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At least 325 records · Page 18

Updating the BNB Flux Prediction at SBND

Precise, accurate neutrino flux predictions for neutrino beam experiments are crucial for physics results. Flux uncertainties contribute significantly to the total systematic uncertainties seen in modern accelerator neutrino measurements such as cross sections, oscillations, and BSM studies.. For over a decade, experiments utilizing Fermilab’s Booster Neutrino Beam (BNB) have relied on the 2009 MiniBooNE flux prediction. However, the high-statistics era of the Short-Baseline Neutrino (SBN) program, with both SBND and ICARUS now operating, demands a modernized flux model and framework. While SBND is using the MiniBooNE flux model for its Generation 1 analyses, including many upcoming cross section measurements, future work will be based on a new flux model. In this talk, the ongoing work towards this new model will be outlined, including a new simulation framework (G4BNB), a new evaluation of model parameters from hadron scattering data, and a new framework for evaluating systematic uncertainties (BNBFP). Additionally, expansions to the flux model to include BSM contributions from neutral mesons will be discussed, as well as the PRISM capabilities of SBND to observe a wide range of off axis angles of the neutrino beam.

Paton, Josephine [Fermilab]↗

Some Aspects of the Liquid Water Thermodynamic Behavior: From The Stable to the Deep Supercooled Regime

Liquid water is considered to be a peculiar example of glass forming materials because of the possibility of giving rise to amorphous phases with different densities and of the thermodynamic anomalies that characterize its supercooled liquid phase. In the present work, literature data on the density of bulk liquid water are analyzed in a wide temperature-pressure range, also including the glass phases. A careful data analysis, which was performed on different density isobars, made in terms of thermodynamic response functions, like the thermal expansion αP and the specific heat differences C P -C V , proves, exclusively from the experimental data, the thermodynamic consistence of the liquid-liquid transition hypothesis. The study confirms that supercooled bulk water is a mixture of two liquid “phases”, namely the high density (HDL) and the low density (LDL) liquids that characterize different regions of the water phase diagram. Furthermore, the C P -C V isobars behaviors clearly support the existence of both a liquid–liquid transition and of a liquid–liquid critical point.

59 BASIC BIOLOGICAL SCIENCES↗

Direct measurement of the thermal expansion coefficient of epitaxial WSe 2 by four-dimensional scanning transmission electron microscopy

Current reports of thermal expansion coefficients (TEC) of two-dimensional (2D) materials show large discrepancies that span orders of magnitude. Determining the TEC of any 2D material remains difficult due to approaches involving indirect measurement of samples that are atomically thin and optically transparent. We demonstrate a methodology to address this discrepancy and directly measure TEC of nominally monolayer epitaxial WSe 2 using four-dimensional scanning transmission electron microscopy (4D-STEM). Experimentally, WSe 2 from metal-organic chemical vapor deposition (MOCVD) was heated through a temperature range of 18- 564 °C using a barrel-style heating sample holder to observe temperature-induced structural changes without additional alterations or destruction of the sample. By combining 4D-STEM measurements with quantitative structural analysis, the thermal expansion coefficient of nominally monolayer polycrystalline epitaxial 2D WSe 2 was determined to be (3.5 ± 0.9) × 10 -6 K -1 and (5.7 ± 2) × 10 -5 K -1 for the in- and out-of-plane TEC, respectively, and (3.6 ± 0.2) × 10 -5 K -1 for the unit cell volume TEC, in good agreement with historically determined values for bulk crystals.

2D materials↗

The Prospects for Pumped Storage Hydropower in Alaska

Key Takeaways: The resource mapping analysis confirmed that numerous locations in Alaska are suitable for the development of pumped storage hydropower (PSH) projects, both larger grid scale projects and smaller projects that could be suitable for remote communities; The resource assessment for larger, grid-scale projects showed the potential for more than 1,800 closed-loop systems in Alaska, with a total energy storage capacity of about 4 terawatt hours (TWh); Because of their small reservoir sizes and dam heights, many locations were identified as potentially suitable for small-scale PSH systems. Nearly 50% of the identified potentially suitable small-scale PSH sites are in Southeast Alaska; PSH candidate sites were part of the optimal capacity expansion solution in all scenarios analyzed for the Railbelt system. Depending on the scenario, the new PSH capacity that the model selected for the analysis period until 2046 ranged from 300 MW to 600 MW. The locations and timing of new PSH investments vary in different scenarios; Lithium-ion batteries were also selected a source of new generating capacity in all analyzed scenarios for the Railbelt system, indicating that the system will need a mix of short- and long-duration energy storage to support variable renewable energy sources and provide system reliability in the future; For rural communities, analysis results showed that PSH suitability is very site-specific; in addition to diesel fuel costs and PSH capital costs, suitability depends heavily on available renewable resources and existing infrastructure (e.g., reservoirs, transmission access and construction road access); The analysis for rural communities also showed that PSH projects with 10-hour energy storage are likely to be more economical for remote community applications in Alaska than those with larger reservoirs that could provide 10 days of energy storage; Lithium-ion batteries seem to be an economically more viable energy storage option for small, remote communities in Alaska.

13 HYDRO ENERGY↗

Distribution Grid Impacts of Community Solar [Slides]

Community solar (CS) projects often face uncertain interconnection costs and fees associated with distribution grid infrastructure upgrades required to connect the project. These costs can determine the economic viability of a CS project, but they are difficult to assess. Cost uncertainty can discourage new projects and prevent communities from accessing the benefits of community solar projects. At the same time, CS deployment strategies hold potential to defer or avoid some distribution costs due to new loads. To mitigate CS interconnection costs, it is important to find least-cost combinations of distribution system infrastructure solutions (transformer upgrades, reconductoring, voltage regulators, storage), and to understand how location of CS projects within a feeder impact distribution grid upgrade costs. This study aims to quantify CS impacts on the distribution grid and provide policy and regulatory insights and CS deployment strategies to address them. It is the first analysis that has systematically studied the technical impacts of community solar projects on a wide range of distribution feeders using state-of-the-art optimization and power flow tools. The analysis employs Berkeley Lab’s novel Least-cost Optimal Distribution Grid Expansion (LODGE) model, a deterministic version of the REPAIR model, that optimally upgrades hundreds or even thousands of distribution circuits or feeders. This is the first application of the LODGE model. LODGE finds the least-cost portfolio of traditional distribution system upgrades to integrate CS in combination with alternative solutions, such as utility-owned storage and downsizing CS capacity. Working with a set of least-cost solutions per feeder allows us to benchmark, compare and find techno-economic trends in CS interconnection.

14 SOLAR ENERGY↗

Development and Experimental Optimization of High-Temperature Modeling Tools and Methods for Concentrated Solar Power Particle - Systems

A novel, open-source radiative modeling toolset was developed to extend the functionality of particle-based modeling software (e.g. discrete element method (DEM)) to environmental conditions relevant to concentrated solar power applications. This toolset was optimized for deployment on desktop workstations instead of high-performance computing systems, to render such tools more accessible to the research community. Both particle-based modeling and radiative exchange modeling are computationally expensive and often require specialized programming expertise, making these methods cumbersome to use. Recent developments in DEM software by DCS Computing have greatly reduced these challenges, providing a graphical-user-interface based platform and modeling optimization for desktop workstations, HPCs, and cloud computing. The University of Dayton leveraged the experience of DCS Computing in developing a user-friendly, open-source radiative heat transfer expansion for DEM modeling. The University of Dayton DEM+ radiative modeling toolset was developed using a combination of fundamental experimental measurements, modeling, and simplified flow experiments over a range of temperatures and flow conditions. The toolset provides researchers with access to multiple radiative models including an accelerated Monte-Carlo Ray Tracing (application agnostic, highly computationally expensive), an expanded database of distance-based approximations (application limited, computationally light), and a weighted blending of the two methods capable of achieving over 90% reduction in computation time with equivalent accuracy compared to Monte-Carlo Ray Tracing. Through a graphical user interface, users can customize the radiative models to match their desired accuracy and available computational resources, improving access to particle based modeling for the research community. Ceramic sintered bauxite proppants were used in modeling and experimentally as a baseline. Both the radiative heat transfer and flow properties for particulate systems were investigated at elevated temperatures up to 800 °C. The major accomplishments for this work include a verified, open-source radiative modeling toolset to be distributed amongst the research community and the fabrication of three small-scale test facilities to investigate particle behavior and tune DEM flow properties for operation up to 800 °C. The findings have been shared with the research community via conference modeling workshops, deployment of the tools in DCS Computing Aspherix®, and open-source access to the developed radiative modeling tool. The development of next-generation CSP facilities and thermal energy storage systems based on ceramic particles requires providing access to computationally efficient and accurate modeling tools. Particles will experience a wide range of environments (20-800 °C) and handling conditions (dilute curtains or dense packing), requiring specially designed and optimized equipment. Optimizing solid particle physics models and establishing best-practices for particle modeling in CSP environments will assist researchers with designing optimized equipment, accelerating the deployment of more economically-competitive CSP facilities.

14 SOLAR ENERGY↗

Tax Credits for Clean Electricity: The Distributional Impacts of Supply-Push Policies in the Power Sector

We evaluate distributional and efficiency consequences of the bulk power clean electricity tax credits authorized by the 2022 Inflation Reduction Act. To do so, we link detailed electricity capacity expansion, computable general equilibrium, data-rich microsimulation, and air pollution models to estimate the policy incidence in terms of economic welfare and health impacts across a wide range of demographic groups. We evaluate the tradeoff between policy efficiency and income progressivity by comparing the tax credits to cap-and-trade policies that vary revenue recycling approaches. Under the scenarios analyzed the bulk power tax credits lead to increased clean electricity technology deployment resulting in a reallocation of capital from elsewhere in the economy, higher prices for capital and other goods, lower power prices, and lower emissions. The tax credits yield progressive outcomes for both economic welfare and health impacts. The health benefits exceed total policy costs and provide greater benefits for low-income and historically-marginalized households given the coincidence of household and emission source locations.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Implementing Chiral Three-Body Forces in Terms of Medium-Dependent Two-Body Forces

Three-nucleon (3N) forces are an indispensable ingredient for accurate few-body and many- body nuclear structure and reaction theory calculations. While the direct implementation of chiral 3N forces can be technically very challenging, a simpler approach is given by employing instead a medium-dependent NN interaction V med that reflects the physics of three-body forces at the two-body normal-ordered approximation. We review the derivation and construction of Vmed from the chiral 3N interaction at next-to-next-to-leading order (N2LO), consisting of a long-range 2π-exchange term, a mid-range 1π-exchange component and a short-range contact-term. Several applications of V med to the equation of state of cold nuclear and neutron matter, the nucleon single-particle potential in nuclear matter, and the nuclear quasiparticle interaction are discussed. We also explore differences in using local vs. nonlocal regulating functions on 3N forces and make direct comparisons to exact results at low order in perturbation theory expansions for the equation of state and single-particle potential. We end with a discussion and numerical calculation of the in-medium NN potential V med from the next-to-next-to-next-to-leading order (N3LO) chiral 3N force, which consists of a series of long-range and short-range terms.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Mechanical and Thermal Properties for Uranium and U–6Nb Alloy from First-Principles Theory

Elasticity, lattice dynamics, and thermal expansion for uranium and U–6Nb alloy (elastic moduli) are calculated from density functional theory that is extended to include orbital polarization (DFT+OP). Introducing 12.5 at.% of niobium, substitutionally, in uranium softens all the cii elastic moduli, resulting in a significantly softer shear modulus (G). Combined with a nearly invariant bulk modulus (B), the quotient B/G increases dramatically for U–6Nb, suggesting a more ductile material. Lattice dynamics from a harmonic model coupled with a DFT+OP electronic structure is applied for α uranium, and the obtained phonon density of states compares well with inelastic neutron-scattering measurements. The Debye temperature associated with the lattice dynamics falls within the range of experimentally observed Debye temperatures and it also validates our quasi-harmonic (QH) phonon model. The QH Debye–Grüneisen phonon method is combined with a DFT+OP electronic structure and used to explore the anisotropic thermal expansion in α uranium. The anomalous negative thermal expansion (contraction) of the b lattice parameter of the α-phase orthorhombic cell is relatively well reproduced from a free-energy model consisting of QH-phonon and DFT+OP electronic structure contributions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Formation of short-range magnetic order and avoided ferromagnetic quantum criticality in pressurized LaCrGe 3

LaCrGe 3 has attracted attention as a paradigm example of the avoidance of ferromagnetic (FM) quantum criticality in an itinerant magnet. In this work, we combined thermodynamic (specific heat and thermal expansion), transport, x-ray, and neutron scattering as well as μSR measurements to obtain insights on the temperature-pressure phase diagram of LaCrGe 3 . Consistent with previous studies of the phase diagram by transport measurements, our thermodynamic data shows clearly that the FM transition at T FM changes its character from second order to first order when it is suppressed to low temperatures by pressure. In addition, previous studies demonstrated that for high pressures a new phase occurs below T 2 , which was proposed to be a long-wavelength antiferromagnetic state (AFM q ). In this paper, we provide evidence from our thermodynamic data that this phase transition is preceded by yet another phase transition at T 1 >T 2 . Our μSR data indicate that full magnetic volume fraction is only established below T 2 , but that this magnetism is characterized by a short correlation length. Within the experimental resolution, our neutron-scattering data is not able to identify any magnetic Bragg peaks. Overall, the microscopic magnetic data is therefore consistent with the formation of FM clusters in the proximity of the avoided FM quantum critical point in LaCrGe 3 . This conclusion is at odds with the previous proposal of AFM q order and raises questions on the role of disorder in this stochiometric compound.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Future bioenergy expansion could alter carbon sequestration potential and exacerbate water stress in the United States

The maximum future projected bioenergy expansion potential, in scenarios limiting warming to 2°C or below, is equivalent to half of present-day croplands. We quantify the impacts of large-scale bioenergy expansion against re/afforestation, which remain elusive, using an integrated human-natural system modeling framework with explicit representation of perennial bioenergy crops. The end-of-century net carbon sequestration due to bioenergy deployment coupled with carbon capture and storage largely depends on fossil fuel displacement types, ranging from 11.4 to 31.2 PgC over the conterminous United States. These net carbon sequestration benefits are inclusive of a 10 PgC carbon release due to land use conversions and a 2.4 PgC loss of additional carbon sink capacity associated with bioenergy-driven deforestation. Moreover, nearly one-fourth of U.S. land areas will suffer severe water stress by 2100 due to either reduced availability or deteriorated quality. These broader impacts of bioenergy expansion should be weighed against the costs and benefits of re/afforestation-based strategies.

09 BIOMASS FUELS↗

Interpretation of wide-angle x-ray diffraction patterns from mesophase pitch-based carbon fibers – a simulation and experimental study

Carbon fiber is a critical material in a wide range of industries, where it is highly valued for its high specific strength/stiffness, excellent wear resistance, efficient electrical and thermal transport properties, chemical resistance, and low coefficient of thermal expansion. The properties of a specific carbon fiber are closely tied to its structural characteristics at all length scales. Here, in this work, we applied wide-angle x-ray diffraction to a set of heat-treated mesophase pitch-based carbon fibers, with the goal of elucidating the crystalline structures as a function of fiber orientation. To assist with analysis and interpretation of the experimental data, we employed diffraction pattern simulations using the scalar and vector forms of the Debye scattering equation to determine the influence of basal plane orientation, crystalline ordering (turbostratic-graphitic), and basal plane asymmetry on the diffraction patterns. The results presented here suggest that growth of the transverse crystallites in mesophase pitch-based carbon fiber is fixed until graphitization temperatures are reached. The work completed here provides a framework for the analysis of carbon fiber and other oriented carbon-based materials via diffraction.

36 MATERIALS SCIENCE↗

Estimating the impact of tariff-driven behind-the-meter storage operation on distribution grid investments

Increasing growth of distributed solar photovoltaics (PV) and electric vehicles (EV) can strain local distribution networks and require costly upgrades. Distributed battery storage, often deployed alongside PV, can be used to mitigate those costs, depending on how batteries are operated. This study evaluates the potential deferral value of distributed battery storage across a range of tariff structures, focusing on the rate structures most commonly available to residential customers today and related variants. Deferrals are evaluated with a least-cost distribution grid expansion optimization model to identify requirements on line reconductoring, transformer upgrades, and voltage regulator installations under each tariff. Results show that TOU rates and net billing tariffs can yield meaningful deferral value, depending on specific tariff structure features. Under the best performing tariff structure tested, storage produced a median annualized deferral value of $7.18 per kW of storage capacity ( kW S ) across all feeders in the sample, though deferral values were considerably larger for feeders with peak loads that coincide with utility system peak, i.e., timing of TOU peak period. In contrast, under an unrestricted TOU design with no restrictions on grid charging or discharging, the median deferral value was $0/ kW S illustrating the critical importance of tariff structure details.

Rodriguez-Garcia, Luis↗

An ab initio molecular dynamics investigation of the thermophysical properties of molten NaCl-MgCl 2

Molten salts have many applications in the nuclear and solar energy industries for thermal storage and heat transfer applications. However, there is a knowledge gap in molten salt thermophysical properties which hinders the technical readiness level of molten salt applications, especially in the nuclear industry. A common method of investigating new materials is through ab initio Molecular Dynamics (AIMD) simulations which is an effective tool to investigate structural and thermophysical properties at realistic temperatures. NaCl-MgCl 2 is an inexpensive salt that is a good candidate for use as a heat transfer medium in solar power applications or in the secondary loop of a nuclear reactor. In this article, the thermophysical properties of NaCl-MgCl 2 are computed via AIMD calculations to supplement the limited experimental studies in the literature. Here a wide range of compositions and temperatures for the pseudo-binary NaCl-MgCl 2 were used to calculate the density, heat capacity, compressibility, enthalpy of mixing, and volumetric thermal expansion coefficient. AIMD is shown to accurately model the densities of molten NaCl-MgCl 2 as there is good agreement with the available literature. This work observed a transition to a monotonic increase of the density with respect to MgCl 2 composition occurring above 1100 K. The heat capacity values increase uniformly with respect to concentration of MgCl 2 at a rate of 2.85 J/mol-K per 10 mol% of MgCl 2 . Select thermophysical properties are fit to a Redlich-Kister expansion for utilization in multiphysics simulations.

36 MATERIALS SCIENCE↗

High precision tests of QCD without scale or scheme ambiguities: The 40th anniversary of the Brodsky–Lepage–Mackenzie method

A key issue in making precise predictions in QCD is the uncertainty in setting the renormalization scale μ r and thus determining the correct values of the QCD running coupling α s (μ r ) at each order in the perturbative expansion of a QCD observable. It has often been conventional to simply set the renormalization scale to the typical scale of the process Q and vary it in the range μ r $\in$ [Q/2, 2Q] in order to estimate the theoretical error. This is the practice of Conventional Scale Setting (CSS). The resulting CSS prediction will however depend on the theorist’s choice of renormalization scheme and the resulting pQCD series will diverge factorially. It will also disagree with renormalization scale setting used in QED and electroweak theory thus precluding grand unification. A solution to the renormalization scale-setting problem is offered by the Principle of Maximum Conformality (PMC), which provides a systematic way to eliminate the renormalization scale-and-scheme dependence in perturbative calculations. The PMC method has rigorous theoretical foundations, it satisfies Renormalization Group Invariance (RGI) and preserves all self-consistency conditions derived from the renormalization group. The PMC cancels the renormalon growth, reduces to the Gell-Mann–Low scheme in the N c → 0 Abelian limit and leads to scale- and scheme-invariant results. The PMC has now been successfully applied to many high-energy processes. In this article we summarize recent developments and results in solving the renormalization scale and scheme ambiguities in perturbative QCD. In particular, we present a recently developed method the PMC ∞ and its applications, comparing the results with CSS. The method preserves the property of renormalizable SU(N)/U(1) gauge theories defined as Intrinsic Conformality (iCF). This property underlies the scale invariance of physical observables and leads to a remarkably efficient method to solve the conventional renormalization scale ambiguity at every order in pQCD. This new method reflects the underlying conformal properties displayed by pQCD at NNLO, eliminates the scheme dependence of pQCD predictions and is consistent with the general properties of the PMC. A new method to identify conformal and β-terms, which can be applied either to numerical or to theoretical calculations is also shown. We present results for the thrust and C-parameter distributions in e + e - annihilation showing errors and comparison with the CSS. We also show results for a recent innovative comparison between the CSS and the PMC ∞ applied to the thrust distribution investigating both the QCD conformal window and the QED N c → 0 limit. In order to determine the thrust distribution along the entire renormalization group flow from the highest energies to zero energy, we consider the number of flavors near the upper boundary of the conformal window. In this flavor-number regime the theory develops a perturbative infrared interacting fixed point. These results show that PMC ∞ leads to higher precision and introduces new interesting features in the PMC. In fact, this method preserves with continuity the position of the peak, showing perfect agreement with the experimental data already at NNLO. We also show a detailed comparison of the PMC ∞ with the other PMC approaches: the multi-scale-setting approach (PMCm) and the single-scale-setting approach (PMCs) by comparing their predictions for three important fully integrated quantities R e+e- , R$_Τ$ and Γ (H→$b\bar{b}$) up to the four-loop accuracy.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Reflections on the Shifting Experiences of Scientific Infrastructure

Infrastructure of all types is fundamental to modern work and life. Computing for scientific work, especially, extends from distributed local research sites, often at the edges of other major systems, outward into globally connected high-performance facilities and infrastructures. This commentary reviews longstanding research on the social characteristics of infrastructure. We reflect on social concerns that affect the ongoing development, use, and maintenance of a wide range of scientific computing and data resources. Reflecting on the social nature of infrastructure is timely for Computing in Science & Engineering readers, given continued emphasis on developing even more expansive platforms for data and artificial intelligence work in science (e.g., the United States’ Genesis Mission). We assert that, regardless of technological advances, the complex nature of scientific research and data will require continued understanding of longstanding and nascent social practices across varied communities. This is fundamentally necessary to build and sustain usable infrastructure or platforms that can productively advance scientific research.

Paine, Drew [Lawrence Berkeley National Laboratory↗

HydraGNN v4.0

The new version of HydraGNN v4.0 provides additional core capabilities, such as: Inclusion of multi-body atomistic cluster expansion MACE, polarizable atom interaction neural network PAINN, and equivariant principal neighborhood aggregation (PNAEq) among the message passing layers supported -Inclusion of graph transformers to directly model long-range interactions between nodes that are distant in the graph topology Integration of graph transformers with message passing layers by combining the graph embedding generated by the two mechanisms, which allows for an improved expressivity of the HydraGNN architecture Improved re-implementation of multi-task learning (MTL) to allow its use for stabilized training across imbalanced, multi-source, multi-fidelity data Introduction of multi-task parallelism, a newly proposed type of model parallelism specifically for MTL architectures, which allows to dispatch different output decoding heads to different GPU devices Integration of multi-task parallelism with pre-existing distributed data parallelism to enable a 2D parallelization for distributed training Improved portability of the distributed training across Intel GPUs, which has been testes on ALCF exascale supercomputer Aurora Inclusion of 2-level fine-grained energy profilers portable across NVIDIA, AMD, and Intel GPUs to monitor the power and energy consumption associated with different functions executed by the HydraGNN code during data pre-load and training Restructuring of previous examples and inclusion of new sets of examples to illustrate the download, preprocess, and training of HydraGNN models on new large-scale open-source datasets for atomistic materials modeling (e.g., Alexandria, Transition1x, OMat24, OMol25)

Lupo Pasini, Massimiliano [Oak Ridge National Labo↗

Grid Planning Impacts of Hydropower Growth and Decline

Hydropower and pumped storage hydropower (PSH) have a complex and uncertain future in the U.S. electricity system. On one hand, existing assets have the potential for an expanded role in integrating variable renewable energy while new deployment, particularly of PSH, can help meet growing needs for grid flexibility and improved reliability. On the other hand, challenging environmental and cost considerations could limit the extent of new investments in hydropower and PSH capacity and flexibility. This technical presentation demonstrates the use of a high-fidelity capacity expansion model of the U.S. electric grid (the National Renewable Energy Laboratory's Regional Energy Deployment System) to understand the impacts of alternative futures for the hydropower and PSH fleet, including scenarios of both growth and decline. Growth scenarios include new PSH deployment or improved hydropower flexibility, while scenarios of decline reduce the capacity or energy production potential of hydropower and PSH. Economic, environmental, and performance outcomes of the grid are compared across these scenarios to reveal the potential contributions of hydropower and PSH in the U.S. electric sector over the next several decades, focusing on changes to the grid technology mix, electric sector costs, electricity prices, and air emissions. This broad scenario approach demonstrates how flexible hydropower and PSH can help reduce air emissions and cost by complementing variable renewables, but the opposite can occur with reduced hydropower availability, particularly in the next decade. It is important to consider a wide range of scenarios and metrics to gain a national and regional understanding of hydropower's future in the United States.

capacity expansion↗