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NASA NTRS2000

Thermodynamics of Aqueous Organic Sulfur Compounds: A Key to the Organic Geochemistry of Hydrothermal Systems?

Hydrothermal environments are locations of varied geochemistry due to the disequilibrium between vent fluids and seawater. The disequilibrium geochemistry has been hypothesized to include reactions to synthesize organic compounds. Observations of the organic geochemistry of hydrothermal vent sites has received little attention. Experimental simulations of these environments, however, indicate that organic compounds may have difficulty forming in a purely aqueous environment. On the other hand, thiols. thioesters and disulfides have been implicated as reaction intermediates between CO or CO2 in experiments of carbon reduction in hydrothermal environments as well as in a variety of biological processes and other abiotic reactions (Wachtershauser, 1990, OLEB 20, 173; Heinen and Lauwers, 1996, OLEB 26, 13 1, Huber and Wachtershauser, 1997, Science 276, 245; Russell et al., 1998, in Thermophiles: The keys to molecular evolution and the origin of life?). The reduction of CO2 to thiols, for example, is observed using the FeS-H2S/FeS2 couple to provide the reducing power (see Schoonen et al., 1999, OLEB 29, 5). In addition, the enzyme involved in final stage of methanogenesis, coenzyme-M, is itself a thiol. Thus, organic sulfur compounds may hold the key to the organic chemistry leading to the origin of life at high temperatures. Understanding the biochemical processes of microorganisms that can live to temperatures at least as high as 113 C (Blochl et al., 1996, Extremophiles 1, 14) requires knowledge of the properties of the chemical reactions involved. In order to assess the role of aqueous organic sulfur compounds in hydrothermal organic geochemistry, we have been attempting to determine their thermodynamic properties. We have culled the literature to obtain the properties of organic sulfur compounds. We are able to calculate a number of essential properties, such as free energies of formation, from solubility data available in the literature together with standard properties of organic sulfur gases. However, a number of the properties for aqueous organic sulfur compounds have not been experimentally determined. Furthermore, most of thermodynamic data that are available are for 25 C and 1 bar. In order to determine reaction properties to temperatures and pressures appropriate to the hydrothermal conditions in which thermophilic organisms actually live, we use equations of state developed by Helgeson and co-workers (Helgeson et al., 1981, AJS 281, 1249). A key piece of information needed to go up in temperature is the partial molal heat capacity, which is one of the properties for which experimental data are unavailable for nearly all organic sulfur compounds. We have used correlation methods to determine the partial molal heat capacities and volumes of many organic solutes. These estimates allow us to asses the role of organic sulfur compounds during the reduction of carbon in hydrothermal settings. We will present these data, along with examples of the thermodynamic properties of reactions involving aqueous organic sulfur compounds.

Schulte, Mitchell↗

NASA NTRS2018

Molecular Dynamics of ULTEM 9085 for 3D Manufacturing: Spectra, Thermodynamic Properties, and Shear Viscosity.

We present results of a molecular dynamic analysis of welding at the polymer-polymer interface. The analysis is performed for polyetherimide/ polycarbonate polymer blends. The work is motivated by the applications to 3D manufacturing in space. In the first part of the report, we discuss bulk and spectral characteristics of the amorphous polymer blends. The vibrational and infra-red spectra obtained using auto-correlation functions calculations in molecular dynamics are compared with the experimental spectra. The mechanical and thermal properties of the samples including heat capacity, bulk modulus, and thermal expansion coefficients are estimated and compared with experimental values. In the second part of the report, we discuss the result of molecular dynamical modeling of shear viscosity in a fully atomistic model of amorphous polymer blends with flat interface. The key result of the research is the demonstration of shear thinning behavior of the shear viscosity as a function of shear rate which is in good agreement with experimental data.

Luchinsky, Dmitry G.↗

NASA NTRS2019

On-Orbit Xenon Refueling Loading Times and Transient Analysis

The Power and Propulsion Element (PPE) of the Lunar Orbital Platform-Gateway will demonstrate the first on-orbit refueling of xenon propellant for a solar electric propulsion system. An analysis was performed in Microsoft Excel to determine what factors influence the overall refueling time of a single 2,000-kilogram capacity xenon propellant tank, as well as provide estimates for overall refueling duration. Due to the high heat of compression of xenon, the propellant tank could exceed its maximum allowable temperature during refueling if the xenon flow rate and temperature are unregulated. In order to prevent overheating, a logic based "bang-bang" operation was used for refueling, shutting off the mass feed when the tank reached a maximum temperature. Heat is removed from the tank via radiation to the surrounding spacecraft bus. The analysis shows that optimizing key parameters such as mass flow rate into the tank, residual propellant in the tank during the onset of refueling, and tank diameter significantly reduces the overall refueling duration. Optimization is not straightforward, however, as the loading time does not trend monotonically with the parameters. Overall, the most significant impact on loading duration comes from altering the residual propellant in the tank. Increasing the mass of residual propellant from 2 percent to 20 percent reduces the overall refueling duration by 56 percent. Future work based on this analysis includes creation of a SINDA/FLUINT model and building a ground-based xenon refueling system emulator.

Xenon↗

DOE OSTI2016

System and method for design and optimization of grid connected photovoltaic power plant with multiple photovoltaic module technologies

A system and method of using one or more DC-DC/DC-AC converters and/or alternative devices allows strings of multiple module technologies to coexist within the same PV power plant. A computing (optimization) framework estimates the percentage allocation of PV power plant capacity to selected PV module technologies. The framework and its supporting components considers irradiation, temperature, spectral profiles, cost and other practical constraints to achieve the lowest levelized cost of electricity, maximum output and minimum system cost. The system and method can function using any device enabling distributed maximum power point tracking at the module, string or combiner level.

14 SOLAR ENERGY↗

DOE OSTI2018

Hydropower Development Opportunities for Alaska Native Villages

As a part of the Department of Energy’s (DOE) 2014 study on hydropower new stream-reach development (NSD) opportunities in the U.S., Oak Ridge National Laboratory (ORNL) coordinated with the Alaskan Energy Authority (AEA) and the United States Army Corps of Engineers to assess Alaska’s undeveloped hydropower potential at sites where no dams currently exist. That study identified 437 feasible sites with a combined capacity of 4,723 MW (Kao et al., 2014). In 2016, ORNL met with the U.S. Department of Energy-Alaska Office to discuss hydropower development opportunities to support Alaska Native villages. ORNL, with AEA’ collaboration is evaluating opportunities to increase renewable energy generation for these villages based on the NSD assessment, recent project license applications, and candidate Alaska Renewable Energy Fund projects.Using data for village location, population, diesel consumption, generation and cost, and proximity to existing hydropower and transmission, an initial NSD site feasibility study was performed. To screen out villages and potential hydropower sites that did not meet high-level feasibility criteria, seven filters were used. Based on these filter values, only eleven villages passed all criteria. These eleven hydropower sites have a combined potential capacity of 2.95MW and could supply an estimated 12,934 MWh of renewable hydropower annually. Results indicate that these eleven villages could potentially reduce their total diesel usage by 520,000 gallons per year, which amounts to a present-day value of 50-year diesel savings totaling more than $57 million by tapping into this potential. Follow-up data collection, reconnaissance studies, and pre-feasibility analyses could provide more insight into hydropower development opportunities for Alaska Native villages and focus on the most promising development opportunities identified through this initial study.

Hadjerioua, Boualem↗

DOE OSTI2021

Queued Up: Characteristics of Power Plants Seeking Transmission Interconnection As of the End of 2020

Proposed large-scale electric generation and storage projects must apply for interconnection to the bulk power system via interconnection queues. While many projects that apply for interconnection are not subsequently built, data from these queues nonetheless provide a general indicator for mid-term trends in developer interest. Berkeley Lab compiled and analyzed data from all seven ISOs/RTOs in concert with 35 non-ISO utilities, representing an estimated 85% of all U.S. electricity load. We include all "active" projects in these generation interconnection queues through the end of 2020, as well as data on "completed" and "withdrawn" projects for five of the ISOs (CAISO, ISO-NE, MISO, NYISO, PJM). We find that the total capacity active in the queues is growing year-over-year, with over 750 GW of generation and an estimated 200 GW of storage capacity as of the end of 2020. Solar (462 GW) accounts for a large – and growing – share of generator capacity in the queues. Substantial wind (209 GW) capacity is also in development, 29% of which is for offshore projects (61 GW). In total, about 680 GW of zero-carbon capacity is currently seeking transmission access, as is 74 GW of natural gas capacity. Hybrids now comprise a large – and increasing – share of proposed projects, particularly in CAISO and the non-ISO West. 159 GW of solar hybrids (primarily solar+battery) and 13 GW of wind hybrids are currently active in the queues. However, much of this proposed capacity will not ultimately be built. Among a subset of queues for which data are available, only 24% of the projects seeking connection from 2000 to 2015 have subsequently been built. Completion percentages appear to be declining, and are even lower for wind and solar than other resources. Additionally, wait times are on the rise: in four ISOs, the typical duration from connection request to commercial operation increased from ~1.9 years for projects built in 2000-2009 to ~3.5 years for those built in 2010-2020. There are growing calls for queue reform to reduce cost, lead times, and speculation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2016

Thermophysical Properties and Corrosion Characterization of Low Cost Lithium Containing Nitrate Salts Produced in Northern Chile for Thermal Energy Storage

In recent years, lithium containing salts have been studied for thermal energy storage (TES) systems applications, because of their optimal thermophysical properties. In solar power plants, lithium is seen as a way to improve the properties of molten salts used today. Lithium nitrate is a good candidate for sensible heat storage, due to its ability to increase the salt mixture's working temperature range. In the present research, thermophysical properties characterization of lithium nitrate containing salts, produced in Chile, have been carried out. Corrosion evaluations of carbon and low chromium steels were performed at 390 degrees C for 1000 hours. Thermophysical properties of the salt mixtures, such as thermal stability and heat capacity, were measured before and after corrosion tests. Chemical composition of the salts was also determined and an estimation of Chilean production costs is reported. Results showed that purity, thermal stability and heat capacity of the salts were reduced, caused by partial thermal decomposition and incorporation of corrosion products from the steel.

14 SOLAR ENERGY↗

DOE OSTI2023

Lithium-Ion Battery Diagnostics Using Electrochemical Impedance via Machine-Learning

Diagnosing battery states such as health, state-of-charge, or temperature is crucial for ensuring the safety and reliability of electrochemical energy storage systems. While some states, such as temperature, may be measured using cheap sensors, accurate diagnosis of battery health metrics usually requires time-consuming performance measurements, making them infeasible for use in real-world operation. These health metrics can be measured during lab-testing and then estimated on-line using predictive life models or via state observer algorithms such as Kalman filters, but these predictive methods should be supplemented by actual measurement of battery health whenever possible to ensure reliability. Rapid measurement of battery health may be done by various types of fast diagnostic techniques such as electrochemical impedance spectroscopy (EIS), which can be performed in only a few minutes and require only a fraction of the energy and power needed for a full charge and discharge measurement. But there is a substantial challenge for estimating battery health using EIS data, as EIS is sensitive to cell temperature, state-of-charge, current, and resting time in addition to health. Thus, utilizing EIS data to predict battery capacity requires correcting for all these additional variables, a task that is extremely difficult to handle analytically. This talk utilizes machine-learning methods to estimate the effectiveness of battery capacity prediction from EIS data, leveraging a data set of hundreds of EIS measurements recorded at varying temperature and state-of-charge throughout a 500-day aging study of 32 commercial, large-format NMC-Graphite lithium-ion batteries. Using EIS as input to machine-learning models is complicated by the nonlinear response of impedance to battery health, temperature, and state-of-charge, as well as the collinearity between the impedance response at neighboring frequencies, which can easily lead to overfit models. To train robust models, features from EIS data need to be extracted from the data or some subset of critical frequencies selected. Many approaches for extracting and selecting features from EIS data from electrochemical analysis and machine-learning fields were identified for analysis: using the entire raw spectra; selection of one, two, or many frequencies from the entire spectra; selecting interesting points from the EIS measurement using domain knowledge; fitting EIS with an equivalent-circuit model; calculating statistics on the raw impedance values; and reducing the dimensionality of the data using unsupervised linear (principal component analysis) and non-linear (uniform manifold approximation and projection) methods. These approaches were rigorously compared using a machine-learning pipeline approach, training linear, Gaussian process, and random forest regression models and quantifying performance using cross-validation as well as a held-out test set. An artificial neural network model trained on the raw spectra was also tested. Promising pipelines were fine-tuned via Bayesian hyperparameter optimization using cross-validation loss and training with class-specific weights to counter data set imbalance. The most reliable method for utilizing impedance in this work was the selection of two optimal frequencies through an exhaustive search, resulting in about 2% mean absolute error on test data for both Gaussian process and random forest model architectures. Interrogation of a variety of models reveals critical frequencies of 100 Hz and 103 Hz for this data set, though the optimal set of frequencies is not necessarily intuitive, i.e., the best performing models are not simply those that use impedance at frequencies that have the highest correlation to the relative discharge capacity. The best performing model is an ensemble model, which is able to predict battery capacity with 1.9% mean absolute error for unseen cells using impedance recorded at a variety of temperatures and states-of-charge.

battery↗

DOE OSTI2017

Infusion of hydrogen into nanostructured bainitic steel

Highlights: • Results show that austenite is more effective in trapping hydrogen than α/γ interfaces. • The H desorption behaviour was accurately reproduced with local equilibrium model. • The trapping capacity of retained austenite originates from the austenite lattice sites. - Abstract: The trapping of hydrogen in nanostructured bainitic steel has been investigated using thermal desorption analysis, in order to determine the potency of the ferrite-retained austenite (α/γ) interfaces and retained austenite as trapping sites. Thermal desorption data showed that the volume of retained austenite is more effective in trapping hydrogen than the interfaces. There is a close correlation between the quantity of hydrogen and the retained austenite content rather than the density of interfaces. A local equilibrium model was able to reproduce the hydrogen desorption behaviour of saturated and unsaturated samples considering both retained austenite and α/γ interfaces as the trapping sites. A trap binding energy ranging from 47 to 52 kJ/mol was estimated for retained austenite, suggesting that the observed trapping capacity originates from the austenite lattice sites.

36 MATERIALS SCIENCE↗

DOE OSTI2021

A Circular Economy for Solar Photovoltaic System Materials: Drivers, Barriers, Enablers, and U.S. Policy Considerations

As PV capacity increases, owners are also decommissioning older system assets. Estimates based on a 30-year lifetime assumption found that cumulative U.S. end-of-life (EoL) PV modules could total one million metric tons (Mt) by 2030 and up to 10 million Mt by 2050 (Weckend, Wade, and Heath 2016). Beyond maintenance replacements, early retirements that are due to efficiency upgrades and extreme weather, as well as PV deployment beyond earlier expectations, would increase these projections. PV system owners must evaluate equipment management options for used modules and system components retired during maintenance activities, refurbishment, repowering and system decommissioning. PV manufacturers must also evaluate material management options from customer returns, defects, and scrap. Management options for early retired and EoL PV system material include reuse, repair for reuse, recycling-based resource recovery, storage, and disposal. Disposal of PV system material increases the burden on landfill capacity, while reuse, repair for reuse, and recycling-based resource recovery (reuse/repair/recovery) options salvage valuable materials and provide secondary market opportunities and ancillary benefits (Weckend, Wade, and Heath 2016; EPA 2019c; SWEEP 2019). PV system owners may also decide store used modules and components as spares, or in the interim before a reuse or EoL management decision is made. Despite potential secondary market opportunities and the potential benefits associated with the repair/reuse/recovery of PV system material, anecdotal evidence suggests that in the United States decommissioned PV modules are stored, landfilled or otherwise disposed of (Salim et al. 2019; CPUC 2019b; DTSC 2019b; NREL 2019a). Some modules are being disposed of in municipal nonhazardous landfills and federally regulated hazardous treatment, storage, and disposal facilities, and others are being stored in warehouses until economically viable repair/reuse/recycling becomes available (CPUC 2019b; DTSC 2019b; NREL 2019a; Libby and Shaw 2018). As awareness of current practices grows, and the demand for critical PV module material increases, U.S. industry stakeholders, regulators, and policymakers are starting to (1) consider solutions to drive and enable environmentally sustainable materials management decisions and behaviors and (2) identify barriers to a circular economy for PV system materials. Circular economy principles attempt to transition from a "take-make-consume-dispose" linear economic system to a circular system that allows for the long life, and the reuse/repair/recovery of products and materials (Ellen MacArthur Foundation 2020). We begin this report by summarizing the drivers, barriers, and enablers to a circular economy for PV system materials in the United States. We then report on our analysis of federal and state regulatory considerations that may impact the repair/reuse/recovery of PV materials, and potential civil and criminal liabilities associated with noncompliance. We then discuss state policies and initiatives in the United States that expressly address PV system decommissioning and repair/reuse/recovery of PV materials. We conclude by providing case studies of U.S. business models for the repair/reuse/recovery of PV system materials. Our results are based on legal and literature-based research and interviews with solar industry stakeholders, regulators, and policymakers.

14 SOLAR ENERGY↗

DOE OSTI2023

Cost of Fish Exclusion and Passage Technologies for Hydropower

Hydropower represents a reliable source of renewable energy and accounts for approximately 7% of the total electrical generation in the United States. Future expansion of hydropower is likely to be in the form of either smaller new stream development projects or powering existing non-powered dams. For these new projects to be successful, careful analysis of risks, costs, and uncertainty to offset reduced power production as well as ensuring the protection and safe passage of migratory fish to gain public support, will be required. Exclusion and passage are two common approaches to protect fish from entrainment and impingement at hydropower facilities. The thresholds for entrainment risk and requirements for exclusion and passage often differ depending on the species involved, the characteristics of the facility, and the goals of stakeholders. While the costs associated with environmental mitigations represent a large proportion of the total costs required for the licensing of hydropower facilities, little quantitative information is present within the literature regarding the specific costs of fish exclusion and passage. Working with FOA awardee Natel Energy, scientists at Oak Ridge National Laboratory were tasked with assessing the capital construction costs for downstream fish exclusion and passage infrastructure. This report used keyword searches of an existing environmental mitigation cost data set and manual extraction of additional cost data associated with protection, mitigation, and enhancement (PM&E) measures related to positive barrier screening and passage from regulatory licensing documents available in the Federal Energy Regulatory Commission (FERC) eLibrary. This approach yielded a total of 50 PM&E mitigation measures with estimated capital construction costs pertaining to positive barrier screens, 142 pertaining to passage studies, and 26 pertaining to passage-related studies. PM&E measures associated with positive barrier screens represented <10% of the 171 total FERC project dockets available in the data set. These data were highly skewed toward conventional relicensing projects, as <7% were associated with new stream development (NSD) projects. Results from these data indicate highly variable costs associated with fish screening, with flow-normalized costs one to two orders of magnitude higher for screening with the highest exclusion capability (≤0.09 in. spacing) compared with coarser screening (1 to 2 in.). Furthermore, estimated capital costs of passage infrastructure were positively related to the scale of the project based on installed capacity for some, but not all, types of passage. These data provide an initial baseline for estimating exclusion and passage costs for hydropower development and may help developers consider options for more fish-friendly generation technologies, though gaps remain relating to a lack of data, particularly for NSD projects. More data may still be available within the FERC eLibrary, but significant effort will be required to manually identify and extract the data for future analyses.

13 HYDRO ENERGY↗

DOE OSTI2026

Assessing Photovoltaic Capacity Factor Variability Using Long-Term Satellite Derived Solar Resource Data Under Brazilian Climate

Accurate estimation of photovoltaic (PV) energy yield and its variability is essential for reducing financial risk and supporting reliable system planning for rapidly expanding PV markets. In Brazil, high solar adoption and increasing levels of distributed energy resources are beginning to introduce operational challenges such as curtailment and evolving grid requirements. Understanding how natural variability in solar resource propagates into PV system performance is therefore increasingly important for both project design and grid integration. Modern PV yield assessments commonly rely on multi-year meteorological datasets and probabilistic exceedance metrics (e.g., P50/P90) to quantify energy yield uncertainty for project financing. However, the implications of long-term solar resource variability for PV system design choices and high-adoption grid conditions remain less well characterized for rapidly expanding markets such as Brazil. In particular, understanding how weather-driven variability propagates into PV production distributions and capacity factor expectations is important for evaluating curtailment exposure, deployment strategies, and storage requirements in regions experiencing rapid growth of distributed and utility-scale PV. Seasonal and interannual variability in atmospheric conditions can produce substantial fluctuations in monthly PV energy production, which propagate into uncertainty in annual energy yield and capacity factor expectations. Characterizing this variability using long-term meteorological datasets allows probabilistic estimation of PV system performance and provides improved insight into the range of expected PV energy outcomes. This study explores the use of long-term satellite-derived meteorological data from the National Solar Radiation Database (NSRDB) to evaluate the variability of photovoltaic system performance across multiple locations in Brazil. Using a 27-year dataset (1998-2024), PV system simulations are performed to characterize the distribution of annual and seasonal capacity factors and energy yield outcomes, while propagating key sources of meteorological variability and model uncertainty through the PV modeling chain. The analysis also investigates the sensitivity of PV performance outcomes to key system design assumptions within the PV modeling chain, including tracking configuration and system sizing parameters. The resulting probabilistic performance characterization provides insight into how weather-driven variability influences PV production expectations and capacity factor distributions. These results provide a foundation for evaluating how weather-driven variability interacts with high PV adoption and potential storage or curtailment mitigation strategies.

14 SOLAR ENERGY↗

DOE OSTI2016

Impacts of Federal Tax Credit Extensions on Renewable Deployment and Power Sector Emissions

Federal tax credits for renewable energy (RE) have served as one of the primary financial incentives for RE deployment over the last two decades in the United States. In December 2015, the wind power production tax credit and solar investment tax credits were extended for five years as part of the Consolidated Appropriations Act of 2016. This report explores the impact that these tax credit extensions might have on future RE capacity deployment and power sector carbon dioxide (CO2) emissions. The analysis examines the impacts of the tax credit extensions under two distinct natural gas price futures as natural gas prices have been key factors in influencing the economic competitiveness of new RE development. The analysis finds that, in both natural gas price futures, RE tax credit extensions can spur RE capacity investments at least through the early 2020s and can help lower emissions from the U.S. electricity system. More specifically, the RE tax credit extensions are estimated to drive a net peak increase of 48-53 GW in installed RE capacity in the early 2020s -- longer term impacts are less certain. In the longer term after the tax credits ramp down, greater RE capacity is driven by a combination of assumed RE cost declines, rising fossil fuel prices, and other clean energy policies such as the Clean Power Plan. The tax credit extension-driven acceleration in RE capacity development can reduce fossil fuel-based generation and lower electric sector CO2 emissions. Cumulative emissions reductions over a 15-year period (spanning 2016-2030) as a result of the tax credit extensions are estimated to range from 540 to 1420 million metric tonnes CO2. These findings suggest that tax credit extensions can have a measurable impact on future RE deployment and electric sector CO2 emissions under a range of natural gas price futures.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2025

Baseline Cost Model for Hydropower: Documentation (2025)

Hydropower currently contributes about 80 GW of conventional and 23 GW of pumped storage capacity to the United States (US) power grid. Previous studies have estimated a considerable amount of remaining US hydropower resources, including non-powered dams (NPD) (Hadjerioua et al., 2012), new stream-reach developments (NSD) (Kao et al., 2014), pumped storage hydropower (PSH) and canal/conduit (Kao et al., 2022). The combined theoretical capacity potential of these various hydropower resources is comparable to the existing US hydropower capacity. There is a continuing interest in developing this hydropower potential, particularly to help meet the increasing demand for electricity. However, available data (Sasthav and Oladosu, 2022) show that the rate of new hydropower development has slowed considerably over time despite the interest of industry stakeholders. This is partly due to the competition from other energy resources and from the highly dispersed nature of remaining hydropower resources, which lead to high information requirements for evaluating the feasibility of potential projects. Cost information provides the most succinct summary of the feasibility of a potential hydropower project required by stakeholders, including developers, investors, policymakers, consumer groups, etc., considering investment options. The best estimates of hydropower costs can be obtained through detailed engineering design and cost assessments of individual projects. However, this approach has high data and resource (time, funds, cross-disciplinary expertise) requirements that render it inapplicable for rapid cost estimation with limited data. Although innovative approaches can overcome some of these impediments (see Oladosu and Ma, 2024 for such an application to potential NPD projects), the development of such approaches still requires significant amounts of resources and are not generally applicable to all hydropower project types. Therefore, statistical and parametric methods using simpler cost specifications remain of significant utility to hydropower stakeholders and are, at the least, complementary to more detailed approaches, particularly when evaluating many potential projects.

13 HYDRO ENERGY↗

DOE OSTI2026

Basin-scale analysis of Mokelumne River Formation for multi-well CO 2 injection

Large-scale carbon sequestration will likely require multiple projects injecting CO 2 into the same subsurface formation, raising concerns about safe operation and efficient use of storage capacity. This study evaluates the long-term response of the Mokelumne River Formation in California’s Sacramento Basin to multi-megaton CO 2 injection using three geologic models of the formation and the open-source simulator GEOS. The analysis focuses on three aspects of reservoir performance: (1) average pressure increase and dissolved CO 2 mass after 30 years for varying well counts and injection rates, (2) pressure interference in a multi-well configuration, and (3) dynamic storage capacity with identification of overpressure-prone regions. The results show that average formation pressure increases linearly with injected mass, while CO 2 dissolution exhibits mixed scaling: approximately linear with the number of wells but sublinear with injection rate, indicating that distributing injection across more wells enhances dissolution more effectively than increasing per-well rates. Pressure-interference effects are significant, with lower-permeability conditions delaying their onset but amplifying their magnitude at later times. Dynamic capacity, defined by the first occurrence of pressure exceeding the local overburden-based limit anywhere in the formation, varies across geologic models and assumed overburden pressure gradients. A lower fidelity geologic model predicts nearly twice the storage capacity of the two higher fidelity models, which consistently estimate approximately 1 Gt under the upper-bound overburden pressure gradient considered for the Sacramento Basin. In all model scenarios, overpressure develops away from injection wells, particularly in higher-elevation regions, highlighting the importance of basin-scale modelling for identifying risks beyond the immediate well vicinity.

Basin-scale↗

DOE OSTI2021

Solar-to-Grid Public Data File for Utility-scale (UPV) and Distributed Photovoltaics (DPV) Generation, Capacity Credit, and Value for 2012-2020

Lawrence Berkeley National Laboratory (Berkeley Lab) estimates hourly project-level generation data for utility-scale solar projects and hourly county-level generation data for residential and non-residential distributed photovoltaic (PV) systems in the seven organized wholesale markets and 10 additional Balancing Areas. To encourage its broader use, Berkeley Lab has made this data file public here at OEDI, covering the years 2012-2020. The public project-level dataset is updated annually with data from the previous calendar year. For more information about the research project, including a technical report, briefing material, visualizations, and additional data, please visit the project homepage linked in this submission.

annual solar value↗

DOE OSTI2016

Low Temperature Geothermal Play Fairway Analysis For The Appalachian Basin: Phase 1 Revised Report November 18, 2016

Geothermal energy is an attractive sustainable energy source. Yet project developers need confirmation of the resource base to warrant their time and financial resources. The Geothermal Play Fairway Analysis of the Appalachian Basin evaluated risk metrics that communicate the favorability of potential low-temperature geothermal energy resources in reservoirs more than 1000 m below the surface. This analysis is focused on the direct use of the heat, rather than on electricity production. Four risk factors of concern for direct-use geothermal plays in the Appalachian Basin portions of New York, Pennsylvania, and West Virginia are examined individually, and then in combination: 1) thermal resource quality, 2) natural reservoir quality, 3) induced seismicity, and 4) utilization opportunities. Uncertainty in the risk estimation is quantified. Based on these metrics, geothermal plays in the Appalachian Basin were identified as potentially viable for a variety of direct-use-heat applications. The methodologies developed in this project may be applied in other sedimentary basins as a foundation for low temperature (50-150 °C), direct use geothermal resource, risk, and uncertainty assessment. Three methods with which to combine the four risk factors were used. Among these, the averaging of the individual risk factors indicates the most favorable counties within the study area are the West Virginia counties of Monongalia, Harrison, Lewis (dubbed the Morgantown–Clarksburg play fairway), Putnam, and Kanawha (Charleston play fairway), the New York counties of Chemung and Steuben plus adjacent Bradford county in Pennsylvania (Corning–Ithaca play fairway), and the Pennsylvania counties of Mercer, Crawford, Erie, and Warren, and adjacent Chautauqua county in New York (together, the Meadville–Jamestown play fairway). These higher priority regions are surrounded by broader medium priority zones. Also worthy of additional exploration is a broad region near Pittsburgh Pennsylvania, for which the available geological data are insufficient to fully analyze the geological risks but yet the population is high. First, to assess the spatial variation in the depth to which one would need to drill to obtain geothermal temperatures that are useful to a future project, the project used bottom-hole temperature data from Appalachian Basin oil and gas exploration. These bottom hole temperature data are abundant but of low quality. Second, the project examined the potential for sufficient water flow rates through rocks to harvest heat from a geothermal well field, considering only natural reservoirs. This analysis provides a very incomplete picture of spatial variability of natural reservoirs because the oil and gas reservoir data lack key properties and are spatially biased toward those locations with profitable amounts of hydrocarbons in the rock pore spaces. Third, in light of the fact that earthquake activity has been induced in several states by subsurface work related to the oil and gas industry, this project examined the potential for similar activity in the Appalachian Basin. Acknowledging that data for such a task are insufficient, we utilized what was available: records of seismic activity, regional estimates of the orientations of stress in the rocks, and locations and orientations of zones of lateral change in rock properties at depths down to several kilometers below Earth’s surface. With these data, we created a first approximation of spatially variable risks for induced earthquakes. Because no data existed with which to test the reliability of these methods, the results have a high degree of uncertainty. Fourth, we examined the spatial variability of the above-the-ground factors that contribute to the economical viability of projects to tap low-temperature geothermal resources for direct-use. We worked principally with population density as a regionally known variable that would impact the cost of district heating. The resulting maps omit the costs of producing the hot water from the ground, because the below-ground costs are directly coupled to the thermal resource risk factor and natural reservoir risk factor – later analyses of those costs will be needed. The result of the district heating analysis is highly skewed: few census locations yielded a low estimated surface cost. The team also identified more than 165 prospects for high value direct-use geothermal energy opportunities such as industrial sites, university campuses, and federal facilities, among others. At the closure of this regional analysis, the most significant technical uncertainties are 1) reservoir distribution and capacities; 2) validity of thermal resource maps, and 3) the holistic estimation of Levelized Cost of Heat for favorable geological situations.

15 GEOTHERMAL ENERGY↗

DOE OSTI2025

Williston Basin Resource Study for Commercial-Scale Subsurface Hydrogen Storage

The Energy & Environmental Research Center (EERC), in partnership with the U.S. Department of Energy (DOE) National Energy Technology Laboratory (NETL), the EERC’s State Energy Research Center (SERC), MPLX Operations LLC, and TC Energy Development Holdings Inc. (a subsidiary of TC Energy Corporation), studied the potential for subsurface hydrogen storage and recovery in the Williston Basin of western North Dakota. The project’s goal was to evaluate the feasibility of large-scale, secure geologic H 2 storage to support future hydrogen generation, storage, and use. This work included laboratory testing, H 2 –rock–fluid exposure experiments, literature reviews on H 2 embrittlement, and reservoir modeling and simulations. The study included an assessment of storage potential across three types of storage reservoirs using both reservoir simulation and DOE’s web-based tool SHASTA-HELP (Subsurface Hydrogen Assessment, Storage, and Technology Acceleration – Hydrogen Estimator for Logistical Planning), as well as investigation of potential H 2 production and markets for commercial-scale deployment. Building on prior EERC gas storage research, three storage options were selected for detailed evaluation: the Broom Creek Formation (a clastic saline reservoir), the Dickinson Lodgepole Mounds (DLM) complex (carbonate mud mound structures) of the Lodgepole Formation (an active oil and gas producing reservoir), and the Dunham Salt Interval of the Piper Formation (to be used for engineered salt cavern development). These targets were prioritized based on prior EERC research using datasets related to seal capacity, reservoir quality, mechanical integrity, and injectivity. Exposure tests on Broom Creek and DLM samples showed mineral dissolution and precipitation that increased brine salinity and altered reservoir rock surfaces. Although these results provide useful insight, they are limited by small sample sizes and short-term (30-day) exposure, requiring further study to assess long-term storage integrity. Salt formations were not tested because of their known nonreactivity and established mechanical stability. Results of reservoir simulations performed for a single site demonstrated that the Broom Creek Formation may be capable of receiving up to 42,000 tonnes of injected H 2 over 7 months via one well. H 2 recovery took place over 5 months, resulting in approximately 26,000 tonnes (~62% without cushion gas [CG]). This work suggests water production may be important and subsequent cycles of injection and production may perform more efficiently; however, significant site-specific work in the future is needed to assess actual reservoir performance of injection and withdrawal of H 2 storage. For oil reservoir potential, a multiple-well model was used to simulate injection of approximately 32,000 tonnes of H 2 into a single wellbore while simultaneously producing in place reservoir fluids from four offset wells to maintain reservoir pressure. The simulation results suggested a high recovery (~98%); in addition, cost advantages through existing infrastructure could be realized. Challenges in this reservoir include vi managing gas purity and leakage risks. In both scenarios, production of H 2 takes place in a single-well scenario with 10 cycles (7 months of injection and 5 months of production) over 10 years. Finally, the use of engineered caverns in the Dunhan Salt was evaluated, and the results suggest that while they have a smaller capacity (<1000 tonnes per cavern), they exhibit nearly complete gas recovery (>99%), fast response times, and low purity risk. While caverns in North Dakota may be smaller in capacity, fields can be developed in galleries to accommodate the volumetric needs and rapid turnaround times necessary to meet market demands. Geographic limitations and thin salt intervals in North Dakota may represent less total storage potential than salt domes elsewhere, but significant opportunities exist to expand this market for gas storage in North Dakota. A basinwide assessment was performed to estimate a first-of-its-kind value for H 2 storage on a large scale. DOE’s SHASTA-HELP, combined with EERC simulation work, was used to perform the assessment. Estimated H 2 storage potential varied widely for each formation type. The Broom Creek saline formation was estimated to have a storage potential of approximately 1.7–90.5 million tonnes (MMt). The DLM oil reservoirs were estimated to have 0.07–0.19 MMt of capacity. Notably, each of these estimates relies on significant assumptions regarding reservoir thickness, porosity, permeability, and CG needed for operation. Much research is needed to understand the true site-specific storage resource potential of each formation. Using the Dunham Salt Interval for cavern development may result in as much as 4.79 MMt (up to 2.87 MMt working gas) of H 2 storage potential. An important note for consideration is that the values presented here need significantly more geological characterization and engineering assessments prior to gaining confidence in performance. This will be a focal point for future research and development needs. The basinwide evaluation also indicated that North Dakota has significant H 2 generation potential, with estimates up to a possible 13 MMt annually, suggesting a substantial opportunity for H 2 market development and thus the need for commercial-scale H 2 storage to facilitate growth and resilience. Key Recommendations 1. Conduct detailed site characterization (3D seismic, well logs, core sampling) to reduce geologic uncertainty. 2. Perform techno-economic analyses incorporating market, regulatory, and incentive frameworks. 3. Investigate long-term interactions among H 2 , CGs, well materials, and formations to assess risks. 4. Develop pilot- and field-scale demonstrations to validate models and establish best practices.

03 NATURAL GAS↗