Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “WIND RESOURCE ASSESSMENT”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 325 records · Page 18

Assessment of the Economic Potential of Distributed Wind in Colorado, Minnesota, and New York

Stakeholders in the small and distributed wind space require access to better tools and data for more informed decisions on high-impact topics, including project planning, policymaking, and funding allocation. A major challenge in obtaining improved information is in the identification of favorable sites - namely, the intersection of sufficient wind resource with economic parameters such as retail rates, incentives, and other policies. This presentation made at the AWEA WINDPOWER Conference and Exhibition in Chicago in 2018 explores the researchers' objective: To understand the spatial variance of key distributed wind parameters and identify where they intersect to form pockets of favorable areas in Colorado, Minnesota, and New York.

17 WIND ENERGY↗

AI-based Detection and Defense Against Cyberattacks in Distributed Energy Resources

This study will provide comprehensive artificial intelligence (AI)-based solution tools for network security, malware prevention, and sensor data anomaly detection for distributed energy resource (DER) research, development, and demonstration. DER technologies are energy systems (e.g., solar panels, wind turbines, and energy storage systems) that are often connected to the internet and thus vulnerable to cyberattacks. Cybersecurity should be of primary concern for DERs, which is why we propose an integrated multi-layer cyber-defense system for DERs. This system encompasses risk assessments, network security, malware prevention, and detection of anomalies in the sensor data. Implementation of a comprehensive risk assessment with an overview of the model architecture should be the primary step, and should include the potential impact of experiencing, at a given time, one or more cyberattacks on the system. The second step is to ensure that the network security includes firewalls, intrusion detection, and malware prevention. The third step is to provide solution tools that enable sensor data anomaly detection for DERs. By incorporating these considerations into DER research, development, and demonstration, organizations can help ensure the safety and security of their systems and protect against potential cyberattacks.

20 FOSSIL-FUELED POWER PLANTS↗

Modeling the Value of Integrated Canadian and U.S. Power Sector Expansion

The United States and Canada power systems are not isolated. Cross-border transmission and coordination of system operation create an interconnected power system, which results in combined imports and exports of electricity of greater than 70 TWh per year [1]. Currently, over 5 GW of new international transmission lines are in various stages of permitting and development. These lines may enable greater integration and coordination of the U.S. and Canada systems, which can in turn reduce challenges associated with integration of high penetrations of variable renewables. Furthermore, low-cost Canadian resources, such as wind and hydro, could contribute to compliance with the EPA's recently released Clean Power Plan. Improving integration and coordination internationally will reduce the costs of accessing these resources. This analysis work build on previous work by Ibanez and Zinaman [2]. In this work we seek to better understand the value of additional interconnection between the U.S. and Canadian power systems. Specifically, we quantify the value of additional interconnection and coordination within the Canadian-US integrated power system under scenarios in which large reductions (>80%) in power sector CO2 emissions are achieved. We explore how the ability to add additional cross-border transmission impacts capacity investment, the generation mix, system costs, and the ability of the system to integrate variable renewable energy into the power system. This analysis uses the Regional Energy Deployment System (ReEDS) capacity expansion model [3], [4] to quantify the value of the integrated power system expansion of the United States and Canada. ReEDS is an optimization model that assesses the deployment and operation (including transmission) of the electricity sector of the contiguous United States and Canadian provinces from 2016 through 2050. It has the ability to model the integration of renewable energy technologies into the grid. ReEDS captures renewable energy resources through the use of 356 individual resource regions and 134 balancing areas across the U.S. and is able to handle renewable energy issues such as variability in wind and solar output, transmission costs and constraints, and ancillary services requirements.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100): Six-Month Progress Update [Slides]

Puerto Rico has committed to meeting its electricity needs with 100% renewable energy by 2050, along with realizing interim goals of 40% by 2025, 60% by 2040, the phase-out of coal-fired generation by 2028, and a 30% improvement in energy efficiency by 2040, as established in Puerto Rico Energy Public Policy Act (Act 17). Since hurricanes Irma and Maria in September 2017, DOE and its national laboratories have provided Puerto Rico energy system stakeholders with tools, training, and modeling support to enable planning and operation of the electric power grid with more resilience against further disruptions. On February 2, 2022, DOE, FEMA, and six national laboratories launched the two-year Puerto Rico Grid Resilience and Transitions to 100% Renewable Energy Study (PR100) to conduct comprehensive analysis of stakeholder-driven pathways to Puerto Rico's energy future. The robust and objective energy analysis entails five activities, with an emphasis on power system reliability, resilience, and generation planning. This presentation provides a six-month progress update on the study, including presentation of four initial scenario frameworks defined with extensive stakeholder input.

14 SOLAR ENERGY↗

Estudio de Resiliencia de la Red Electrica de Puerto Rico y Transicion a Energia 100% Renovable (PR100): Actualizacion de Progreso de Seis Meses [Slides]

Puerto Rico se ha comprometido a satisfacer sus necesidades de electricidad con un 100% de energia renovable para 2050, junto con el cumplimiento de objetivos intermedios del 40% para 2025, el 60% para 2040, la eliminacion gradual de la generacion a base de carbon para 2028, y una mejora del 30% en la eficiencia energetica para 2040, segun lo establecido en la Ley de Politica Publica Energetica de Puerto Rico (Ley 17). Desde los huracanes Irma y Maria en septiembre de 2017, DOE y sus laboratorios nacionales han proporcionado a las partes interesadas del sistema energetico de Puerto Rico herramientas, adiestramiento y apoyo de modelaje para permitir la planificacion y el funcionamiento de la red electrica con mas resiliencia frente a nuevas interrupciones. El 2 de febrero de 2022, DOE, FEMA y seis laboratorios nacionales lanzaron el Estudio de Resiliencia de la Red Electrica de Puerto Rico y Transicion a la Energia 100% Renovable (PR100), de dos anos de duracion, para llevar a cabo un analisis exhaustivo de las vias impulsadas por las partes interesadas para el futuro energetico de Puerto Rico. El analisis energetico, solido y objetivo, comprende cinco actividades, con enfasis en la confiabilidad del sistema electrico, la resiliencia y la planificacion de la generacion. Esta presentacion provee una actualizacion de progreso del trabajo de seis meses sobre el Estudio, incluyendo la presentacion de cuatro escenarios iniciales definidos mediante un rol activo de las partes interesadas. This is the Spanish translation of NREL/PR-6A20-83432.

14 SOLAR ENERGY↗

Integrating in situ environmental covariates in an American lobster catch model to improve impact assessment

The installation and operation of floating offshore wind power is an integral component of societal transition to renewable energy generation where fixed bottom offshore wind is not possible. However, it will cause unique ecosystem changes. To disentangle the effects of offshore wind installations from the concurrent effects of climate change and the fishing practices on commercially significant resources, we must develop detailed characterizations of the resources before development occurs. In the Gulf of Maine, American lobster is the most commercially and culturally important fishery. At the time of writing, this is the largest fishery by value in North America. Our understanding of baseline localized parameters (such as catch per trap at the spatial scale of individual turbines) should be informed by relationships to environmental, biological, and survey-specific functional drivers of catch. A more mechanistic understanding of catch will allow for strategic adjustments to Post- Deployment fishery responses and ultimately, the development of research- and commercial-scale floating offshore wind development. Here, we used survey data from the New England Aqua Ventus Pre-Construction Commercial Trapping Survey to develop Generalized Additive Models describing seasonal catch per trap for legal and sublegal lobsters. We found fall catch to be nearly twice that of spring. Bottom temperature dynamics could be used to predict catch, and the Fall survey was associated with a warmer temperature regime. By using analytical tools that incorporate environmental heterogeneity, we developed monitoring methods from preconstruction baseline data that will be applicable over the post-construction operating period of an offshore wind farm.

BACI↗

Identifying Robust Decarbonization Pathways for the Western U.S. Electric Power System Under Deep Climate Uncertainty

Climate change threatens the resource adequacy of future power systems. Existing research and practice lack frameworks for identifying decarbonization pathways that are robust to climate-related uncertainty. We create such an analytical framework, then use it to assess the robustness of alternative pathways to achieving 60% emissions reductions from 2022 levels by 2040 for the Western U.S. power system. Our framework integrates power system planning and resource adequacy models with 100 climate realizations from a large climate ensemble. Climate realizations drive electricity demand; thermal plant availability; and wind, solar, and hydropower generation. Among five initial decarbonization pathways, all exhibit modest to significant resource adequacy failures under climate realizations in 2040, but certain pathways experience significantly less resource adequacy failures at little additional cost relative to other pathways. By identifying and planning for an extreme climate realization that drives the largest resource adequacy failures across our pathways, we produce a new decarbonization pathway that has no resource adequacy failures under any climate realizations. This new pathway is roughly 5% more expensive than other pathways due to greater capacity investment, and shifts investment from wind to solar and natural gas generators. Our analysis suggests modest increases in investment costs can add significant robustness against climate change in decarbonizing power systems. Our framework can help power system planners adapt to climate change by stress testing future plans to potential climate realizations, and offers a unique bridge between energy system and climate modeling.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Dominant Wave Energy Systems and Conditional Wave Resource Characterization for Coastal Waters of the United States

Opportunities and constraints for wave energy conversion technologies and projects are evaluated by identifying and characterizing the dominant wave energy systems for United States (US) coastal waters using marginal and joint distributions of the wave energy in terms of the peak period, wave direction, and month. These distributions are computed using partitioned wave parameters generated from a 30 year WaveWatch III model hindcast, and regionally averaged to identify the dominant wave systems contributing to the total annual available energy ( A A E ) for eleven distinct US wave energy climate regions. These dominant wave systems are linked to the wind systems driving their generation and propagation. In addition, conditional resource parameters characterizing peak period spread, directional spread, and seasonal variability, which consider dependencies of the peak period, direction, and month, are introduced to augment characterization methods recommended by international standards. These conditional resource parameters reveal information that supports project planning, conceptual design, and operation and maintenance. The present study shows that wave energy resources for the United States are dominated by long-period North Pacific swells (Alaska, West Coast, Hawaii), short-period trade winds and nor’easter swells (East Coast, Puerto Rico), and wind seas (Gulf of Mexico). Seasonality, peak period spread, and directional spread of these dominant wave systems are characterized to assess regional opportunities and constraints for wave energy conversion technologies targeting the dominant wave systems.

16 TIDAL AND WAVE POWER↗

A Structured-Grid Quality Measure for Simulated Hypersonic Flows

A structured-grid quality measure is proposed, combining three traditional measurements: intersection angles, stretching, and curvature. Quality assesses whether the grid generated provides the best possible tradeoffs in grid stretching and skewness that enable accurate flow predictions, whereas the grid density is assumed to be a constraint imposed by the available computational resources and the desired resolution of the flow field. The usefulness of this quality measure is assessed by comparing heat transfer predictions from grid convergence studies for grids of varying quality in the range of [0.6-0.8] on an 8'half-angle sphere-cone, at laminar, perfect gas, Mach 10 wind tunnel conditions.

Alter, Stephen J.↗

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↗

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↗

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.↗