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At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Building High-Energy Silicon-Containing Batteries Using Off-The-Shelf Materials

The technology of silicon anodes appears to be reaching maturity, with high-energy Si cells already in pilot-scale production. However, the performance of these systems can be difficult to replicate in academic settings, making it challenging to translate research findings into solutions that can be implemented by the battery industry. Part of this difficulty arises from the lack of access to engineered Si particles and anodes, as electrode formulations and the materials themselves have become valuable intellectual property for emerging companies. Here, we summarize the efforts by Argonne’s Cell Analysis, Modeling, and Prototyping (CAMP) Facility in developing Si-based prototypes made entirely from commercially available materials. We describe the many challenges we encountered when testing high-loading electrodes (>5 mAh cm −2 ) and discuss strategies to mitigate them. With the right electrode and electrolyte design, we show that our pouch cells containing ≥ 70 wt% SiO x can achieve 600–1,000 cycles at C/3 and meet projected energy targets of 700 Wh L −1 and 350 Wh kg −1 . These results provide a practical reference for research teams seeking to advance silicon-anode development using accessible materials.

25 ENERGY STORAGE↗
DOE OSTI2014

Reference Manual for the System Advisor Model's Wind Power Performance Model

This manual describes the National Renewable Energy Laboratory's System Advisor Model (SAM) wind power performance model. The model calculates the hourly electrical output of a single wind turbine or of a wind farm. The wind power performance model requires information about the wind resource, wind turbine specifications, wind farm layout (if applicable), and costs. In SAM, the performance model can be coupled to one of the financial models to calculate economic metrics for residential, commercial, or utility-scale wind projects. This manual describes the algorithms used by the wind power performance model, which is available in the SAM user interface and as part of the SAM Simulation Core (SSC) library, and is intended to supplement the user documentation that comes with the software.

17 WIND ENERGY↗
NASA NTRS2016

Mass and Reliability System (MaRS)

The Safety and Mission Assurance (S&MA) Directorate is responsible for mitigating risk, providing system safety, and lowering risk for space programs from ground to space. The S&MA is divided into 4 divisions: The Space Exploration Division (NC), the International Space Station Division (NE), the Safety & Test Operations Division (NS), and the Quality and Flight Equipment Division (NT). The interns, myself and Arun Aruljothi, will be working with the Risk & Reliability Analysis Branch under the NC Division's. The mission of this division is to identify, characterize, diminish, and communicate risk by implementing an efficient and effective assurance model. The team utilizes Reliability and Maintainability (R&M) and Probabilistic Risk Assessment (PRA) to ensure decisions concerning risks are informed, vehicles are safe and reliable, and program/project requirements are realistic and realized. This project pertains to the Orion mission, so it is geared toward a long duration Human Space Flight Program(s). For space missions, payload is a critical concept; balancing what hardware can be replaced by components verse by Orbital Replacement Units (ORU) or subassemblies is key. For this effort a database was created that combines mass and reliability data, called Mass and Reliability System or MaRS. The U.S. International Space Station (ISS) components are used as reference parts in the MaRS database. Using ISS components as a platform is beneficial because of the historical context and the environment similarities to a space flight mission. MaRS uses a combination of systems: International Space Station PART for failure data, Vehicle Master Database (VMDB) for ORU & components, Maintenance & Analysis Data Set (MADS) for operation hours and other pertinent data, & Hardware History Retrieval System (HHRS) for unit weights. MaRS is populated using a Visual Basic Application. Once populated, the excel spreadsheet is comprised of information on ISS components including: operation hours, random/nonrandom failures, software/hardware failures, quantity, orbital replaceable units (ORU), date of placement, unit weight, frequency of part, etc. The motivation for creating such a database will be the development of a mass/reliability parametric model to estimate mass required for replacement parts. Once complete, engineers working on future space flight missions will have access a mean time to failures and on parts along with their mass, this will be used to make proper decisions for long duration space flight missions

Barnes, Sarah↗
DOE OSTI2015

Erratum to: Impacts of rising air temperatures and emissions mitigation on electricity demand and supply in the United States: a multi-model comparison

The electric power sector both affects and is affected by climate change. Numerous studies highlight the potential of the power sector to reduce greenhouse gas emissions. Yet fewer studies have explored the physical impacts of climate change on the power sector. The present analysis examines how projected rising temperatures affect the demand for and supply of electricity. We apply a common set of temperature projections to three well-known electric sector models in the United States: the US version of the Global Change Assessment Model (GCAM-USA), the Regional Electricity Deployment System model (ReEDS), and the Integrated Planning Model (IPM®). Incorporating the effects of rising temperatures from a control scenario without emission mitigation into the models raises electricity demand by 1.6 to 6.5 % in 2050 with similar changes in emissions. The increase in system costs in the reference scenario to meet this additional demand is comparable to the change in system costs associated with decreasing power sector emissions by approximately 50 % in 2050. This result underscores the importance of adequately incorporating the effects of long-run temperature change in climate policy analysis.

McFarland, James↗
DOE OSTI2020

Future impacts of ozone driven damages on agricultural systems

Current ozone (O 3 ) concentration levels entail significant damages in crop yields around the world. The reaction of the emitted precursors (mostly methane and nitrogen oxides) with solar radiation contribute to O 3 levels that exceed established thresholds for crop damage. This paper shows current and projected (up to 2080) relative yield losses (RYLs) driven by O 3 exposure for different crops and the associated economic damages applying dynamic crop production and prices that are calculated per region and period. We adjust future crop yields in the Global Change Assessment Model (GCAM) to reflect the RYLs and analyze the effects on agricultural markets. We find that the changes (generally reductions) in O 3 precursor emissions in a reference scenario would reduce the agricultural damages, compared to present, for most of the regions, with a few exceptions including India, where higher future O3 concentrations have large negative impacts on crop yields. The annual economic impact of O3 driven losses from 2010-2080 are, in billion US dollars at 2015 prices ($B), 5.0-6.0, 9.8-18.8, 6.7-10.6 and 10.4-12.5 for corn, soybeans, rice and wheat, respectively, with the large losses for wheat and soybeans driven by their comparatively high responses to O 3 . When O 3 effects are explicitly modelled as exogenous yield shocks in future periods, there is a direct impact in future agricultural markets. Therefore, the aggregated net present value (NPV) of crop production would be reduced around by $90.8B at a global level. However, these changes are not distributed evenly across regions, and the net present market value of the crops would increase by up to $118.2B (India) or decrease by up to $59.2B (China).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Performance Evaluation of Intelligent Solar Control Software Through Hardware-in-the-Loop (CRADA Final Report)

Recent research has highlighted the potential for solar to act as a zero-marginal-cost and zero-emission flexibility resource on the bulk power system when operated with advanced control systems. To increase the performance of these systems, leading technologies, including machine learning (ML) and hierarchical inverter set point allocation, have been developed by Latimer Controls, Inc. to estimate the headroom of large PV plants for grid operation and control; however, these technologies lack comprehensive validation under real-world application scenarios. Latimer Controls, Inc. received two voucher awards for research at a national laboratory from the Department of Energy American Made Solar Prize Round 6. The National Renewable Energy Laboratory (NREL) was selected to collaborate with Latimer staff to conduct a performance evaluation of Latimer PV control software. The NREL team will develop a hardware-in-the-loop (HIL) testbed to perform testing and validation of the Latimer PV control technology in a de-risked yet realistic testbed environment. Latimer and NREL worked together to analyze the test data, draw conclusions from the results, and disseminate the resulting scientific findings. In this CRADA work, we propose to test and validate the real-world application of the Latimer Control solution in an HIL environment. We evaluate the performance of different flexible solar technologies in responding to automatic generation control signals in a closed-loop fashion. In particular, a data-driven potential high limit (PHL) estimation is developed for large solar plants to accurately estimate their headroom so that they have fast and short-time regulation and control capability to participate in grid services and respond to grid signals in real time (e.g., AGC). This PHL estimation algorithm is embedded in a hardware power plant controller (PPC) and tested with an IEEE-39 bus system model developed in RTDS. To account for the varying cloud conditions and diverse inverter dispatches, we developed a 135-MW PV plant with detailed modeling of 27 individual PV modules and inverters using RTDS. The real-world communications used in such big plants, such as ModBus TCP/IP for inverter level and DNP3 for plant level, were developed to emulate the real-world applications in big PV plants. The ML-based PHL estimation method is tested under nine separate weather scenarios against the ‘reference-control’ solution, hereafter referred to as the baseline solution. The baseline method reserves a subset of inverters (reference group) to operate at their PHL at all times and dispatches only the remaining inverters (control group) at curtailed levels to fulfill the flexibility need. Despite being successfully piloted by NREL in California in 2017 and Chile in 2020, there exist two gaps in the state of the art to fully unlock the flexibility of PV plants: a. There is a trade-off between the PHL estimation accuracy and the flexibility range. b. There lacks granularity in the PHL estimation to capture the variation across inverters. The Latimer solution seeks to address these gaps by applying machine learning methods to improve PHL estimation accuracy while accounting for variability at every inverter. Performance metrics were taken from the 2023 Georgia Power CARES utility-scale RFP. The results demonstrate that the ML-based approach outperforms the traditional baseline method in PHL estimation accuracy for 7 of 9 scenarios. The average PHL error across the nine scenarios was 7.40% for the ML-based method, 2.06% less than the 9.46% PHL error average across scenarios that was exhibited by the baseline method. Additionally, the PHL error was below 5% for at least 95% of the testing interval for 3 of 9 tested intervals with the ML approach, whereas it did not achieve this metric for any of the baseline tests. Overall, simulation results indicate the superior performance of an ML-based approach compared to the conventional baseline reference-control approach, showcasing its potential to support grid stability and operational efficiency. This laboratory HIL testing using real PPC, representative power system simulation models in real-time with detailed PV plant and inverter models, and real-world communication protocols gives us confidence that this machine learning based PHL estimation algorithm works well in the hardware PPC and therefore de-risks future field commissioning. The end goal of this project is to advance grid technology to address the grid operation challenges brought by solar plant’s variability and uncertainties in power generation.

14 SOLAR ENERGY↗
NASA NTRS2004

Advanced Life Support Research and Technology Development Metric: Fiscal Year 2003

This document provides the official calculation of the Advanced Life Support (ALS) Research and Technology Development Metric (the Metric) for Fiscal Year 2003. As such, the values herein are primarily based on Systems Integration, Modeling, and Analysis (SIMA) Element approved software tools or reviewed and approved reference documents. The Metric is one of several measures employed by the National Aeronautics and Space Administration (NASA) to assess the Agency s progress as mandated by the United States Congress and the Office of Management and Budget. Because any measure must have a reference point, whether explicitly defined or implied, the Metric is a comparison between a selected ALS Project life support system and an equivalently detailed life support system using technology from the Environmental Control and Life Support System (ECLSS) for the International Space Station (ISS). More specifically, the Metric is the ratio defined by the equivalent system mass (ESM) of a life support system for a specific mission using the ISS ECLSS technologies divided by the ESM for an equivalent life support system using the best ALS technologies. As defined, the Metric should increase in value as the ALS technologies become lighter, less power intensive, and require less volume. For Fiscal Year 2003, the Advanced Life Support Research and Technology Development Metric value is 1.47 for an Orbiting Research Facility and 1.36 for an Independent Exploration Mission.

Hanford, A. J.↗
NASA NTRS2004

Optical Diagnostic System for Solar Sails: Phase 1 Final Report

NASA's In-Space Propulsion program recently selected AEC-ABLE Engineering and L'Garde, Inc. to develop scale-model solar sail hardware and demonstrate its functionality on the ground. Both are square sail designs with lightweight diagonal booms (<100 g/m) and ultra-thin membranes (<10 g/sq m). To support this technology, the authors are developing an integrated diagnostics instrumentation package for monitoring solar sail structures such as these in a near-term flight experiment. We refer to this activity as the "Optical Diagnostic System (ODS) for Solar Sails" project. The approach uses lightweight optics and photogrammetric techniques to measure solar sail membrane and boom shape and dynamics, thermography to map temperature, and non-optical sensors including MEMS accelerometers and load cells. The diagnostics package must measure key structural characteristics including deployment dynamics, sail support tension, boom and sail deflection, boom and sail natural frequencies, sail temperature, and sail integrity. This report summarizes work in the initial 6-month Phase I period (conceptual design phase) and complements the final presentation given in Huntsville, AL on January 14, 2004.

Pappa, Richard S.↗
DOE OSTI2015

IAEA Coordinated Research Project on HTGR Reactor Physics, Thermal-hydraulics and Depletion Uncertainty Analysis

The continued development of High Temperature Gas Cooled Reactors (HTGRs) requires verification of HTGR design and safety features with reliable high fidelity physics models and robust, efficient, and accurate codes. The predictive capability of coupled neutronics/thermal-hydraulics and depletion simulations for reactor design and safety analysis can be assessed with sensitivity analysis (SA) and uncertainty analysis (UA) methods. Uncertainty originates from errors in physical data, manufacturing uncertainties, modelling and computational algorithms. (The interested reader is referred to the large body of published SA and UA literature for a more complete overview of the various types of uncertainties, methodologies and results obtained). SA is helpful for ranking the various sources of uncertainty and error in the results of core analyses. SA and UA are required to address cost, safety, and licensing needs and should be applied to all aspects of reactor multi-physics simulation. SA and UA can guide experimental, modelling, and algorithm research and development. Current SA and UA rely either on derivative-based methods such as stochastic sampling methods or on generalized perturbation theory to obtain sensitivity coefficients. Neither approach addresses all needs. In order to benefit from recent advances in modelling and simulation and the availability of new covariance data (nuclear data uncertainties) extensive sensitivity and uncertainty studies are needed for quantification of the impact of different sources of uncertainties on the design and safety parameters of HTGRs. Only a parallel effort in advanced simulation and in nuclear data improvement will be able to provide designers with more robust and well validated calculation tools to meet design target accuracies. In February 2009, the Technical Working Group on Gas-Cooled Reactors (TWG-GCR) of the International Atomic Energy Agency (IAEA) recommended that the proposed Coordinated Research Program (CRP) on the HTGR Uncertainty Analysis in Modelling (UAM) be implemented. This CRP is a continuation of the previous IAEA and Organization for Economic Co-operation and Development (OECD)/Nuclear Energy Agency (NEA) international activities on Verification and Validation (V&V) of available analytical capabilities for HTGR simulation for design and safety evaluations. Within the framework of these activities different numerical and experimental benchmark problems were performed and insight was gained about specific physics phenomena and the adequacy of analysis methods.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS1994

Numerical analysis and modeling of atmospheric phenomena

For the past 22 years Grant NGR 22-009-727 has been supporting research in the Center for Meteorology and Physical Oceanography (and its predecessors) in a wide variety of diagnostic and modeling studies of atmospheric and ocean phenomena. Professor Jule Charney was the initial Principal Investigator. Professor Peter Stone joined him as co-Principal Investigator in 1975 and became the sole Principal Investigator in 1981. During its lifetime the Grant has supported in whole or in part 11 Master's theses, 14 Ph.D. theses, and 45 papers published in refereed scientific journals. All of these theses and papers (with bibliographic references) are listed below. All but one of the theses were used to fulfill the requirements for MIT (Massachusetts Institute of Technology) degrees and are available from the MIT libraries. The one exception is F. Chen's Ph.D. thesis which was for a Harvard degree and is available from the Harvard libraries. In addition to the work described in the citations listed below, the Grant has supported Research Assistant Amy Solomon during the past two years to carry out a study of how baroclinic adjustment is affected by vertical resolution, vertical temperature structure, and dissipation. Ms. Solomon plans to use this project for her Ph.D. thesis. Support for this project will continue under NASA Grant NAG 5-2490, 'The Factors Controlling Poleward Heat Transport in Climate Models.'

Stone, Peter H.↗
DOE OSTI2022

INGENIOUS - Great Basin Regional Dataset Compilation

This is the regional dataset compilation for the INnovative Geothermal Exploration through Novel Investigations Of Undiscovered Systems (INGENIOUS) project. The primary goal of this project is to accelerate discoveries of new, commercially viable hidden geothermal systems while reducing the exploration and development risks for all geothermal resources. These datasets will be used in INGENIOUS as input features for predicting geothermal favorability throughout the Great Basin study area. Datasets consist of shapefiles, geotiffs, tabular spreadsheets, and metadata that describe: 2-meter temperature probe surveys, quaternary faults and volcanic features, geodetic shear and dilation models, heat flow, magnetotellurics (conductance), magnetics, gravity, paleogeothermal features (such as sinter and tufa deposits), seismicity, spring and well temperatures, spring and well aqueous geochemistry analyses, thermal conductivity, and fault slip and dilation tendency. For additional project information, see the INGENIOUS project site linked in the submission. Terms of use: These datasets are provided "as is", and the contributors assume no responsibility for any errors or omissions. The user assumes the entire risk associated with their use of these data and bears all responsibility in determining whether these data are fit for their intended use. These datasets may be redistributed with attribution (see citation information below). Please refer to the license information on this page for full licensing terms and conditions.

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

Documented Kokkos API: WBS STPR 04 Milestone 13

This report documents the completion of milestone STPRO4-13 "Documented Kokkos API", which is part of the Exascale Computing Project (ECP). The goal of this Milestone was to generate documentation for the Kokkos programming model accessible to the open HPC community, beyond what was available via the tutorials. The total documentation for Kokkos now contains the equivalent of about 250 pages in text book format. About a third of it is contained in a more text book like style like the Kokkos Programming Guide, while most of the rest is an API reference modelled after popular C++ reference webpages. On the order of 175 pages was generated new as part of the work for this milestone.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2010

Performance and Stability Analyses of Rocket Combustion Devices Using Liquid Oxygen/Liquid Methane Propellants

Liquid rocket engines using oxygen and methane propellants are being considered by the National Aeronautics and Space Administration (NASA) for in-space vehicles. This propellant combination has not been previously used in flight-qualified engine systems, so limited test data and analysis results are available at this stage of early development. NASA has funded several hardware-oriented programs with oxygen and methane propellants over the past several years with the Propulsion and Cryogenic Advanced Development (PCAD) project, under the Exploration Technology Development Program. As part of this effort, NASA Marshall Space Flight Center has conducted combustion, performance, and combustion stability analyses of several of the configurations on these programs. This paper summarizes these analyses. Test and analysis results of impinging and coaxial element injectors using liquid oxygen and liquid methane propellants are included. Several cases with gaseous methane are included for reference. Several different thrust chamber configurations have been modeled, including thrust chambers with multi-element like-on-like and swirl coax element injectors tested at NASA MSFC, and a unielement chamber with shear and swirl coax injectors tested at The Pennsylvania State University. Configurations were modeled with two one-dimensional liquid rocket combustion analysis codes, the Rocket Combustor Interaction Design and Analysis (ROCCID), and the Coaxial Injector Combustion Model (CICM). Significant effort was applied to show how these codes can be used to model combustion and performance with oxygen/methane propellants a priori, and what anchoring or calibrating features need to be applied or developed in the future. This paper describes the test hardware configurations, presents the results of all the analyses, and compares the results from the two analytical methods.

Hulka, James R.↗
NASA NTRS2016

Optical Modeling and Polarization Calibration for CMB Measurements with Actpol and Advanced Actpol

The Atacama Cosmology Telescope Polarimeter (ACTPol) is a polarization sensitive upgrade to the Atacama Cosmology Telescope, located at an elevation of 5190 m on Cerro Toco in Chile. ACTPol uses transition edge sensor bolometers coupled to orthomode transducers to measure both the temperature and polarization of the Cosmic Microwave Background (CMB). Calibration of the detector angles is a critical step in producing polarization maps of the CMB. Polarization angle offsets in the detector calibration can cause leakage in polarization from E to B modes and induce a spurious signal in the EB and TB cross correlations, which eliminates our ability to measure potential cosmological sources of EB and TB signals, such as cosmic birefringence. We calibrate the ACTPol detector angles by ray tracing the designed detector angle through the entire optical chain to determine the projection of each detector angle on the sky. The distribution of calibrated detector polarization angles are consistent with a global offset angle from zero when compared to the EB-nulling offset angle, the angle required to null the EB cross-correlation power spectrum. We present the optical modeling process. The detector angles can be cross checked through observations of known polarized sources, whether this be a galactic source or a laboratory reference standard. To cross check the ACTPol detector angles, we use a thin film polarization grid placed in front of the receiver of the telescope, between the receiver and the secondary reflector. Making use of a rapidly rotating half-wave plate (HWP) mount we spin the polarizing grid at a constant speed, polarizing and rotating the incoming atmospheric signal. The resulting sinusoidal signal is used to determine the detector angles. The optical modeling calibration was shown to be consistent with a global offset angle of zero when compared to EB nulling in the first ACTPol results and will continue to be a part of our calibration implementation. The first array of detectors for Advanced ACTPol, the next generation upgrade to ACTPol, will be deployed in 2016.We plan to continue using both techniques and compare them to astrophysical source measurements for the Advanced ACTPol polarization calibration.

Koopman, Brian↗
NASA NTRSDate not supplied

Sensorimotor Application of Proposed Methods to Combine the Effects of Multiple Countermeasures for PRisM

Risk associated with human systems is challenging to quantify but is critical for the mission planning and decision making required to enable future Lunar and Martian missions. To address this gap, the Crew Health and Performance-Probabilistic Risk Assessment (CHP-PRA) project is developing an integrated computational model for CHP mission risk. Much like how MEDPRAT is designed to allow medical resource trades informed by medical risk, CHP-PRA will enable analogous trades in human system risks across multiple CHP functions and capabilities. Human performance is one component of the risk intended to be captured by CHP-PRA through the Performance Risk Model (PRisM). The sensorimotor risk area provides a good frame of reference for investigating the structure of a performance model because most tasks that astronauts are expected to perform require input from the sensory system and/or movement/motor control. Additionally, sensorimotor countermeasures are an area of particular concern for NASA’s Human Research Program because of the increased sensorimotor risk associated with surface operations in Lunar and Martian missions. Thus, a tool that can quickly compare risk reductions of potential countermeasures would be beneficial in guiding research and development of effective countermeasures. In this proof of concept, we present a systematic way to combine multiple performance data sets for humans subjected to different countermeasures such that we can predict the countermeasure(s) that optimize astronaut performance on relevant tasks. PRisM assumes that both the tests that are used to measure countermeasure effectiveness (input data) and the tasks we use to represent astronaut performance, can be broken down and represented as a function/vector of the human systems required to perform that test/task. Through mathematical combination, test data are used to predict performance on astronaut tasks that use similar systems. We propose that when combining countermeasures evaluated using the same test, that only one value should be used to represent their combined effectiveness. We start our analysis with the assumption that two countermeasures together will perform better than each countermeasure individually. Our initial implementation of this framework compares various space motion sickness countermeasures and the most up to date analysis will be demonstrated at the IWS.

Caroline R Austin↗
DOE OSTI2020

A reduced-order shifted boundary method for parametrized incompressible Navier–Stokes equations

Here, we investigate a projection-based reduced order model of the steady incompressible Navier–Stokes equations for moderate Reynolds numbers. In particular, we construct an “embedded” reduced basis space, by applying proper orthogonal decomposition to the Shifted Boundary Method, a high-fidelity embedded method recently developed. We focus on the geometrical parametrization through level-set geometries, using a fixed Cartesian background geometry and the associated mesh. This approach avoids both remeshing and the development of a reference domain formulation, as typically done in fitted mesh finite element formulations. Two-dimensional computational examples for one and three parameter dimensions are presented to validate the convergence and the efficacy of the proposed approach.

"embedded" basis↗
DOE OSTI2023

Symmetry-projected cluster mean-field theory applied to spin systems

We introduce S z spin-projection based on cluster mean-field theory and apply it to the ground state of strongly correlated spin systems. In cluster mean-fields, the ground state wavefunction is written as a factorized tensor product of optimized cluster states. In previous work, we have focused on unrestricted cluster mean-field, where each cluster is S z symmetry adapted. We here remove this restriction by introducing a generalized cluster mean-field (GcMF) theory, where each cluster is allowed to access all S z sectors, breaking S z symmetry. In addition, a projection scheme is used to restore global S z , which gives rise to the S z spin-projected generalized cluster mean-field (S z GcMF). Both of these extensions contribute to accounting for inter-cluster correlations. We benchmark these methods on the 1D, quasi-2D, and 2D J 1 – J 2 and XXZ Heisenberg models. Furthermore, our results indicate that the new methods (GcMF and S z GcMF) provide a qualitative and semi-quantitative description of the Heisenberg lattices in the regimes considered, suggesting them as useful references for further inter-cluster correlations, which are discussed in this work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Assessing the Costs of Hydropower at Non-Powered Dams Using a Reference Site Model

Hydropower capacity in the United States currently stands at approximately 103 GW, and there are remaining water resources that could help meet the rapidly increasing demand for electricity and ancillary grid services. Existing dams that do not generate power, known as non-powered dams, are a near-term solution to enhance the contribution of hydropower to the US power grid. However, there are thousands of such sites, and the lack of detailed information about their specific characteristics and associated costs presents significant challenges for stakeholders. This study addresses these challenges by developing a reference site model to evaluate the potential costs of hydropower at non-powered dams using currently available technologies. An application of the model reveals a wide range of estimates for capacity, capital costs, levelized cost of electricity, and cost components. While many sites are competitive with current technologies, the majority would need cost-reducing innovations to be viable. Despite the limited available information, the model offers valuable insights into the relative competitiveness of hydropower projects at non-powered dams. The simulation results highlight the need for continued technological advancements in hydropower and provide a basis for evaluating the benefits of new innovations.

cost drivers↗