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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

Assessment of Offshore Wind System Design, Safety, and Operation Standards

This report is a deliverable for a project sponsored by the U.S. Department of Energy (DOE) entitled National Offshore Wind Energy Resource and Design Data Campaign -- Analysis and Collaboration (contract number DE-EE0005372; prime contractor -- AWS Truepower). The project objective is to supplement, facilitate, and enhance ongoing multiagency efforts to develop an integrated national offshore wind energy data network. The results of this initiative are intended to 1) produce a comprehensive definition of relevant met-ocean resource assets and needs and design standards, and 2) provide a basis for recommendations for meeting offshore wind energy industry data and design certification requirements.

17 WIND ENERGY↗
DOE OSTI2026

Dynamical Downscaling of Earth System Model Data for Energy System Analysis

Assessing energy resources (e.g., solar, wind, and hydro) under future scenarios requires datasets with sufficient spatial and temporal detail to capture variability and extreme events. While global-scale Earth System Model (ESM) projections are widely used, their coarse resolution limits direct application to regional energy system analyses. Dynamical downscaling offers a robust approach to generate physically consistent, fine-scale datasets that better represent local atmospheric processes impacting energy resources. In this work, we present a two-stage approach for producing high-resolution historical and future projections over the contiguous United States (CONUS). First, we optimize the Weather Research and Forecasting (WRF) model configuration for energy-relevant variables - solar irradiance, wind speed, and precipitation - by conducting ERA5-driven simulations at 8-km and 28-km resolution. Multiple physics schemes and model configurations within the WRF are evaluated against observational datasets including the National Solar Radiation Database (NSRDB), the Parameter-elevation Regressions on Independent Slopes Model (PRISM), and the Stage IV multi-radar/multi-sensor precipitation product for the CONUS domain. Using the best-performing configuration, we dynamically downscale MPI-ESM1-2-HR simulations for 2000-2060 under SSP2-4.5 and SSP5-8.5 scenarios at 4-km spatial and hourly temporal resolution. This presentation will provide a comprehensive analysis of the results from multiple numerical experiments and high-resolution ESM projections. In addition, we will discuss potential applications of our high-resolution datasets within the energy sector and outline future research avenues dedicated to evaluating how extreme weather events influence system performance and resilience.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Scientific challenges to characterizing the wind resource in the marine atmospheric boundary layer

Abstract. With the increasing level of offshore wind energy investment, it is correspondingly important to be able to accurately characterize the wind resource in terms of energy potential as well as operating conditions affecting wind plant performance, maintenance, and lifespan. Accurate resource assessment at a particular site supports investment decisions. Following construction, accurate wind forecasts are needed to support efficient power markets and integration of wind power with the electrical grid. To optimize the design of wind turbines, it is necessary to accurately describe the environmental characteristics, such as precipitation and waves, that erode turbine surfaces and generate structural loads as a complicated response to the combined impact of shear, atmospheric turbulence, and wave stresses. Despite recent considerable progress both in improvements to numerical weather prediction models and in coupling these models to turbulent flows within wind plants, major challenges remain, especially in the offshore environment. Accurately simulating the interactions among winds, waves, wakes, and their structural interactions with offshore wind turbines requires accounting for spatial (and associated temporal) scales from O(1 m) to O(100 km). Computing capabilities for the foreseeable future will not be able to resolve all of these scales simultaneously, necessitating continuing improvement in subgrid-scale parameterizations within highly nonlinear models. In addition, observations to constrain and validate these models, especially in the rotor-swept area of turbines over the ocean, remains largely absent. Thus, gaining sufficient understanding of the physics of atmospheric flow within and around wind plants remains one of the grand challenges of wind energy, particularly in the offshore environment. This paper provides a review of prominent scientific challenges to characterizing the offshore wind resource using as examples phenomena that occur in the rapidly developing wind energy areas off the United States. Such phenomena include horizontal temperature gradients that lead to strong vertical stratification; consequent features such as low-level jets and internal boundary layers; highly nonstationary conditions, which occur with both extratropical storms (e.g., nor'easters) and tropical storms; air–sea interaction, including deformation of conventional wind profiles by the wave boundary layer; and precipitation with its contributions to leading-edge erosion of wind turbine blades. The paper also describes the current state of modeling and observations in the marine atmospheric boundary layer and provides specific recommendations for filling key current knowledge gaps.

17 WIND ENERGY↗
DOE OSTI2022

Renewable Energy Resource Assessment Information for the United States

The Renewable Energy Resource Assessment Information for the United States report summarizes the results of nearly 30 national renewable energy resource assessments performed by the U.S. national laboratories since 2012. Included are assessments for solar, wind, biomass, marine, geothermal, and hydropower energy resource technologies. Increased attention is given to the renewable energy resources available near federally recognized Tribal Nations and low-to-moderate income households, where assessed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Distributed Wind Representation in Modeling and Simulation Tools: An Assessment of Existing Tools

PNNL evaluated the inclusion of wind in distributed energy resource modeling and simulation tools. Tools were assessed based on a survey of publicly available and readily accessible information. While the authors have made a good faith effort to understand these tools, PNNL does not know the intentions of the developers and acknowledges that some tool capabilities or features may not have been accurately captured in this assessment. This evaluation informs an ongoing effort by PNNL to modernize existing tools both directly by working with developers of some tools and indirectly by providing best practices on how different types of tools could enhance certain modeling features to improve distributed wind’s representation and valuation.

17 WIND ENERGY↗
DOE OSTI2013

DeepCwind Consortium Research Program: January 15, 2010 - March 31, 2013 (Final Technical Report)

This is the final technical report for the U.S. Department of Energy-funded program, DE-0002981: DeepCwind Consortium Research Program. The project objective was the partial validation of coupled models and optimization of materials for offshore wind structures. The United States has a great opportunity to harness an indigenous abundant renewable energy resource: offshore wind. In 2010, the National Renewable Energy Laboratory (NREL) estimated there to be over 4,000 GW of potential offshore wind energy found within 50 nautical miles of the US coastlines (Musial and Ram, 2010). The US Energy Information Administration reported the total annual US electric energy generation in 2010 was 4,120 billion kilowatt-hours (equivalent to 470 GW) (US EIA, 2011), slightly more than 10% of the potential offshore wind resource. In addition, deep water offshore wind is the dominant US ocean energy resource available comprising 75% of the total assessed ocean energy resource as compared to wave and tidal resources (Musial, 2008). Through these assessments it is clear offshore wind can be a major contributor to US energy supplies. The caveat to capturing offshore wind along many parts of the US coast is deep water. Nearly 60%, or 2,450 GW, of the estimated US offshore wind resource is located in water depths of 60 m or more (Musial and Ram, 2010). At water depths over 60 m building fixed offshore wind turbine foundations, such as those found in Europe, is likely economically infeasible (Musial et al., 2006). Therefore floating wind turbine technology is seen as the best option for extracting a majority of the US offshore wind energy resource. Volume 1 - Test Site; Volume 2 - Coupled Models; and Volume 3 - Composite Materials.

17 WIND ENERGY↗
DOE OSTI2015

Remote Sensing of Complex Flows by Doppler Wind Lidar: Issues and Preliminary Recommendations

Remote sensing of winds using lidar has become popular and useful in the wind energy industry. Extensive experience has been gained with using lidar for applications including land-based and offshore resource assessment, plant operations, and turbine control. Prepared by members of International Energy Agency Task 32, this report describes the state of the art in the use of Doppler wind lidar for resource assessment in complex flows. The report will be used as input for future recommended practices on this topic.

17 WIND ENERGY↗
DOE OSTI2013

The impact of climate change on the U.S. wind energy resource

The growing need for low-carbon emitting electricity sources has resulted in rapid growth in the wind power industry. The size and steadiness of the offshore wind resource has attracted growing investment in the planning of offshore wind turbine installations. Decisions about the location and character of wind farms should be made with an eye not only to present but also future wind resource, which may change as increasing carbon dioxide forces reductions in the poleward temperature gradient, and thus potentially in the mean tropospheric westerly winds. I propose to use the new North American Regional Climate Change Assessment Program climate projections to estimate the change of the wind power resource under various carbon dioxide loading scenarios and for a range of climate models. We will compare our assessment with both our assessment based on the IPCC AR4 model runs, to explore the extent to which improved model resolution changes the prediction for the wind power resource, and with present day estimates from reanalysis and scatterometer winds.

17 WIND ENERGY↗
DOE OSTI2020

Adversarial super-resolution of climatological wind and solar data

Accurate and high-resolution data reflecting different climate scenarios are vital for policy makers when deciding on the development of future energy resources, electrical infrastructure, transportation networks, agriculture, and many other societally important systems. However, state-of-the-art long-term global climate simulations are unable to resolve the spatiotemporal characteristics necessary for resource assessment or operational planning. We introduce an adversarial deep learning approach to super resolve wind velocity and solar irradiance outputs from global climate models to scales sufficient for renewable energy resource assessment. Using adversarial training to improve the physical and perceptual performance of our networks, we demonstrate up to a 50 × resolution enhancement of wind and solar data. In validation studies, the inferred fields are robust to input noise, possess the correct small-scale properties of atmospheric turbulent flow and solar irradiance, and retain consistency at large scales with coarse data. An additional advantage of our fully convolutional architecture is that it allows for training on small domains and evaluation on arbitrarily-sized inputs, including global scale. We conclude with a super-resolution study of renewable energy resources based on climate scenario data from the Intergovernmental Panel on Climate Change’s Fifth Assessment Report.

14 SOLAR ENERGY↗
DOE OSTI2013

Office of Legacy Management Decision Tree for Solar Photovoltaic Projects - 13317

To support consideration of renewable energy power development as a land reuse option, the DOE Office of Legacy Management (LM) and the National Renewable Energy Laboratory (NREL) established a partnership to conduct an assessment of wind and solar renewable energy resources on LM lands. From a solar capacity perspective, the larger sites in the western United States present opportunities for constructing solar photovoltaic (PV) projects. A detailed analysis and preliminary plan was developed for three large sites in New Mexico, assessing the costs, the conceptual layout of a PV system, and the electric utility interconnection process. As a result of the study, a 1,214-hectare (3,000-acre) site near Grants, New Mexico, was chosen for further study. The state incentives, utility connection process, and transmission line capacity were key factors in assessing the feasibility of the project. LM's Durango, Colorado, Disposal Site was also chosen for consideration because the uranium mill tailings disposal cell is on a hillside facing south, transmission lines cross the property, and the community was very supportive of the project. LM worked with the regulators to demonstrate that the disposal cell's long-term performance would not be impacted by the installation of a PV solar system. A number of LM-unique issues were resolved in making the site available for a private party to lease a portion of the site for a solar PV project. A lease was awarded in September 2012. Using a solar decision tree that was developed and launched by the EPA and NREL, LM has modified and expanded the decision tree structure to address the unique aspects and challenges faced by LM on its multiple sites. The LM solar decision tree covers factors such as land ownership, usable acreage, financial viability of the project, stakeholder involvement, and transmission line capacity. As additional sites are transferred to LM in the future, the decision tree will assist in determining whether a solar PV project is feasible on the new sites. (authors)

14 SOLAR ENERGY↗
DOE OSTI2022

Duke Energy Carbon-Free Resource Integration Study

Duke Energy has partnered with the National Renewable Energy Laboratory (NREL) to evaluate pathways to achieving their carbon-free targets and to assess the operational impacts of the resulting system. This report details findings from Phase II of the Duke Low Carbon Resource Integration study, which consisted of three separate but interrelated analyses: (1) a resource assessment exploring the technical and economic potential and characteristics of wind and solar resources in the Carolinas; (2) capacity expansion modeling identifying the least-cost investment pathways for achieving 70% CO 2 emissions reductions in North Carolina by 2030 and a net-zero electricity system by 2050; and (3) detailed production cost modeling of power system operations at the higher shares of low- and zero-carbon emitting generation sources, informed by the capacity expansion modeling portion of the analysis. The analysis finds that Duke Energy can approach the 2030 and 2050 emissions target in North Carolina through investment in a combination of solar, wind, and storage along with maintaining its existing nuclear fleet. The average cost of CO 2 abatement in the Carolinas through 2021-2050 is on the order of $\$27-33$ per metric ton (range of $\$9-34$ per metric ton across key sensitivities).Duke Energy can expected increased interchange with neighbors to help balance higher levels of solar, although the ability to do this will depend on whether neighboring regions also move to integrate more carbon-free resources. As Duke Energy moves toward both the 2030 and 2050 targets, addressing energy needs during the winter peak period becomes particularly important, and the system relies on the availability of resources such as renewable or hydrogen combustion turbines, seasonal storage, or other similar technologies that are dispatchable but able to operate at low capacity factors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS1992

A Combined XRD/XRF Instrument for Lunar Resource Assessment

Robotic surface missions to the Moon should be capable of measuring mineral as well as chemical abundances in regolith samples. Although much is already known about the lunar regolith, our data are far from comprehensive. Most of the regolith samples returned to Earth for analysis had lost the upper surface, or it was intermixed with deeper regolith. This upper surface is the part of the regolith most recently exposed to the solar wind; as such it will be important to resource assessment. In addition, it may be far easier to mine and process the uppermost few centimeters of regolith over a broad area than to engage in deep excavation of a smaller area. The most direct means of analyzing the regolith surface will be by studies in situ. In addition, the analysis of the impact-origin regolith surfaces, the Fe-rich glasses of mare pyroclastic deposits, are of resource interest, but are inadequately known; none of the extensive surface-exposed pyroclastic deposits of the Moon have been systematically sampled, although we know something about such deposits from the Apollo 17 site. Because of the potential importance of pyroclastic deposits, methods to quantify glass as well as mineral abundances will be important to resource evaluation. Combined x ray diffraction (XRD) and x ray fluorescence (XRF) analysis will address many resource characterization problems on the Moon. XRF methods are valuable for obtaining full major-element abundances with high precision. Such data, collected in parallel with quantitative mineralogy, permit unambiguous determination of both mineral and chemical abundances where concentrations are high enough to be of resource grade. Collection of both XRD and XRF data from a single sample provides simultaneous chemical and mineralogic information. These data can be used to correlate quantitative chemistry and mineralogy as a set of simultaneous linear equations, the solution of which can lead to full characterization of the sample. The use of Rietveld methods for XRD data analysis can provide a powerful tool for quantitative mineralogy and for obtaining crystallographic data on complex minerals.

Vaniman, D. T.↗
DOE OSTI2017

An Assessment of the Economic Potential of Offshore Wind in the United States from 2015 to 2030

This study describes an assessment of the spatial variation of levelized cost of energy (LCOE) and levelized avoided cost of energy to understand the economic viability of fixed-bottom and floating offshore wind technologies across major U.S. coastal areas between 2015 and 2030. In particular, this study offers insights into the available offshore wind resource by region at different levels of LCOE and an assessment of the economically viable resource capacity in the United States.

17 WIND ENERGY↗
DOE OSTI2021

Comparing Capacity Credit Calculations for Wind: A Case Study in Texas

The degree to which wind energy can contribute to the capacity needed to meet resource adequacy requirements, also known as capacity credit (CC), varies regionally with wind resource and correlation to net load. CC is an important metric widely used for resource planning and resource adequacy assessments. However, there are multiple methods for computing and estimating CC, depending on specific needs, access to data, and computational burden. It is unclear the extent to which the CC computation method may influence the result. To address this, we use a probabilistic resource adequacy tool and multiple approximation methods to systematically assess the CC of wind for near-term wind deployment under a case study in Texas. We find that proper consideration of transmission constraints is important; some approximation methods may overestimate the CC of wind due to a lack of consideration of transmission constraints, while other approximation methods may underestimate the CC by not capturing the ability of wind to be shipped to neighboring regions. In this case study, we find that several approximation methods do come close to the CC calculated by more robust probabilistic methods. However, the best approximation method may vary on a case-by-case basis, depending on system-specific considerations.

17 WIND ENERGY↗
DOE OSTI2014

Representation of Solar Capacity Value in the ReEDS Capacity Expansion Model

An important issue for electricity system operators is the estimation of renewables' capacity contributions to reliably meeting system demand, or their capacity value. While the capacity value of thermal generation can be estimated easily, assessment of wind and solar requires a more nuanced approach due to the resource variability. Reliability-based methods, particularly assessment of the Effective Load-Carrying Capacity, are considered to be the most robust and widely-accepted techniques for addressing this resource variability. This report compares estimates of solar PV capacity value by the Regional Energy Deployment System (ReEDS) capacity expansion model against two sources. The first comparison is against values published by utilities or other entities for known electrical systems at existing solar penetration levels. The second comparison is against a time-series ELCC simulation tool for high renewable penetration scenarios in the Western Interconnection. Results from the ReEDS model are found to compare well with both comparisons, despite being resolved at a super-hourly temporal resolution. Two results are relevant for other capacity-based models that use a super-hourly resolution to model solar capacity value. First, solar capacity value should not be parameterized as a static value, but must decay with increasing penetration. This is because -- for an afternoon-peaking system -- as solar penetration increases, the system's peak net load shifts to later in the day -- when solar output is lower. Second, long-term planning models should determine system adequacy requirements in each time period in order to approximate LOLP calculations. Within the ReEDS model we resolve these issues by using a capacity value estimate that varies by time-slice. Within each time period the net load and shadow price on ReEDS's planning reserve constraint signals the relative importance of additional firm capacity.

14 SOLAR ENERGY↗
DOE OSTI2021

A systematic evaluation of wind's capacity credit in the Western United States

Abstract The degree to which wind energy can contribute to the capacity needed to meet resource adequacy requirements, also known as capacity credit (CC), can be impacted by many factors. The CC varies regionally with wind resource and correlation to net load and may also vary with wind technology (land‐based versus offshore) and turbine specifications. We use a probabilistic resource adequacy tool to systematically assess the CC of multiple technologies for near‐term wind deployment across the Western US power system to help inform planning decisions. We find that wind CC varies by weather year and location but averages 16% for land‐based turbines and 41% for offshore turbines, with large regional variations. The average wind CC increases to 20% for land‐based and 53% for offshore when considering only the sites in the top 25th percentile of capacity factor. The CC of land‐based wind is generally lower than its capacity factor, which indicates a low correlation of generation to system needs. However, offshore wind shows a substantially higher CC, which is driven by not only a higher capacity factor but also a greater correlation with system needs.

17 WIND ENERGY↗
DOE OSTI2023

City and Borough of Sitka, Alaska: Modeling and Controls Assistance and Renewable Energy Resource Assessment [Slides]

This project develops the dynamic modeling of hydro plants and wind generation in Sitka, Alaska. A dynamic penetration of renewables was evaluated under various conditions. The impact of altering hydro generation control to synchronous condenser control was evaluated. While the existing hydro generations are sufficient to address voltage instability, a detailed study of the active-reactive capability limits of hydro generation operation should be conducted to uptake at various wind penetration levels.

14 SOLAR ENERGY↗
DOE OSTI2020

Preliminary Assessment of Potential for Wind Energy Technology on the Turtle Mountain Band of Chippewa Reservation

Wind energy can provide renewable and sustainable electricity to Native American reservations, including rural homes, and power schools and businesses on reservations. It can also provide tribes with a source of income and economic development. The purpose of this paper is to determine the potential for deploying community and utility-scale wind renewable technologies on the Turtle Mountain Band of Chippewa tribal lands. Ideal areas for wind technology development were investigated based on annual wind resources, terrain, land usage, and other factors such as culturally sensitive sites. The result is a preliminary assessment of wind energy potential on Turtle Mountain lands, which can be used to justify further investigation and investment into determining the feasibility of future wind technology projects.

17 WIND ENERGY↗