitoring systems

Effective minimization of negative effects of wind energy on wildlife is an iterative process whereby direct observations of wildlife effects inform and validate mitigation strategies. Yet, the full implementation of this adaptive management has been hindered by a lack of appropriate data. The accurate, high-resolution data required exceeds the capacity of most current monitoring approaches (human observers or monitoring technologies applied in isolation). Current applications of monitoring technologies struggle to harness their full potential by failing to capitalize on opportunities for integration with additional technologies and/or by having limited temporal and spatial resolution. At the emergence of this new frontier of wildlife monitoring, we review the elements of a robust wind-wildlife monitoring system and highlight sensor fusion principles that facilitate effective implementation and integration of multiple monitoring technologies. We also illustrate how sensor fusion solutions can generate high resolution data on collision and displacement effects on terrestrial wildlife across complex spatial and temporal scales.

17 WIND ENERGY↗

Wind Beneath Your Wings

Advances in wind turbine technology and the need for renewable energy resources drive the rapid expansion of the wind industry in the Unites States and abroad. In 2019, wind energy overtook hydropower as the most-used source of renewable energy generation in the country, producing 300 million megawatt-hours of electricity or roughly 6% of the nation's total power output. Continuing this rapid expansion while also protecting wildlife requires more efficient and cost-effective wind-energy-wildlife impact monitoring and minimization technologies. The National Renewable Energy Laboratory's (NREL's) wind energy program offers unparalleled expertise in environmental science and wildlife impact mitigation, helping project partners develop and validate their ideas.

Altamont Pass↗

Idaho & Oregon Agriculture: Monitoring Vegetation Impacts of Livestock Management Practices Used to Reduce Predator Conflicts on Idaho and Oregon Grazing Allotments

The practice of night penning, which involves corralling livestock into a fenced, secure area overnight, aims to safeguard animals from predators. Although this method has proven successful in minimizing interactions between livestock and wildlife, the extent of its impact on vegetation communities is still being explored. This project examines the feasibility of using Net Primary Productivity (NPP) values from the Rangeland Analysis Platform (RAP) to quantify the impacts of night penning on rangeland vegetation communities. RAP provides spatially distributed values of vegetation composition, cover, and productivity, and is derived from imagery from Landsat 5, Landsat 7 & Landsat 8 at a 30m resolution for rangelands across the United States. Our DEVELOP team partnered with Alderspring Ranch, Krebs Livestock, and the U.S Department of Agriculture Animal & Plant Health Inspection Service (APHIS) to analyze the impacts of night penning on vegetation communities. We identified control sites that captured the topographic characteristics of night pen sites used by our partners. We then quantified and compared changes in annual NPP between night pen and control sites. Our analysis of RAP NPP data, using a control-treatment design did not find impacts of night penning on vegetation. However, this was a preliminary analysis, and does not conclusively quantify the impacts of night penning on rangeland vegetation. Our analysis indicated that RAP may be a feasible tool to study livestock management impacts on rangeland vegetation; however, future studies could further validate these findings through ground observations.

Rangeland Analysis Platform (RAP)↗

Monitoring Vegetation Impacts of Night Penning in Idaho and Oregon Grazing Allotments Using Remote Sensing

The practice of night penning, which involves corralling livestock into a fenced, secure area overnight, aims to safeguard animals from predators. Although this method has proven successful in minimizing interactions between livestock and wildlife, the extent of its impact on vegetation communities is still being explored. In this study, we used the Rangeland Analysis Platform (RAP), which aggregates spatially distributed values of vegetation composition, cover, and productivity from the Landsat missions, to quantify the effects of night penning on rangeland vegetation communities. We identified control sites that had similar topographic characteristics to night pen sites used by ranchers in Idaho and Oregon. We then quantified and compared changes in annual net primary productivity (NPP) between night pen and control sites. Our study found that RAP NPP data did not show a noticeable difference between control sites and night penning sites. When analyzed quantitatively, night pen sites showed variability in NPP before and after night penning; however, there were few discernible differences between night pen sites and control sites, suggesting that climate conditions can have more of an effect on NPP measurements compared to land management decisions. In the summer of 2024, field crews from the Natural Resource Ecology Laboratory collected biomass data from these rangeland sites, and this will be used to compare and validate RAP products while continuing to investigate the effects of night penning.

Truman Anarella↗

The Importance of Addressing Disagreements Between Nominal and Effective Treatments During Bat Mortality Minimization Validation Studies

As the wind energy industry grows, so too does our need for effective and low-cost bat mortality minimization solutions. Despite knowledge gaps in our understanding of what drives bats to collide with spinning turbines, minimization solutions have shown success during validation studies. Curtailment has been consistently effective, reducing bat mortality from 33%-79%, depending on the curtailment scenario and species present. Several validation studies have demonstrated deterrent solutions, specifically ultrasonic deterrents, to be effective, but overall, more variable compared to curtailment solutions. Further, a study combining curtailment with ultrasonic deterrents produced encouraging results, finding that adding ultrasonic deterrents to turbines that were designated to curtail, significantly reduced mortality rates compared to curtailment only turbines. Despite positive results, the strength of inference achieved with validation studies is limited by methodological constraints associated with appropriately assigning fatalities to treatments. Because of the temporal separation between when a bat collides with a turbine and when it is discovered during a ground-based carcass survey, we must assign carcasses to a treatment that ran during the prior night(s). This process may introduce errors at multiple stages. First, for studies that rotate treatments among turbines, mortality surveyors must be confident that carcasses are 'fresh' such that mortalities are correctly assigned to the treatment from the previous night(s). Second, we must reconcile any misalignments between how we assign treatments and how we implement treatments (e.g., turbines assigned with a deterrent treatment may be implemented as another treatment when deterrent devices are not operating as designed). Finally, for curtailment solutions, it is critical to recognize that measured effects are a function of not just the treatment as implemented but the proportion of the night the treatment is realized (e.g., if wind speeds are greater than the curtailment treatment cut-in speed for the entire night, we cannot expect there to me any differences in mortality reduction relative to control turbines). Using a dataset collected between June and October 2017, that rotated 3 treatments (Deterrent Only, 5 m/s Curtail only, and 5 m/s Curtail & Deterrent) and 1 control condition across 16 turbines each night, we explored the importance and implications of accounting for potential errors in assigning fatalities to treatments. We present preliminary results comparing the mortality associated with error-corrected treatments and control conditions highlighting how the measured effect of a treatment (mortality) greatly depends on site specific implementation.

bats↗

Evaluating the effectiveness of a camera-based detection system to support informed curtailment and minimize eagle fatalities at wind energy facilities

The American Wind Wildlife Institute (AWWI – now Renewable Energy Wildlife Institute, REWI) – was appointed prime awardee of DOE award number DE-EE0007880 to lead a team of scientists, wind developers, and technology manufacturers in a collaborative evaluation of the effectiveness of a technology intended to help reduce eagle collisions with wind turbines. IdentiFlight, developed by Renewable Energy Systems (RES) in collaboration with Boulder Imaging, is an autonomous aerial monitoring and detection system. REWI partnered with ecological consultants, Western Ecosystems Technology, Inc. (WEST), to independently evaluate the performance of IdentiFlight reducing eagle collision risk under a suite of environmental conditions relative to the performance of a Biomonitor (human observer-based) Program. The project objectives were to 1) evaluate how IdentiFlight compared to biomonitors in detecting and identifying eagles under a suite of environmental conditions and 2) use the observation data to model how IdentiFlight and biomonitors reduced the eagle fatality prediction through informed curtailment. Field testing was to take place at two geographically distinct wind farms over two field seasons at each wind farm with a study design appropriate for meta-analyses across sites and years.

17 WIND ENERGY↗

Accelerating technology development to monitor and minimize effects from land‐based wind energy on birds and bats

While wind energy is a key sector of domestic energy production for the United States, operation of wind turbines directly and indirectly adversely affects certain species of birds and bats. The cumulative effect of wind turbine strikes can have both biological and regulatory consequences, and, in some cases, delay permitting and construction or affect ongoing operations. Technology can help quantify and minimize these effects, but the pace of development, acceptance, and adoption of technological solutions is slow. Although adopting cost‐effective technologies may reduce negative effects on wildlife and help achieve both energy production and conservation goals, consensus is lacking among developers, regulators, and the conservation community regarding how to define technology effectiveness and acceptance and how to develop a standardized process for doing so. Removing barriers to technology advancement requires deviating from the status quo. Changes include 1) creating incentives to mitigate impacts, 2) establishing options for research as mitigation, 3) rethinking how research is funded, 4) increasing stakeholder coordination, and 5) increasing the efficiency of research and development. We recommend the creation of a national framework to establish clear criteria and protocols for technology evaluation and adoption.

17 WIND ENERGY↗

Mesoscale Modeling to Characterize Eagle Soaring Habitat

Uncovering drivers of risk is crucial to understanding interactions between wildlife and wind turbines, and identifying options for impact minimization. These drivers tie to co-variates linked to behavior and movement patterns that allow us to estimate locations and periods of risk. For volant species, atmospheric flow can have significant influence on flight patterns. For obligate soaring birds, like golden eagles, updraft velocities can inform where eagles are likely to travel, at what altitude, and where conditions are not likely sufficient to sustain soaring flight. This has been an active area of study in recent years, using relatively coarse atmospheric data generally at the 20km x 20km scale or larger. Leveraging a 20-year dataset from the Weather Research and Forecasting Model (WRF) (https://www.mmm.ucar.edu/weather-research-and-forecasting-model), we are quantifying vertical velocities across the continental United States at a 2km x 2km resolution. Wind resource data sets originally were static maps showing the mean annual wind speed over an area. However, for these data sets to be optimally used for various applications they must be high-resolution time series, seamlessly span large geographic contexts, and account for uncertainty in wind speed. The National Renewable Energy Laboratory is producing public available datasets that meet these criteria and will be bias corrected to yield the most accurate wind resource data. This effort is an augment to the current WIND Toolkit which houses a high resolution data set. In the new iteration of the WIND Toolkit, a 20-year dataset will be used to improve the accuracy and estimate uncertainty using ensemble and machine-learning techniques. The resulting product will be the most accurate dataset of its size and at a 2km x 2km spatial and 5-minute temporal resolution. Through this work, a mesoscale vertical velocity layer will be produced by calculating the likelihood of orographic updraft and thermal updraft conditions across the continental United States. Specifically, we will use WRF model output combined with digital elevation maps to predict updrafts and then determine if vertical velocities are sufficient to support Golden Eagle soaring and gliding. Ultimately this data layer will be made available as a GIS layer in the Wind Prospector (maps.nrel.gov/wind-prospector/) tool or a similar framework. Data that will be incorporated include wind speed, direction temperature, relative humidity, barometric pressure, air density, precipitation rate, solar radiation, atmospheric stability, skin temperature, and upward heat flux. These products will advance research on interactions between volant species and wind energy by providing open access to highly resolved data with uncertainty quantification not previously available at this scale.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Wind and Wildlife Co-Exist With Help From ECO Wind

Sustainable deployment of wind energy requires a balance of conservation, energy, and economic goals. The Enabling Coexistence Options for Wind Energy and Wildlife (ECO Wind) program at the U.S. Department of Energy National Renewable Energy Laboratory (NREL) supports efforts to reduce wildlife impacts at land-based and offshore wind energy facilities with monitoring and minimization technology solutions.

50 EE - Wind and Water Power Program - Water (EE-4↗

Raptor Monitoring and Minimization Technologies

In June 2023, the International Energy Agency Wind Task 34 - Working Together to Resolve the Environmental Effects of Wind Energy (WREN) - organized a forum to discuss monitoring and minimization strategies used to study raptor interactions with wind energy facilities. The forum included experts in raptor movement and behavior, minimization measures, technology validation, and wind energy development from four countries. The experts represented a range of international stakeholder groups including private industry, financial institutions, government agencies, nonprofit organizations, and wildlife consultants. This educational brief summarizes the discussion during the forum and written comments from additional participants who could not attend the live event. Relevant literature was used to provide additional context when needed.

minimization↗

Improving the accessibility and transferability of machine learning algorithms for identification of animals in camera trap images: MLWIC2

Motion-activated wildlife cameras (or “camera traps”) are frequently used to remotely and noninvasively observe animals. The vast number of images collected from camera trap projects has prompted some biologists to employ machine learning algorithms to automatically recognize species in these images, or at least filter-out images that do not contain animals. These approaches are often limited by model transferability, as a model trained to recognize species from one location might not work as well for the same species in different locations. Furthermore, these methods often require advanced computational skills, making them inaccessible to many biologists. We used 3 million camera trap images from 18 studies in 10 states across the United States of America to train two deep neural networks, one that recognizes 58 species, the “species model,” and one that determines if an image is empty or if it contains an animal, the “empty-animal model.” Our species model and empty-animal model had accuracies of 96.8% and 97.3%, respectively. Furthermore, the models performed well on some out-of-sample datasets, as the species model had 91% accuracy on species from Canada (accuracy range 36%–91% across all out-of-sample datasets) and the empty-animal model achieved an accuracy of 91%–94% on out-of-sample datasets from different continents. Our software addresses some of the limitations of using machine learning to classify images from camera traps. By including many species from several locations, our species model is potentially applicable to many camera trap studies in North America. We also found that our empty-animal model can facilitate removal of images without animals globally. We provide the trained models in an R package (MLWIC2: Machine Learning for Wildlife Image Classification in R), which contains Shiny Applications that allow scientists with minimal programming experience to use trained models and train new models in six neural network architectures with varying depths.

59 BASIC BIOLOGICAL SCIENCES↗

Proceedings from the State of the Science and Technology for Minimizing Impacts to Bats from Wind Energy

The U.S. Department of Energy Wind Energy Technologies Office (DOE WETO), and the National Renewable Energy Laboratory convened a workshop entitled the State of the Science and Technology for Minimizing Impacts to Bats from Wind Energy on 13–14 November 2019. The objectives of the workshop were to (1) Identify the current impact minimization measures that are, or can be, used to reduce bat fatalities at wind energy facilities, (2) Assess the current effectiveness of those minimization measures, (3) Identify and assess the research and development (R&D) opportunities needed to optimize and improve the effectiveness of current minimization and deterrent technologies and inform the development of future solutions; and (4) Identify potential emerging or novel methods for informing impact minimization measures at or around wind energy facilities. Specifically, the workshop focused on deterrent and curtailment strategies. For deterrents, the discussion centered on the existing technology (i.e., ultrasonic deterrents, dim-UV light, and texture coating), integration with wind turbines (either retrofitting or out of the box installation), effectiveness, validation studies, and cost (e.g., technology, installation, validation, and maintenance). For curtailment, the conversation was divided into blanket curtailment (i.e., based on time and wind speed) and smart curtailment (i.e., blanket curtailment plus additional variables such as temperature or bat activity). The workshop included plenary presentations, panels, and breakout sessions to share data and stakeholder perspectives, and engage participants. Although there are several priority topics related to bat and wind energy, this workshop focused the discussion on the current technologies and strategies that are, or can be, used to reduce bat fatalities at wind energy facilities, status of research and development (R&D) of minimization measures, opportunities to optimize costs and improve effectiveness, and potential emerging or novel approaches to explore. This workshop took a holistic approach and discussed all aspects associated with advancing deterrent technologies and curtailment strategies, including the technological, biological, economic, and regulatory barriers faced by the wind energy and wildlife community.

13 HYDRO ENERGY↗

[X-33 Launch and Landing Facilities]

Sverdrup is responsible for the design, construction and activation of the X-33 Flight Operations Center at Edwards Air Force Base and for providing assistance in activating the X-33 Landing Sites. The past year has seen the completion of the construction of the X-33 Flight Operations Center. Construction was completed in December of 1998, with systems checkout and testing continuing into early 1999. Integration of the site with LMCMS and other partner-supplied systems began in December and will continue through rollout of the X-33 vehicle. The construction of the X-33 Launch Complex has been performed within the Edwards AFB and Air Force Research Laboratory (AFRL) systems with no substantial interference to either parties. A high level of cooperation exists between Sverdrup, Edwards AFB, and the Air Force Research Laboratory in the areas of access, training, security, and operations. There have been no conflicts between programs that have not been accommodated. Development of the landing sites is progressing with many of the modifications necessary underway. GSE commitments are in place. The personnel training program developed by Sverdrup for persons entering the launch site construction areas, was modified by Lockheed for use in training and access control to the Center during flight operations to maximize safety and minimize intrusion upon the environment. Close cooperation between Sverdrup, the construction workers, and the environmental biologist permitted construction to proceed in a timely fashion without harm to the wildlife, in particular, the Desert Tortoise. Although the entire X-33 site encompasses approximately 50 acres including a new access road, only the areas directly impacted by the construction were cleared to minimize the impact on the environment. A total of about 30 acres was actually disturbed.

Source record↗

Minimizing Ecological Impacts of Marine Energy Lighting

Marine energy is poised to become an important renewable energy contributor for the U.S., but widespread deployment of the technology hinges on its benefits outweighing the potential ecological impacts. One stressor marine energy installations introduce is light, which is known to cause varying responses among wildlife and has not yet been addressed as an environmental concern. This review discusses requirements and regulations for similar structures and how lighting design choices can be made to meet these requirements while minimizing environmental consequences. More practical guidance on implementing lighting for marine energy is needed, as well as updated guidelines to reflect technological and research advances. Known responses of wildlife to light are introduced in addition to how the responses of individuals may lead to ecosystem-level changes. The impact of light associated with marine energy installations can be reduced by following basic guidance provided herein, such as removing excess lighting, using lights with high directionality, and employing controls to reduce light levels. Continued research on animal responses to light, such as findings on minimum light levels for animal responses, alongside the development of highly-sensitivity spectral characterization capabilities can further inform lighting guidelines for deploying future open ocean marine energy devices.

54 ENVIRONMENTAL SCIENCES↗

Evaluating Movement Patterns of the Rattlesnake Hills Elk Herd on Hanford for Calendar Years 2019-2024

Biologists first documented elk on the Hanford Site in 1972; since then, the elk herd known as the Rattlesnake Hills Elk Herd (RHEH) has grown substantially (PNNL-13331, Population Characteristics and Seasonal Movement Patterns of the Rattlesnake Hills Elk Herd: Status Report 2000). Through the 1990s, the core range of the RHEH was focused on the portion of the Hanford Reach National Monument known as the Fitzner-Eberhardt Arid Lands Ecology (ALE) Reserve. More recently, larger numbers of elk have been occupying the U.S. Department of Energy (DOE), Hanford Field Office (HFO), formerly the DOE, Richland Operations Office managed portion- of the Hanford Site, known as central Hanford (Figure 1-1). This began with bachelor groups of bulls occupying the site intermittently, and the herd has grown to resident herds, including bulls, cows, and calves. The Washington Department of Fish and Wildlife (WDFW) established a target herd size for the RHEH of less than 350 animals to minimize damages on adjacent private agricultural lands (Washington State Elk Herd Plan–Yakima Elk Herd [WDFW 2002]). Attempts to control the RHEH population through hunting on private lands and a relocation effort during 2000 have failed to limit growth of the population toward the WDFW target, and the herd exceeds 1,600 according to recent counts (PNNL-13331; DOE/RL- 2023-20, Hanford Annual Site Environmental Report for Calendar Year 2022). Although elk are present on central Hanford year-round, they continue to move between areas offsite, the ALE Reserve, and central Hanford throughout the year, and it is these movements that result in many of the elk-vehicle collisions (EVC) that occur along Hanford Site roads and on the Washington State highways bordering the site. In addition, changes in management strategies on the ALE Reserve, including recent and potential future tribal elk hunts, may alter herd behavior and result in additional animals transiting onto and off central Hanford.

54 ENVIRONMENTAL SCIENCES↗

Evaluating the Effectiveness of a Detection and Deterrent System in Reducing Golden Eagle Fatalities at Operational Wind Facilities

The Renewable Energy Wildlife Institute (REWI) was appointed as the prime awardee of DOE award number DE-EE0007883 to lead a team of scientists, wind developers, and technology manufacturers toward the overarching goal of evaluating the effectiveness of the current DTBird system in minimizing the risk of golden eagles (Aquila chrysaetos) and other large soaring raptors from approaching the rotor-swept zone (RSZ) of operating wind turbines. As part of this goal, the team set out to 1) quantify the expected reduction in collision risk for golden eagles from operation of the detection and deterrence modules in a manner that supports the approach used by the U.S. Fish and Wildlife Service (USFWS) to assess and credit facility operators for their efforts to minimize predicted collision fatalities and 2) provide information to help improve the technology to maximize its effectiveness. DTBird is an automated detection and audio deterrent system created by the Spanish company Liquen, designed to discourage birds from entering the RSZ of spinning wind turbines. The system uses cameras to automatically detect airborne targets of interest, records each such event in an online database, and triggers a warning signal (loud sound) if the tracked object has moved close to the turbine. If the object moves even closer to the RSZ, a more aggressive dissuasion signal is broadcast. To meet our objectives, the team conducted a two-year experiment at the Goodnoe Hills wind facility in Washington state, in which 14 turbines were outfitted with DTBird units. Daily, each DTBird-equipped turbine was randomly assigned to a control or treatment group. Treatment turbines operated with DTBird running as intended—broadcasting warning or deterrent signals when DTBird detected a target within range. On control turbines, no sound signals were broadcast if a moving target triggered the DTBird system. The team also flew unmanned aerial vehicles (UAVs) designed to coarsely mimic the general size, weight, and coloration of golden eagles in programmed flight transects across DTBird detection ranges to quantify DTBird’s ability to detect intended targets and to evaluate factors that influence the probability of detection and DTBird’s response distances. Additionally, the team evaluated the behavioral responses of in situ eagles exposed to spinning turbines alone (visual and sound influences) versus spinning turbines plus broadcasted DTBird audio deterrents, to estimate the effectiveness of deterrence by the DTBird system. The data and results from these investigations were combined with those from a pilot study conducted at the Manzana Wind Power Project in California to better evaluate DTBird’s effectiveness across different landscapes.

17 WIND ENERGY↗