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At least 199 records · Page 11

Tidal Resource Gaps Analysis Technical Report

The tidal resource gaps project was created to address a growing body of evidence that models underpredict tidal current speeds compared to measurements at a number of the top-ranking tidal energy sites. In response, this project compared opportunistic tidal power density measurements from 16 tidal energy hot spot sites with estimates from resource assessment data to identify discrepancies. To improve the accuracy of resource estimates from model data, updated data from eight improved model simulations were obtained. Model improvements included grid refinement, domain coupling, and the use of unstructured or nested grids. New resource estimates were calculated from the updated models, and these data were used to update the tidal hot spots-a list of promising tidal energy sites around the United States.

16 TIDAL AND WAVE POWER↗

The Baseline Performance Reference for Irradiance in PV System Applications

This report proposes the definition of a new baseline performance reference (BPR). The definition goes beyond existing standards pertaining to photovoltaic (PV) reference cells and devices to define the response under all possible operating conditions in the field. Field evaluations using BPR devices will be more sensitive to performance anomalies than pyranometers because they track PV system power output more closely. At the same time, they will be able to detect a broader range of performance anomalies than traditional matched reference devices, which might have matching defects. The BPR definition also opens the door to new practices in resource assessment and yield prediction. Solar resource data can be collected or modeled and validated directly as BPR irradiance, and PV system simulations based on BPR irradiance need fewer assumptions and less processing to obtain the effective irradiance on modules. As a result, lower uncertainty in yield assessments can be expected.

14 SOLAR ENERGY↗

Wave resource characterization at regional and nearshore scales for the U.S. Alaska coast based on a 32-year high-resolution hindcast

A wave resource characterization was performed for the southern coast of Alaska based on a 32-year hindcast covering the period from 1979 to 2010. The characterization closely followed International Electrotechnical Commission (IEC) Technical Specifications. An unstructured-grid Simulating WAves Nearshore (SWAN) model, which had an approximate spatial resolution of 300 m within 30 km from the nearest shoreline, was developed. Additionally, extensive model validation and error characterization was performed. The model was found to perform well with an average absolute percent error of 8.6% in significant wave height, averaged over 18 buoys. Statistics for the six IEC wave resource parameters were calculated and aggregated at 20 km from shore to quantify the incident wave power and its variability at a regional scale. The southern coast of the Aleutian Archipelago was found to have the most available wave energy in the region. A nearshore resource assessment was performed by evaluating resource hotspots located 1 km from shore. More than 900 nearshore stations had an Optimum Hotspot Identifier value of 5 (kW/m) at diverse water depths, thereby positioning Alaska as a promising location for wave energy development.

54 ENVIRONMENTAL SCIENCES↗

Wind Plant Performance Prediction Benchmark Phase 1 (Technical Report)

Financial risk resulting from the uncertainty associated with developing, owning, and operating wind power plants remains a barrier to reducing the levelized cost of energy (LCOE). On average, modern wind power plants in the U.S. underperform their expected annual energy output by 3.5-4.5% , with many underperforming by over 10%. To compensate for this uncertainty, investors require a larger return on investment (ROI) and apply "knock-down" factors that mask much of the underlying sources of uncertainty. Wind energy projects thus have reduced access to low-cost capital. Furthermore, operating wind plants often take a simple approach to estimating operations & maintenance (O&M) costs (e.g. straight-line estimates based on similar plants), which can eat into profits. To overcome these issues, the wind industry must improve the models they use for estimating wind plant performance and operations. An industry consortium (IC) requested that the National Renewable Energy Laboratory (NREL) lead a Department of Energy (DOE) working group to benchmark the accuracy of wind power plant energy predictions against real operational data. The IC was also motivated by DOE and NREL's potential to characterize systematic energy underperformance, identify sources of uncertainty, and explore root causes. The Wind Plant Performance Prediction (WP3) project was created out of this request, and this report represents the successful completion of Phase 1 of the WP3 project. During the project, wind plant owners provided both pre-construction and operational data to NREL. The pre-construction data was provided to wind resource assessment (WRA) consultants so they could conduct energy yield assessments (EYA). NREL took all of the completed EYAs, along with the operational data, and conducted an operational assessment to benchmark the EYA results against actual operational data. Given the large amounts of sensitive data required for this effort, as well as historical opposition to sharing data within industry, successful completion of Phase 1 represents an unprecedented milestone for industry data sharing. To improve the accuracy and confidence of pre-construction EYAs, wind plant owners and investors need better, more certain, energy yield predictions. The WP3 Benchmark Project is an industry-driven response to this reality. For the first time, industry has taken the important step of working together at scale, sharing valuable operational data with DOE and NREL in order to investigate the sources of bias and uncertainty in these energy estimates. This IC provides wind plant preconstruction and operational data to NREL in an organized and documented fashion and provides guidance and feedback as needed. The IC also provides introspection of the design of experiment, key metrics of success, data challenges, analysis best practices, and quality of results.

17 WIND ENERGY↗

Impact of Siting Ordinances on Land Availability for Wind and Solar Development

In the United States, many siting regulations for wind and solar developments are created at the county or township level. Here we survey local zoning ordinances across the contiguous United States to understand the types and frequency of ordinances that might impact wind and solar development. We identify over 1,800 ordinances for wind and more than 800 ordinances for solar in 2022. To understand the impact of ordinances on anticipated land availability, we use spatial modelling on the setbacks specified in the ordinances. Extrapolating the setbacks throughout the country can reduce wind and solar resources by up to 87% and 38%, respectively, depending on the size of the setbacks applied. These results indicate the importance of capturing setback ordinances in resources assessments so as to not overstate resource potential, especially when considering highly decarbonized futures.

county↗

Impact of Siting Ordinances on Land Availability for Wind and Solar Development

In the United States, many siting regulations for wind and solar developments are created at the county or township level. Here we survey local zoning ordinances across the contiguous United States to understand the types and frequency of ordinances that might impact wind and solar development. We identify over 1,800 ordinances for wind and more than 800 ordinances for solar in 2022. To understand the impact of ordinances on anticipated land availability, we use spatial modelling on the setbacks specified in the ordinances. Extrapolating the setbacks throughout the country can reduce wind and solar resources by up to 87% and 38%, respectively, depending on the size of the setbacks applied. These results indicate the importance of capturing setback ordinances in resources assessments so as to not overstate resource potential.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Evaluation of a high-resolution regional climate simulation for surface and hub-height wind climatology over North America

Assessing the availability of key wind resources requires augmenting observations to support the implementation of wind energy infrastructure. However, observations are limited, necessitating the development of high-resolution, long-term gridded datasets. This study presents a robust, dynamically downscaled climatological dataset, offering 20 years of hourly wind data at a 4 km spatial resolution across North America, and evaluates its performance against observations, including meteorological towers and automated surface-observing system (ASOS) stations, as well as coarse-resolution reanalysis data (the European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis version 5 (ERA5)). Results demonstrate that the downscaled high-resolution wind data outperform ERA5 in regions of complex terrain and coastal areas, with improved overlap coefficients for wind data distributions and reduced root mean square errors (RMSEs) for hub-height and near-surface diurnal wind patterns. The downscaled simulation also captures the synoptic drivers of seasonal wind direction patterns reasonably well, indicated by high wind rose similarity indices. This study also provides an analysis of interannual variability, utilizing the dataset's full 20-year period, and model uncertainty, generated by varying model initial conditions and physics parameterizations across 1-year ensemble members, which are key considerations for wind resource assessment in wind farm development.

17 WIND ENERGY↗

Massachusetts and New England SAF Study [Slides]

The Massachusetts Port Authority established a project to assess feedstock availability to produce SAF near 10 New England airports. A techno-economic analysis was conducted to determine renewable fuels and SAF that could be produced from these feedstocks. The resource assessment found municipal solid waste, woody biomass, and food waste were most abundant. The techno-economic analysis found that potential fuel production varied widely based on location, feedstock, and technology production pathway. An assessment of infrastructure readiness to handle SAF was conducted. It was determined that SAF produced outside of New England should be blended in other regions with more capacity and flexibility and delivered to New England as Jet A is today. For SAF produced in New England, there are terminals that have existing infrastructure to receive, blend, and distribute SAF/Jet A blends.

33 ADVANCED PROPULSION SYSTEMS↗

Offshore Wind Technology: Above the Water

WINDExchange will produce an Offshore Wind Technology: Above the Water Webinar. The webinar will explore the technology involved in offshore wind above the water including wind farm technology, turbine technology, and wind resource assessments and modeling to provide foundational technical information to communities and interested stakeholders.

above the water↗

Methods for Assessing Opportunities for Ring Dam Pumped Storage Hydropower

There is growing interest in new pumped storage hydropower (PSH) deployment to provide a range of grid flexibility, reliability, and resiliency services under an evolving and uncertain future power sector. The National Laboratory of the Rockies develops open PSH resource assessment and cost modeling tools to help evaluate PSH deployment opportunities, and this report describes expansions to those tools to consider an additional PSH system configuration - ring-dam reservoirs built on flat topographical features that are constructed from roller-compacted concrete material. This reservoir type is common among current PSH proposals and requires new methods to identify sites with this reservoir geometry throughout the United States and characterize the associated dam cost. Cost characterization for ring dam reservoirs required collecting historical dam cost data for earthen, rockfill, and roller-compacted concrete dams and regressing equations that relate costs between alternative materials. The ring dam site identification algorithm follows a 5-step procedure to identify circular geometry reservoirs. Once ring dam reservoirs are identified, they are then paired with potential dry-gully reservoirs, and the full set of potential paired reservoirs is cost-optimized to produce a least-cost set of potential PSH sites with no overlapping reservoirs. The resulting analysis found 1,663 ring-dam to dry-gully systems in the contiguous United States that are lower cost than any overlapping dry-gully to dry-gully systems, 29 in Alaska, and none in Hawaii or Puerto Rico. These systems constitute 1.5 TW of capacity in the contiguous United States and nearly 29 GW in Alaska, demonstrating that under suitable topography and head, ring-dam systems can provide cost-effective PSH opportunities. The greatest density of these opportunities are found in the intermountain west where there are mesas and flat land at bases of mountain ranges, but continued work could incorporate additional site characteristics or consider more complex reservoir shapes to find additional PSH deployment opportunities.

13 HYDRO ENERGY↗

Developing a 20-year high-resolution wind data set for Puerto Rico

The purpose of this study is to develop a high-resolution wind resource data set for Puerto Rico as part of the wind resource assessment in the Puerto Rico Grid Resilience and Transition to 100 % Renewable Energy Study (PR100) project. The Weather and Research and Forecasting (WRF) is used to model 20-years (2001-2020) of wind resource data on a 3-km grid for the Puerto Rico region. Because accurately representing the planetary boundary layer (PBL)-physics in the WRF is key to accurately model low-level wind speed, 11 different PBL schemes are examined and evaluated to find a WRF configuration that can provide the most accurate wind data. The modeled wind speeds are validated with buoy observations, and the Shin-Hong PBL scheme is selected to generate the final wind data set. Here, the overall results demonstrate that the high-resolution data correctly represents the climate of Puerto Rico (e.g., a dominant easterly trade wind). At 160 m above ground, the southern regions of Puerto Rico show strong offshore wind speed (>8 m/s on average) throughout the daytime and nighttime. For land-based wind, average wind speed ranges from 5 m/s-7 m/s during daytime, whereas notable high wind speeds (>9 m/s) appear in the mountain regions during nighttime.

17 WIND ENERGY↗

Overview of NASA ISRU Plans, Priorites, and Activities

Introduction:The National Aeronautics andSpace Administration (NASA) of the United States ofAmerica (US) has initiated the Artemis Moon to Marsprogram to send astronauts (the first woman andperson of color) back to the lunar surface, create asustainable human lunar exploration program, andlead the first human exploration mission to the Marssurface in the 2030’s [1]. A major objective of thisprogram is to characterize the resources that exist onthe Moon and Mars, and learn how to utilize them forsustained and affordable exploration. Commonlyknown as In Situ Resource Utilization (ISRU), thesearch for, acquisition, and processing of resources inspace has the potential to greatly reduce thedependency on transporting mission consumables andinfrastructure from Earth, thereby reducing missioncosts, risks, and dependency on Earth.ISRU is Enabling: Through the extraction andprocessing of resources into mission commoditiessuch as rocket propellants, life support consumables,and fuel cell reactants, ISRU enhances and evolvesthe cis-lunar, lander, and surface transportationsystems required for human exploration; expandingand enhancing HOW humans can explore and returnfrom the Moon. Through the extraction andprocessing of resources into metals, silicon, and othermanufacturing and construction feedstock, ISRUenhances and allows for the expansion of criticalinfrastructure using in situ manufacturing andconstruction capabilities that influence WHAT humanscan do on the Moon and in cis-lunar space. Becauseof this, ISRU supports and enables commercialinvolvement beyond NASA and governmentalagencies by both lowering the cost of sustainedtransportation to/from/on the Moon as well assupporting the market required for needing thesetransportation systems. Strategic Framework:To achieve this vision,NASA’s Space Technology Mission Directorate(STMD) ensures the coordinated development ofISRU and other critical space and surfaceinfrastructure elements such as propulsion, power,manufacturing, construction, and robotics through theStrategic Technology Architecture Roundtable(STAR) process. Through STAR, an integratedframework and process has been created allowing forcapabilities and technologies to be linked andassessed, gaps to be identified, specifications andmetrics to be established, and provide a means toprioritize and implement technology development andmissions. A critical part of the STAR effort has beenthe establishment of the Strategic Framework thatorganizes all work under four major Thrusts (Go,Land, Live, and Explore) and identifies the drivingOutcomes for each of these Thrusts. From the Thrustsand Outcomes, all work can be categorized and linkedbetween Capability Areas, and Technology Gaps canbe identified and addressed (Figure 1.)Figure 1. Strategic Framework and STAR FrameworkISRU Envisioned Future: To drive thedevelopment of technologies and capabilities, theSTAR process starts with establishing a ‘grand vision’of where each Outcome and Capability is aiming tobe considered complete. For ISRU, the EnvisionedFuture is “Scalable ISRU production/utilizationcapabilities including sustainable commodities on thelunar and Mars Surface”. This involves starting with10’s of metric tons of products, but evolves into 100’sto 1000’s of metric tons of water, oxygen, propellants,construction and manufacturing feedstock, andcommodities for habitat and food production andoperations. For ISRU, the ‘Prospect to Product’philosophy starts with Destination Reconnaissance &Resource Assessment, followed by ResourceAcquisition, Isolation, and Preparation, leading intoResource Processing (which is further subdivided intomission consumables and feedstocks for constructionand manufacturing). The ISRU Envisioned Futurealso considers what resources are available andattempts to address what and when these resourceswill be evaluated and harnessed, as well asconsidering which products/commodities can beobtained for early use and which ones require moretime and/or users of refined products.It Takes an Architecture: ISRU does not existon its own. By definition, it requires customers/users SHORT TITLE HERE: A. B. Author and C. D. Authorto use the products/commodities produced by ISRUsystems. Also, for an ISRU capability to exist, itmust obtain products and services from other systemsand infrastructure. An important aspect of the STARprocess and the ISRU Envisioned Futures Prioritiesstrategy is to identify and link all of these systems andcapabilities to achieve the desired end state (Figure2).Figure 2. ISRU as Part of a Larger ArchitectureISRU Capability Drivers: The guidingprinciples for NASA’s Space TechnologyDevelopment for Artemis are to develop criticaltechnologies and capabilities that enable (i) asustainable Lunar surface presence, (ii) the future goalof sending humans to Mars, and (iii) promotingcritical technologies to enable future science andcommercial missions. It is a major goal of theArtemis campaign to establish some sort of base campat the lunar South Pole by approximately the end ofthe decade. The ISRU Envisioned Futures Prioritiesstrategy is aligned with the Artemis campaign todevelop and demonstrate ISRU capabilities in thistimeframe that could lead to sustained surfaceoperations, infrastructure growth, and commercialoperations in the next decade (Figure 3).Figure 3. ISRU Dual Path to Full Implementation and CommercializationState of the Art and Gaps: To achieve theenvisioned future, an extensive effort was performedto understand the State of the Art (SOA) for ISRUgoing back decades, and to assess the SOA against thenear and long-term goals and objectives of the ISRUStrategic Outcome objectives. While the releasedISRU Envisioned Futures Priorities only includes atop-level definition of both the SOA and Gaps, furtherinformation on these for ISRU can be found in theISRU Gap Assessment Study performed for theInternational Space Exploration Coordination Group(ISECG) [2]. To provide further guidance to industryand academia, a top level assessment was performedand provide that divides critical areas of ISRUcapabilities and technologies into 3 categories:Significant Funding, Partially Covered/MoreRequired, and Limited/No Funded Activities.Envisioned Future Priorities- Next Steps forISRU: While a significant amount of work over abroad range of technology areas has been performedover the last several years for lunar ISRU, to reach theenvisioned future for ISRU, a lot more work isrequired at the technology level leading to bothsystems and technology demonstrations in the nearfuture. To guide investments within NASA, industry,and academia, 5 specific areas of high priority wereidentified. These are:1.Complete development of the Water and Oxygen Mining Paths and close technology gaps, with emphasis on oxygen extraction from Highland regolith and parallel paths for polar water mining.2.Expand development of metal extraction and feedstock for manufacturing and construction, with emphasis on aluminum and initial/easy to obtain/make construction feedstocks leading to more refined metals and other regolith resources. Also, evaluate biologically inspired/derived technologies in bio-mining, bio-plastic, and other feedstock commodities.3.Ensure the resource assessment needed for future ISRU commercial operations is coordinated with both near/long-term science objectives as well as Artemis mission locations of interest.4.Initiate NASA and industry-led system-level analyses, integration, and testing activities for ISRU capabilities. While significant work has been performed at the technology and subsystemlevel, it is now important to understand how these technology investments can be leveraged and utilized in actual systems and applications5.Initiate lunar ISRU technology flight demonstrations leading to initial ‘Pilot Plant’ end-to-end production capability demonstrations, led by industry

ISRU↗

Mapping Inquiry Tool (MapIT) Database

The Mapping Inquiry Tool (MapIT) database consists of a geodatabase and data catalog of geologic, geophysical, structural, hydrologic, and contextual data, based on the data types to support geologic carbon storage activities and other subsurface energy systems resource assessments. The database was aggregated from publicly available data across the USA from state and federal entities. The database is structured by categories including rock unit geology, boundaries, national CS datasets, geophysical data, faults and structural data, infrastructure, surface hydrology, groundwater, and more. The data described in the data catalog is also available in the Mapping Inquiry Tool (https://edx.netl.doe.gov/dataset/mapping-inquiry-tool). Version 3 of the geodatabase and data catalog have been updated as of 5/17/2024. The database was published with a limited number of layers. The Catalog V3 contains many more resources than the geodatabase, documenting all layers that will be included in MapIT, and includes links to the original sources of the data. Within the catalog, in the final column, there is information about if the file is included in the geodatabase or not. Use the links provided in the catalog to download data directly from the original source if not included in the geodatabase. Four resources are included in this submission: 1. Geodatabase 2. ReadMe file 3. Catalog of data layers and additional data resources 4. Web link to a resource describing the motivation and reviewing the content of the geodatabase - DOE NETL Carbon Storage Site Mapping Inquiry Tool Database

carbon storage↗

Data and Tools for Exploring New Pumped Storage Hydropower Deployment Opportunities

Pumped storage hydropower (PSH) is a flexible energy storage technology with the potential to facilitate variable renewable energy integration into the decarbonized electric grid of the future. NREL is developing new data and tools to help understand opportunities for new PSH deployment, including nationwide resource assessment data, a bottom-up component-level cost model, and a lifecycle greenhouse gas emissions calculator. These datasets lay the foundation for better-informed grid planning decisions about how PSH fits into a future portfolio of generation, transmission, and storage assets.

CEM↗

Development of a Metocean Reference Site near the Massachusetts and Rhode Island Wind Energy Areas

This project developed the first long-term U.S.-based offshore MetOcean Reference Site (MORS-1) by capitalizing on a unique combination of one of the few existing publicly available offshore wind energy metocean observational campaigns in the United States and the only existing research-grade offshore fixed tower. Data collected at MORS-1 has facilitated improved wind resource assessments, improved short-term power production estimates, and reduced costs for sensor validation and calibration efforts, which translate into reduced overall wind energy project risk and cost for developers. Now operational, MORS-1 serves the needs of both industry and researchers using a nonprofit, joint industry-academic partnership model. Led by the Woods Hole Oceanographic Institution, the MORS-1 development effort focused on creating both a recognized organizational structure that will ensure support of the MORS-1 by the wider wind energy industry and research community, and a highly validated data collection and sensor validation facility that will serve as the premier location for cost- and uncertainty-reducing resource characterization and research efforts.

17 WIND ENERGY↗

A Twenty-Year Analysis of Winds in California for Offshore Wind Energy Production Using WRF v4.1.2

Offshore wind resource characterization in the United States relies heavily on simulated winds from numerical weather prediction (NWP) models, given the lack of hub-height observations offshore. One such NWP data set used extensively by U.S. stakeholders is the Wind Integration National Dataset (WIND) Toolkit, a 7-year time-series data set produced in 2013 by the National Renewable Energy Laboratory. In this study, we present an update to that data set for offshore California that leverages recent advancements in NWP modeling capabilities and extends the period of record to a full 20 years. The data set predicts a significantly larger wind resource (0.25–1.75 m s-1 stronger), including in three Call Areas that the Bureau of Ocean Energy Management is considering for commercial activity. We conduct a set of yearlong simulations to study factors that contribute to this increase in the modeled wind resource. The largest impact arises from a change in the planetary boundary layer parameterization from the Yonsei University scheme to the Mellor-Yamada-Nakanishi-Niino scheme and their diverging wind profiles under stable stratification. Additionally, we conduct a refined wind resource assessment at the three Call Areas, characterizing distributions of wind speed, shear, veer, stability, frequency of wind droughts, and power production. We find that, depending on the attribute, the new data set can show substantial disagreement with the WIND Toolkit, thereby driving important changes in predicted power.

49 EE - Wind and Water Power Program - Wind (EE-4W↗

Approaches to wind resource verification

Verification of the regional wind energy resource assessments produced by the Pacific Northwest Laboratory addresses the question: Is the magnitude of the resource given in the assessments truly representative of the area of interest? Approaches using qualitative indicators of wind speed (tree deformation, eolian features), old and new data of opportunity not at sites specifically chosen for their exposure to the wind, and data by design from locations specifically selected to be good wind sites are described. Data requirements and evaluation procedures for verifying the resource are discussed.

Barchet, W. R.↗