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At least 361 records · Page 20

A Large Ensemble Global Dataset for Climate Impact Assessments

We present a self-consistent, large ensemble, high-resolution global dataset of long-term future climate, which accounts for the uncertainty in climate system response to anthropogenic emissions of greenhouse gases and in geographical patterns of climate change. The dataset is developed by applying an integrated spatial disaggregation (SD) - bias-correction (BC) method to climate projections from the MIT Integrated Global System Model (IGSM). Four emission scenarios are considered that represent energy and environmental policies and commitments of potential future pathways, namely, Reference, Paris Forever, Paris 2 °C and Paris 1.5 °C. The dataset contains nine key meteorological variables on a monthly scale from 2021 to 2100 at a spatial resolution of 0.5°x 0.5°, including precipitation, air temperature (mean, minimum and maximum), near-surface wind speed, shortwave and longwave radiation, specific humidity, and relative humidity. We demonstrate the dataset’s ability to represent climate-change responses across various regions of the globe. This dataset can be used to support regional-scale climate-related impact assessments of risk across different applications that include hydropower, water resources, ecosystem, agriculture, and sustainable development.

54 ENVIRONMENTAL SCIENCES↗

Technical Potential Assessment for the Renewable Energy Zone (REZ) Process: A GIS-Based Approach

Geographic Information Systems (GIS)-based energy resource and technical potential assessments identify areas capable of supporting high levels of renewable energy (RE) development as part of a Renewable Energy Zone (REZ) Transmission Planning process. This document expands on the REZ Process to aid practitioners in conducting GIS-based RE resource and technical potential assessments. The REZ process is an approach to plan, approve, and build transmission infrastructure that connects REZs - geographic areas that have high-quality RE resources, suitable topography and land-use designations, and demonstrated developer interest - to the power system. The REZ process helps to increase the share of solar photovoltaic (PV), wind, and other resources while also maintaining reliability and economics.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

A spatially explicit individual-based modeling approach to evaluate the cumulative effects of wind energy development on the greater sage-grouse. Final Report

In order to achieve the national vision of 20% of energy being produced by wind by 2030, issues associated with wind energy development’s potential impacts on ecological resources must be addressed. In particular, wind energy and associated transmission system development may affect wildlife populations through direct mortality, habitat fragmentation, habitat degradation, and disturbance. Although individual projects may have little effect on the sustainability of wildlife populations, cumulative impacts could be significant. The wind energy industry and regulators have developed processes for assessing the impacts of individual projects and identifying mitigation requirements, but no one has developed a methodology for considering cumulative impacts in a systematic and holistic way.

17 WIND ENERGY↗

LANL Meteorology Program Self-Assessment 2025 Update

The LANL Meteorological (Met) Program has been subject to several external reviews over the past 19 years. The DOE Meteorological Coordinating Council (DMCC) conducted an initial Met Program Site Assist Visit (SAV) in August 2006 (DMCC 2006). A follow-up SAV in August 2015 assessed progress (DMCC 2015), and in June 2023, the DOE Meteorological Subcommittee (DMSC), successor to the DMCC, conducted a second follow-up SAV (DMSC 2023), in which the Met Program was evaluated relative to the following 8 high-level questions: • What is the state of the meteorological services provided to its customers? • What is the quality of meteorological data provided to its customers and is it adequate and available to meet all customer needs? • What is the quality of atmospheric transport and diffusion modeling provided to its customers and is it applicable to complex wind flow patterns at LANL? • Are the current and future meteorological service customers being serviced appropriately? • Are there adequate human resources to meet present and future program customer needs and are they being appropriately leveraged? • Are existing instrumentation, facilities, and systems adequate to meet present and future customer needs? • Are LANL meteorological services conducted in an efficient, cost-effective manner? • Is meteorological data used to ensure safety & health of LANL personnel? More specific evaluations were performed relative to 23 performance objectives extracted from the ANSI/ANS-3.11- 2024 national standard and 14 separate performance objectives associated with consequence assessment and atmospheric transport and diffusion modeling in the consequence assessment element of DOE G 151.1-1B. In 2023, the DMSC SAV Team also reviewed the status of each of the 18 remaining recommendations from its 2015 SAV. Based on this review, DMSC stated in its Exit Briefing that the LANL meteorological program has gotten much stronger and more robust since 2015 and now represents one of the better managed programs within the DOE complex.

54 ENVIRONMENTAL SCIENCES↗

Data-driven Community-centered Resilient Assessment and Planning Toolkit for Nexus of Energy and Water (DCRAPT-NEW)

Urban areas, including Detroit and Pittsburgh, have suffered significant dual outages of the electrical and water infrastructure in the past decade due, in part, to the increasing number of extreme weather events. With increasing temperatures and rainfall intensity, these regions need to prepare for increasing extreme events through community-based energy and water resilience analysis, planning, and enhancement. This project developed a suite of open-source, open-access, community-centered, data-driven assessment and distributed energy resource (DER) and planning tools for energy and water resilience enhancement in urban areas. Through establishing a multi-level community awareness and engagement mechanism and a comprehensive collection of power outage and flooding data, an innovative group of community energy and water resilience assessment and planning tools have been developed for a wide range of users with differing and variable sets of data available to them. The developed tools include (1) DOE EAGLE-I data-driven, deep-learning assisted resilience assessment and DER planning tools at the county level with socioeconomic factors incorporated; (2) Utility annual power outage data-driven tools for long term resilience assessment and DER planning and 15-min power outage data-driven tools for short term resilience assessment and planning; (3) Detailed engineering tools for energy and water systems resilience assessment and planning when the system topology and component fragility curves are available; (4) Alternative Resiliency Metric Calculation that extracts and separates outage and restoration processes; and (5) Co-optimization tools that evaluate the resilience of the power and sewage system and allow users to conduct joint planning with energy and wastewater systems. The developed tools provide planners, decision-makers, and stakeholders with powerful capabilities to systematically evaluate system/community resilience and optimal and actionable guidance for enhancing resilience while prioritizing DER investments. The tools have been used and validated in Detroit and Pittsburgh and can be used in other areas of the nation. In addition, this project will (1) advance the knowledge and applications of machine-learning methods in analyzing and fusing different layers of information and generating meaningful data points such as generating rare weather events; (2) significantly improve the energy and water resilience of the identified communities in Detroit and Pittsburgh and prepare for more frequent and severe weather conditions; (3) help communities assess extreme weather event impacts and address short-term and long-term resilience-related issues The developed tools have been made public via GitHub and demonstrated to community stakeholders and utility companies via the two annual workshops and numerous community engagement meetings. The project outcomes are also disseminated through publications in various journals and conference proceedings, and presentations at top conferences.

13 HYDRO ENERGY↗

Artificial Intelligence-Aided Wind Plant Optimization for Nationwide Evaluation of Land Use and Economic Benefits of Wake Steering

If clean energy pathways are to harness massive increases in wind power, innovations with broad geographic viability will be needed to support buildout in diverse locations. However, geodiversity in impact potential is seldom captured in technology assessment. Here we propose a scalable approach to plant-level optimization using artificial intelligence to evaluate land sparing and economic benefits of wake steering at more than 6,800 plausible onshore wind locations in the USA. This emerging controls strategy optimizes plant energy production by directing turbine wakes. On the basis of estimates from our artificial intelligence model trained on engineering wind flow simulations, co-optimizing plant layouts with wake steering can reduce land requirements by an average of 18% per plant (site-specific benefits range from 2% to 34%), subject to errors and uncertainties in the flow model, wind resource estimates, buildout scenario and geographic factors. According to model estimates, wake steering is predicted to increase power production during high-value (relatively low wind) periods, boosting the annual revenue of individual plants by up to US$3.7 million (equivalent to US$13,000 MW-1 yr-1) but producing negligible gains in some settings. Consideration of wake steering’s geographic potential reveals divergent nationwide prospects for improved economics and siting flexibility.

deployment↗

Mexico Clean Energy Report

This report provides an assessment of Mexico's clean energy resource potential and pathways for rapidly deploying renewable energy technologies to enable Mexico to reach its goal of 35% renewable energy by 2024 within the current legal and regulatory framework. An appendix to the report includes the results of the 2024 Renewable Energy Integration Study, and technology chapters on wind, solar, geothermal, hydropower, transport electrification, and green hydrogen, detailing current state, resource potential, and deployment opportunities and recommendations. Additional sections include transmission, a section on the challenges and solutions for the integration of variable generation resources, and a summary of benefits.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

An Analytical Impact Assessment Framework for Wildlife to Inform the Siting and Permitting of Wind Energy Facilities

In the United States overall electrical generation capacity is expected to increase by 10-25 gigawatts (GW) per year to meet increases in demand. Wind energy is a key component of state and federal renewable energy standards, and central to the Department of Energy’s 20% by 2030 wind production goals. Increased wind energy development may present increased resource conflict with avian wildlife, and environmental permitting has been identified as a potential obstacle to expansion in the sector. ICF developed an analytical framework to help applicants and agencies examine potential impacts in support of facility siting and permitting. A key objective of our work was to develop a framework that is scalable from the local to the national level, and one that is generalizable across the different scales at which biological communities operate – from local influences to meta-populations. The intent was to allow natural resource managers to estimate the cumulative impacts of turbine strikes and habitat changes on long-term population performance in the context of a species demography, genetic potential, and life history. We developed three types of models based on our literature review and participation in the scientific review processes. First, the conceptual model was developed as a general description of the analytical framework. Second, we developed the analytical framework based on the relationships between concepts, and the functions presented in the scientific literature. Third, we constructed an application of the model by parameterizing the framework using data from and relevant to the Altamont Pass Wind Resource Area (APWRA), and an existing golden eagle population model. We developed managed source code, database create statements, and written documentation to allow for the reproduction of each phase of the analysis. ICF identified a potential template adaptive management system in the form of the US Fish & Wildlife Service (USFWS) Adaptive Harvest Management (AHM) program, and developed recommendations for the structure and function of a similar wind-facility related program. We provided a straw-man implementation of the analytical framework based on assumptions for APWRA-wide golden eagle fatalities, and presented a statistical examination of the model performance. APWRA-wide fatality rates appear substantial at all scales examined from the local APWRA population to the Bird Conservation Region. Documented fatality rates significantly influenced population performance in terms of non-territorial non-breeding birds. Breeder, Juvenile, Subadult, and Adult abundance were mostly unaffected by Baseline APWRA-wide fatality rates. However, increased variability in fatality rates would likely have impacts on long-term population performance, and would result in a substantially larger loss of resources. We developed four recommendations for future study. First, we recommend establishment of concept experts through the existing system of non-profits, regulatory agencies, academia, and industry in the wind energy sector. Second, we recommend the development of a central or distributed shared data repository, and establish guidelines for data sharing and transparency. Third, we recommend development a forum and process for model selection at the local and national level. Last, we recommend experimental implementation of the prescribed system at broader scales, and refinement the expectations for modeling and adaptive management.

54 ENVIRONMENTAL SCIENCES↗

Evaluating the mineral commodity supply risk of the U.S. manufacturing sector

Trade tensions, resource nationalism, and various other factors are increasing concerns regarding the supply reliability of nonfuel mineral commodities. This is especially the case for commodities required for new and emerging technologies ranging from electric vehicles to wind turbines. In this analysis, we use a conventional risk-modeling framework to develop and apply a new methodology for assessing the supply risk to the U.S. manufacturing sector. Specifically, supply risk is defined as the confluence of three factors: the likelihood of a foreign supply disruption, the dependency of U.S. manufacturers on foreign supplies, and the ability of U.S. manufacturers to withstand a supply disruption. The methodology is applied to 52 commodities for the decade spanning 2007–2016. The results indicate that a subset of 23 commodities, including cobalt, niobium, rare earth elements, and tungsten, pose the greatest supply risk. This supply risk is dynamic, shifting with changes in global market conditions.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Carolina Offshore Wind Integration Case Study: Phases I and II Final Technical Report

Duke Energy performed a phase 1 study to assess the impact of offshore wind development in the waters off the coasts of North Carolina and South Carolina. The study analyzed the impacts to the Duke Energy Carolinas electric power system of multiple wind deployment scenarios. Focusing on an integrated utility system in the Carolinas provided a unique opportunity to assess the impacts of offshore wind development in a region that has received less attention regarding renewables than others in the US. North Carolina is the only state in the Southeastern United States that currently has a renewable portfolio standard (RPS) which requires that 12.5% of the state’s total energy requirements be met with renewable resources by 2021. 12.5% of the state’s total energy requirements in 2021 equates to approximately 17,000 GWH of energy needed from renewable resources. Wind resources represent one of the ways to potentially meet this requirement. The study builds upon and augments ongoing work, including a study by UNC to identify potential wind development sites and the analysis of impacts to the regional transmission system performed by the NCTPC, an Order 890 planning entity of which DEC is a member. Furthermore, because the region does not have an independent system operator (ISO) or regional transmission organization (RTO), the study will provide additional information unique to non-RTO/ISO systems. The Phase 2 study builds on the results of Phase 1 and investigates the dynamic stability of the electrical network in Task 4, the operating characteristics of the wind turbines as they impact operating reserve requirements of the DEC utility in Task 5, and the production cost of integrating the offshore wind resources into the DEC generation fleet making comparisons to future planned operation without the addition of the wind resources in Task 6.

17 WIND ENERGY↗

Evaluating the tidal energy resource for smooth power output and grid integration in the United States

In comparison to wind and solar energy, tidal resources are predictable with a high degree of certainty. Although tides are inherently variable, their periodicity and predictability create the possibility of providing smooth power output to the grid. By spatially diversifying tidal devices to capture the tidal wave as it propagates through a system, aggregate power becomes smoother. Tidal energy assessments have indicated that energy extraction is viable in several regions around the world, leading to the development and testing of many devices. However, less attention has been given to the interface between energy production and grid integration, particularly in the United States. We evaluate tidal phases for several regions across the United States to determine if there is enough diversity within relatively close distances of one another. By calculating the cross correlations of estimated tidal current velocity time series between representative locations in defined regions, we show three regions in the United States that have the potential to aggregate power output from geographically diversified turbines to generate a smoother, baseload-like power profile.

Preziuso, Danielle C.↗

The RenewElec Project: Variable Renewable Energy and the Power System (Final Report)

Variable energy resources, such as wind power, now produce about 4% of U.S. electricity. They can play a significantly expanded role if the U.S. adopts a systems approach that considers affordability, security and reliability. Reaching a 20-30% renewable portfolio standard goal is possible, but not without changes in the management and regulation of the power system, including accurately assessing and preparing for the operational effects of renewable generation. The RenewElec project will help the nation make the transition to the use of significant amounts of electric generation from variable and intermittent sources of renewable power.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Estimation of Mass-Loss Rates from Emission Line Profiles in the UV Spectra of Cool Stars

The photon-scattering winds of cool, low-gravity stars (K-M giants and supergiants) produce absorption features in the strong chromospheric emission lines. This provides us with an opportunity to assess important parameters of the wind, including flow and turbulent velocities, the optical depth of the wind above the region of photon creation, and the star's mass-loss rate. We have used the Lamers et al. Sobolev with Exact Integration (SEI) radiative transfer code along with simple models of the outer atmospheric structure to compute synthetic line profiles for comparison with the observed line profiles. The SEI code has the advantage of being computationally fast and allows a great number of possible wind models to be examined. We therefore use it here to obtain initial first-order estimates of the wind parameters. More sophisticated, but more time-consuming and resource intensive calculations will be performed at a later date, using the SEI-deduced wind parameters as a starting point. A comparison of the profiles over a range of wind velocity laws, turbulence values, and line opacities allows us to constrain the wind parameters, and to estimate the mass-loss rates. We have applied this analysis technique (using lines of Mg II, 0 I, and Fe II) so far to four stars: the normal K5-giant alpha Tau, the hybrid K-giant gamma Dra, the K5 supergiant lambda Vel, and the M-giant gamma Cru. We present in this paper a description of the technique, including the assumptions which go into its use, an assessment of its robustness, and the results of our analysis.

Carpenter, K. G.↗

Costs and consequences of wind turbine wake effects arising from uncoordinated wind energy development

Optimal wind farm locations require a strong and reliable wind resource and access to transmission lines. As onshore and offshore wind energy grows, preferred locations become saturated with numerous wind farms. An upwind wind farm generates 'wake effects' (decreases in downwind wind speeds) that undermine a downwind wind farm's power generation and revenues. Here we use a diverse set of analysis tools from the atmospheric science, economic and legal communities to assess costs and consequences of these wake effects, focusing on a West Texas case study. We show that although wake effects vary with atmospheric conditions, they are discernible in monthly power production. In stably stratified atmospheric conditions, wakes can extend 50+ km downwind, resulting in economic losses of several million dollars over six years for our case study. However, our investigation of the legal literature shows no legal guidance for protecting existing wind farms from such significant impacts.

17 WIND ENERGY↗

Circular Economy Modeling Efforts at NREL: Circular Economy Lifecycle Analysis and Visualization (CELAVI) and the Circular Economy Agent-Based Model (ABM)

Circular Economy (CE) aims at decoupling human activities from economic growth and resource use. While CE economic and environmental benefits are often touted by its proponents, increased circularity and improved sustainability do not necessarily go hand-in-hand. The Circular Economy Lifecycle Assessment and Visualization (CELAVI) framework simulates the transition of renewable energy technology supply chains towards circularity and quantifies spatially explicit environmental impacts and supply chain costs. Using wind blade end-of-life (EOL) management as a case study, this presentation will highlight CELAVI's features. Furthermore, envisioned extension to the framework could improve the stakeholder decision model by accounting for logistical and other factors. The CELAVI framework could be leveraged to answer crucial questions regarding renewables EOL management.

circular economy↗

Addressing Market Issues in Electrical Power Systems with Large Shares of Variable Renewable Energy

This paper reports recent findings from IEA Wind TCP Task 25, which compiles international experiences and research related to large-scale integration of wind and other renewable energy. In the paper, we address the main challenges for market integration of variable renewable energy, relating to price formation, cost recovery, balancing and other grid services. The paper gives an overview of recent scenario studies on electricity price impacts of (1) various generation, energy storage and demand types in different markets, and (2) different market designs and energy/climate policies. Studying markets with very high shares of variable renewable energy requires an improved set of analysis tools for forecasting market outcomes, estimating flexibility needs and sources, and assessing resource adequacy. Key market features need to be investigated within these improved analytical capabilities for systems transitioning to high shares of variable renewable energy, storage and flexible demand. System services that can be supported by markets will likely need to be revisited. Finally, this paper identifies open questions and suggested future market design work for supporting systems with very high shares of variable renewable energy, which are to be addressed in follow-up work of Task 25 collaborative research.

cost recovery↗

Insights for Canadian electricity generation planning from an integrated assessment model: Should we be more cautious about hydropower cost overruns?

Hydropower accounts for approximately 60% of electricity generation in Canada, with growth expected in the coming decades as part of renewable energy transitions; however, frequent cost overruns threaten the viability of this growth. Here, using the integrated assessment model GCAM, we develop an endogenous representation of hydropower for Canada that accounts for market dynamics, thus permitting analysis of hydropower competition with other electricity generation technologies, both with and without cost overruns. Results show that modelling hydropower resources endogenously increases Canadian hydropower deployment relative to an assumption of fixed hydropower production, from 417 to 495 TWh annually by 2050. In scenarios that apply cost overruns at historical levels, hydropower loses market share to more easily scalable technologies like wind power. When including high cost overrun assumptions, the model determines that hydropower falls from about 73% to 65% of Canadian electricity generation by 2050, while wind power increases from about 8% to 11%. Countries may be better able to achieve electrification and renewable energy targets at lower cost by avoiding large-scale, overrun-prone hydropower and nuclear generation projects. Model results support that cost overruns are important considerations for policy decisions related to electricity sector development in Canada and elsewhere.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Unseen Winds: Harnessing High-Altitude Winds in the Southeast USA

This project aims to identify potential sites in the United States for further testing and development of airborne wind energy systems (AWES). Through industry questionnaires and interviews with AWES companies, the study assesses existing test sites' capabilities and gaps, leading to a three-tiered test site strategy: short-duration prototype demonstrations, long-duration technical assessments and power validations, and airspace interaction and deconfliction studies. Notably, the southeastern United States presents significant potential for AWES due to its lack of traditional wind turbines, which is attributed to low wind speeds at lower altitudes. However, wind conditions improve significantly at higher altitudes, making this region a promising candidate for AWES deployment. The project considers factors such as wind resources, infrastructure proximity, social acceptance, and environmental impacts to recommend sites that can support the unique needs of AWES manufacturers and facilitate their commercialization. Early findings suggest rural communities with low grid resiliency could benefit economically and technologically from hosting AWES test sites, especially with operator training centers and potential for long-term skilled employment in future disaster relief and other applications.

17 WIND ENERGY↗