Assessing CO2 Storage Potential in the Eastern Gulf of Mexico Continental Shelf
Southeast Offshore Storage Resource Assessment (SOSRA): Storage Potential
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Southeast Offshore Storage Resource Assessment (SOSRA): Storage Potential
The utility of TM data natural resource assessment was evaluated with emphasis on manual interpretation and digital classification. The improved spatial resolution of TM data, as compared with MSS data, aided in the location of roads, small stock ponds, and many other land features, permitting positive identification of landmarks. With the TM, there was more efficient manual interpretation of land use, better identification of resource types, and improved assessment of the ecological status of natural vegetation. Band 5 and band 7 aided in defining water resources, wetland vegetation resources, and other terrain features. Results from TM and TM simulator data suggest that the coefficient of variation for major land cover types is less for TM data than for equivalent MSS data. Although the amount of information in bands 5 and 7 is small, it is unique since the same information cannot be derived from the MSS four-band spectral region.
Supplementary files associated with the Unconventional Rare earth and Critical minerals (URC) Resource Assessment method publication (Link/DOI to publication TBD).
Levelized Cost of Energy (LCOE) is an important metric to evaluate the cost and performance of electricity production generation alternatives, and combined with other measures, can be used to assess the economics of future hydropower development. Multiple assumptions on input parameters are required to calculate the LCOE, which each contain some level of uncertainty, in turn affecting the accuracy of LCOE results. This paper explores these uncertainties, their sources, and ultimately the level of variability they introduce at the screening level of project evaluation for non-powered dams (NPDs) across the U.S.Owing to site-specific differences in site design, the LCOE for hydropower varies significantly from project to project unlike technologies with more standardized configurations such as wind and gas. Therefore, to assess the impact of LCOE input uncertainty on the economics of U.S. hydropower resources, these uncertainties must be modeled across the population of potential opportunities. To demonstrate the impact of uncertainty, resource data from a recent nationwide non-powered dam (NPD) resource assessment (Hadjerioua et al., 2012) and screening-level predictive cost equations (O’Connor et al., 2015) are used to quantify and evaluate uncertainties in project capital and operations & maintenance costs, and generation potential at broad scale. LCOE dependence on financial assumptions is also evaluated on a sensitivity basis to explore ownership/investment implications on project economics for the U.S. hydropower fleet.The results indicate that the LCOE for U.S. NPDs varies substantially. The LCOE estimates for the potential NPD projects of capacity greater than 1 MW range from 40 to 182 $/MWh, with average of 106 $/MWh. 4,000 MW could be developed through projects with individual LCOE values below 100 $/MWh. The results also indicate that typically 90 % of LCOE uncertainty can be attributed to uncertainties in capital costs and energy production; however, for small projects (below 10 MW) O&M uncertainty plays an important role. The potential NPDs have costs with uncertainty bands extending well above 100 $/MWh in some cases. A truly representative evaluation should complement LCOE with an assessment of potential revenues from the provision of ancillary services. Moreover, hydroelectric production is often part of multipurpose water resource projects where other purposes (e.g., irrigation, flood control, navigation, recreation, etc.) also provide value. Neither of these considerations are accounted for LCOE.
The production of all forms of energy consumes water. To meet increased energy demands, it is essential to quantify the amount of water consumed in the production of different forms of energy. By analyzing the water consumed in different technologies, it is possible to identify areas for improvement in water conservation and reduce water stress in energy-producing regions. The transportation sector is a major consumer of energy in the United States. Because of the relationships between water and energy, the sustainability of transportation is tied to management of water resources. Assessment of water consumption throughout the life cycle of a fuel is necessary to understand its water resource implications. To perform a comparative life cycle assessment of transportation fuels, it is necessary first to develop an inventory of the water consumed in each process in each production supply chain. The Greenhouse Gases, Regulated Emissions, and Energy Use in Transportation (GREET) model is an analytical tool that can used to estimate the full life-cycle environmental impacts of various transportation fuel pathways from wells to wheels. GREET is currently being expanded to include water consumption as a sustainability metric. The purpose of this report was to document data sources and methodologies to estimate water consumption factors (WCF) for the various transportation fuel pathways in GREET. WCFs reflect the quantity of freshwater directly consumed per unit production for various production processes in GREET. These factors do not include consumption of precipitation or low-quality water (e.g., seawater) and reflect only water that is consumed (i.e., not returned to the source from which it was withdrawn). The data in the report can be combined with GREET to compare the life cycle water consumption for different transportation fuels.
The US Geological Survey (USGS) resource assessment (Williams et al., 2009) outlined a mean 30GWe of undiscovered hydrothermal resource in the western US. One goal of the Geothermal Technologies Office (GTO) is to accelerate the development of this undiscovered resource. The Geothermal Technologies Program (GTP) Blue Ribbon Panel (GTO, 2011) recommended that DOE focus efforts on helping industry identify hidden geothermal resources to increase geothermal capacity in the near term. Increased exploration activity will produce more prospects, more discoveries, and more readily developable resources. Detailed exploration case studies akin to those found in oil and gas (e.g. Beaumont, et al, 1990) will give operators a single point of information to gather clean, unbiased information on which to build geothermal drilling prospects. To support this effort, the National Renewable Energy laboratory (NREL) has been working with the Department of Energy (DOE) to develop a template for geothermal case studies on the Geothermal Gateway on OpenEI. In fiscal year 2013, the template was developed and tested with two case studies: Raft River Geothermal Area (http://en.openei.org/wiki/Raft_River_Geothermal_Area) and Coso Geothermal Area (http://en.openei.org/wiki/Coso_Geothermal_Area). In fiscal year 2014, ten additional case studies were completed, and additional features were added to the template to allow for more data and the direct citations of data. The template allows for: Data - a variety of data can be collected for each area, including power production information, well field information, geologic information, reservoir information, and geochemistry information. Narratives ? general (e.g. area overview, history and infrastructure), technical (e.g. exploration history, well field description, R&D activities) and geologic narratives (e.g. area geology, hydrothermal system, heat source, geochemistry.) Exploration Activity Catalog - catalog of exploration activities conducted in the area (with dates and references.) NEPA Analysis ? a query of NEPA analyses conducted in the area (that have been catalogued in the OpenEI NEPA database.) In fiscal year 2015, NREL is working with universities to populate additional case studies on OpenEI. The goal is to provide a large enough dataset to start conducting analyses of exploration programs to identify correlations between successful exploration plans for areas with similar geologic occurrence models.
This poster provides an overview of using photovoltaic reference cells for solar resource assessment.
This guide describes how to conduct a Solar Resource and Infrastructure Assessment. The guide is designed to assist community officials, volunteers, and regional planning agency staff in conducting a preliminary assessment for a municipality, community, or other jurisdiction, based primarily on a desktop analysis of existing documents and data. The guide provides a process that can be used to inventory and describe existing infrastructure, community needs, and resources from the perspective of solar development planning.
The U.S. Geological Survey (USGS) resource assessment (Williams et al., 2008) outlined a mean 30 GWe of undiscovered hydrothermal resource in the western United States. One goal of the U.S. Department of Energy's (DOE) Geothermal Technology Office (GTO) is to accelerate the development of this undiscovered resource. DOE has focused efforts on helping industry identify hidden geothermal resources to increase geothermal capacity in the near term. Increased exploration activity will produce more prospects, more discoveries, and more readily developable resources. Detailed exploration case studies akin to those found in oil and gas (e.g. Beaumont and Foster, 1990-1992) will give developers central location for information gives models for identifying new geothermal areas, and guide efficient exploration and development of these areas. To support this effort, the National Renewable Energy Laboratory (NREL) has been working with GTO to develop a template for geothermal case studies on the Geothermal Gateway on OpenEI. In 2012, the template was developed and tested with two case studies: Raft River Geothermal Area (http://en.openei.org/wiki/Raft_River_Geothermal_Area) and Coso Geothermal Area (http://en.openei.org/wiki/Coso_Geothermal_Area). In 2013, ten additional case studies were completed, and Semantic MediaWiki features were developed to allow for more data and the direct citations of these data. These case studies are now in the process of external peer review. In 2014, NREL is working with universities and industry partners to populate additional case studies on OpenEI. The goal is to provide a large enough data set to start conducting analyses of exploration programs to identify correlations between successful exploration plans for areas with similar geologic occurrence models.
The USGS Resource Assessment (Williams et al. 2008) outlined a mean 30 GW, of Undiscovered Hydrothermal Resource in the western U.S. One goal of the Geothermal Technology Office (GTO) is to accelerate the development of this undiscovered resource. To help guide its future data collection efforts, GTO funded a data gap analysis in FY2012 to identify high potential hydrothermal areas where critical data are needed. For the gap analysis, information was collected about existing data and data coverage maps were created with this information. Next, these maps were compared with the USGS resource potential maps to identify priority sites for exploration data collection. Though there are many types of data that can be used for hydrothermal exploration, five types of exploration data were targeted for this analysis. These data types were elected for their regional reconnaissance potential, and include many of the primary exploration echniques currently used by the geothermal industry. The data types include: 1) well data; 2) geologic maps; 3) fault maps; 4) geochemistry data; and 5) geophysical data. To determine data coverage, metadata for exploration data (including data type, data status, and coverage information) were collected and catalogued. Many industry, university, laboratory, and agency personnel were contacted in order to collect metadata for this effort. Data and metadata provided by the contributors to the National Geothermal Data System (NGDS) were also incorporated in the gap analysis. An online tool was developed to allow all geothermal data providers to directly add metadata themselves and view the results of the analys is via maps of data coverage in Geothermal Prospector (http://maps.nrel.gov/gt_prospector). A grid of the contiguous U.S. was created with 88,000 10-km by 10-km grid cells, and each cell was populated with the status of data availability corresponding to the five data types. Using these five data coverage maps and the USGS Resource Potential Map, sites were identified for future data collection efforts. These sites signify both that the USGS has indicated high favorability of occurrence of geothermal resources and that data gaps exist.
The U.S. Department of Energy's National Renewable Energy Laboratory collaborates with the solar industry to establish high quality solar and meteorological measurements. This Solar Resource and Meteorological Assessment Project (SOLRMAP) provides high quality measurements to support deployment of power projects in the United States. The no-funds-exchanged collaboration brings NREL solar resource assessment expertise together with industry needs for measurements. The end result is high quality data sets to support the financing, design, and monitoring of large scale solar power projects for industry in addition to research-quality data for NREL model development. NREL provides consultation for instrumentation and station deployment, along with instrument calibrations, data acquisition, quality assessment, data distribution, and summary reports. Industry participants provide equipment, infrastructure, and station maintenance.
Carbon Storage Technical Viability Approach is a comprehensive evaluation of potential geologic carbon storage sites that includes classic subsurface resource assessment components such as reservoir suitability in addition to hazard, environmental, social, regulatory, and jurisdiction components that may enhance or hinder successful carbon storage. Data for assessments of technically viable carbon storage span many categories, types; are disparate and numerous. Variables and types of data required to support CS assessments were previously not clearly defined and documented. Contextualizing available data indicates their utility, potential uncertainty, and gaps. This presentation details the Carbon Storage Technical Viability Approach, the associated matrix and database, and initial results from a portion of the national data availability assessment that contextualizes the data available to support carbon storage projects. Presented at the American Association of Petroleum Geologists' Carbon Capture Utilization and Storage (SPE-AAPG-SEG CCUS 2024) conference in Houston, TX, March 11-13, 2024.
The project Characterization of Most Promising Sequestration Formations in the Rocky Mountain Region is one of 9 site characterization projects that were implemented as part of ARRA (American Recovery and Reinvestment Act). Data from this project was used to improve resolution of data in NATCARB in the area of study. Data related to this study has already been incorporated in NATCARB Atlas. The Rocky Mountain Carbon Capture and Storage (RMCCS) project investigated multiple geologic formations and characterized a local site on the Colorado Plateau for future CCS opportunities. The RMCCS project focused on the Cretaceous Dakota, Jurassic Entrada, and Pennsylvanian Weber Sandstones, the three largest regional formations. All formations in this project are potential CO2 storage resources for future power plants, natural gas processing plants, cement plants, and oil shale development projects. The area adjacent to Craig, Colorado, (Sand Wash Basin) was the area selected for detailed geologic characterization on the RMCCS project. The basin was selected in part because the geology can be extrapolated to other sites on the Colorado Plateau. Field mapping and seismic surveys were conducted to identify and evaluate the basin's structural configuration. A 9,745-foot deep characterization well was drilled to collect 131 feet of core and a suite of geophysical well log data. Petrophysical tests on samples of core were used to calibrate geophysical log data, which can be used to obtain storage resource estimates and evaluate associated uncertainty as well as simulate the hydrologic behavior of injected CO2. A detailed analysis of the primary formations (Dakota, Entrada and Weber sandstones) yielded a more accurate CO2 storage resource assessment for these formations within the Colorado Plateau; RMCCS estimates indicate a total CO2 storage resource of more than 38,000 million metric tons. The characterization of the Sand Wash Basin (2-D seismic surveys, multiple well logs and lithological, petrophysical and geochemical analyses) allowed for a detailed 3-D model to be constructed. The model served as the framework for analyses ranging from CO2 storage resource, injectivity, and subsurface flow to uncertainty estimates to evaluation of risk.
The objective of this design report is to provide an assessment of current technologies used for production, dewatering, and converting microalgae cultivated in open-pond systems to biofuel. The original draft design was created in 2011 and has subsequently been brought into agreement with the DOE harmonized model. The design report extends beyond this harmonized model to discuss some of the challenges with assessing algal production systems, including the ability to (1) quickly assess alternative algal production system designs, (2) assess spatial and temporal variability, and (3) perform large-scale assessments considering multiple scenarios for thousands of potential sites. The Algae Logistics Model (ALM) was developed to address each of these limitations of current modeling efforts to enable assessment of the economic feasibility of algal production systems across the United States. The (ALM) enables (1) dynamic assessments using spatiotemporal conditions, (2) exploration of algal production system design configurations, (3) investigation of algal production system operating assumptions, and (4) trade-off assessments with technology decisions and operating assumptions. The report discusses results from the ALM, which is used to assess the baseline design determined by harmonization efforts between U.S. DOE national laboratories. Productivity and resource assessment data is provided by coupling the ALM with the Biomass Assessment Tool developed at PNNL. This high-fidelity data is dynamically passed to the ALM and used to help better understand the impacts of spatial and temporal constraints on algal production systems by providing a cost for producing extracted algal lipids annually for each potential site.
Biofuels produced from both terrestrial and algal biomass feedstocks can contribute to energy security while providing economic, environmental, and social benefits. To assess the potential for land competition between these two feedstock types in the United States, we evaluate a scenario in which 41.5 x 109 L yr-1 of second-generation biofuels are produced on pastureland, the most likely land base where both feedstock types may be deployed. This total includes 12.0 x 109 L yr-1 of biofuels from open-pond microalgae production and 29.5 x 109 L yr-1 of biofuels from terrestrial dedicated feedstock supply systems. Under these scenarios, open-pond microalgae production is projected to use 1.2 million ha of private pastureland, while terrestrial dedicated feedstock supply systems would use 14.0 million ha of private pastureland. A spatial meta-analysis indicates that potential competition for land under these scenarios would be concentrated in 110 counties, containing 1.0 and 1.7 million hectares of algal and terrestrial dedicated feedstock production, respectively. A land competition index applied to these 110 counties suggests that 38 to 59 counties could experience competition for upwards of 40% of a county’s pastureland. However, this combined 2.7 million ha represents only 2%-5% of total pastureland in the U.S., with the remaining 12.5 million ha of algal or terrestrial dedicated feedstock production on pastureland in non-competing areas.
The dispositioning of nuclear waste generated at facilities across the country is an ongoing battle that affects us all. National laboratories and research centers dealing in medical research, clean energy, and other nuclear activities such as the Department of Energy (DOE) facilities face the need to properly manage and dispose of nuclear waste. A dynamic modeling solution would enable the DOE and others to make decisions on waste disposal and technological options. In doing so, this research explores modeling techniques using available data to address these situations. The focus being on developing an initial robust and adaptable discrete event model using the ExtendSim tool. This modeling effort will target the dispositioning of transuranic waste at the Savannah River National Laboratory (SRNL) which can be expanded to represent the current state of disposition process for waste generated at other DOE facilities. The model aims to assess resource allocation and waste processing options to stabilize productivity and cut the backlog of nuclear waste. By assessing the results of different scenarios, this research aims to provide actionable insights for the DOE. This approach has the potential to significantly improve the management of radioactive waste, offering the capability of evaluating options for optimizing the process for nuclear waste disposal. The findings of this study can serve as a valuable resource for decision-makers and other national laboratories, or research entities engaged in nuclear operations by enabling them to make more informed choices.
This paper introduces T&D LIBRA, a HELICS-based dynamic co-simulation framework designed for transmission and distribution (T&D) load and inverter-based resource assessment. This framework is designed to model interactions between single-phase induction motors (i.e., Motor-D), distributed energy resources (DERs) and the transmission network, emphasizing system stability during fault conditions. The primary objective of this research is to study the fault-induced delayed voltage recovery (FIDVR) behavior of the T&D networks using the co-simulation framework and to compare the results with conventional PSS/E only simulations. Simulations are validated using T&D co-simulations with a single distribution node and the IEEE 123-bus distribution test case. The co-simulation results demonstrate the value of using T&D co-simulations to capture motor stalling, DER tripping and other sources of voltage diversity on distribution networks.
Recent resource assessments conducted by the United States Department of Energy have identified significant opportunities for expanding hydropower generation through the addition of power to non-powered dams and on undeveloped stream-reaches. Additional interest exists in the powering of existing water resource infrastructure such as conduits and canals, upgrading and expanding existing hydropower facilities, and the construction new pumped storage hydropower. Understanding the potential future role of these hydropower resources in the nation’s energy system requires an assessment of the environmental and techno-economic issues associated with expanding hydropower generation. To facilitate these assessments, this report seeks to fill the current gaps in publically available hydropower cost estimating tools that can support the national-scale evaluation of hydropower resources.