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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,351 records · Page 75

Amorphous ZrCl 4 -Based Superionic Conductor as a Cost-Effective Solid Electrolyte for Batteries

Developing highly conductive and cost-effective solid electrolytes is essential for the commercialization of all-solid-state batteries (ASSBs). Zr-based halide electrolytes hold great promise due to their low estimated cost and high oxidation stability. However, the ionic conductivities of most of them are not high enough to enable moderate- and high-rate cycling of ASSBs. Here, fast ion transport is achieved in a group of cost-effective ZrCl 4 -based electrolytes via a design strategy to create highly disordered amorphous structures. Amorphous Li 0.8 ZrCl 4 (SO 4 ) 0.4 , with a low estimated cost of $21 kg –1 , achieves an ionic conductivity of 1.86 mS cm –1 at 25 °C. It also shows a high oxidation limit of 4.5 V vs Li/Li + and good compatibility with high-voltage cathodes, as demonstrated by the stable cycling of ASSBs (73.7% capacity retention after 1000 cycles at 1 C). Synchrotron X-ray diffraction, pair distribution function analysis, and electrochemical impedance spectroscopy reveal that the outstanding conductivity of these amorphous electrolytes is closely related to their short-range and medium-range ordering, revealing new insights for designing high-performance, cost-effective solid electrolytes.

Zhang, Guangxing [Georgia Institute of Technology,↗

Integrated hydrological, power system and economic modelling of climate impacts on electricity demand and cost

Impacts of climate-related water stress and temperature changes can cascade through energy systems, although models have yet to capture this compounding of effects. Here, we employ a coupled water–power–economy model to capture these important interactions in a study of the exceedance of water temperature thresholds for power generation in the western United States. We find that not all reductions in reserve electricity-generation capacity result in impacts, and that when they occur, intermittent interruptions in electricity supply at critical times of the day, week and year account for much of the economic impacts. Finally, we find that impacts may be in different locations from the original water stress. Herein, we estimate that the consumption loss can be up to 0.3% annually and the drivers identified in coupled modelling can increase the average cost of electricity by up to 3%. Integrated models will be needed to capture the cascading effects of climate change through climatic, water, energy and economic systems. Webster et al. now develop a coupled hydrologic–power-production–economic model to estimate water-stress impacts on electricity cost.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Breakeven Prices for Photovoltaics on Supermarkets in the United States

The photovoltaic (PV) breakeven price is the PV system price at which the cost of PV-generated electricity equals the cost of electricity purchased from the grid. This point is also called 'grid parity' and can be expressed as dollars per watt ($\$$W) of installed PV system capacity. Achieving the PV breakeven price depends on many factors, including the solar resource, local electricity prices, customer load profile, PV incentives, and financing. In the United States, where these factors vary substantially across regions, breakeven prices vary substantially across regions as well. In this study, we estimate current and future breakeven prices for PV systems installed on supermarkets in the United States. We also evaluate key drivers of current and future commercial PV breakeven prices by region. The results suggest that breakeven prices for PV systems installed on supermarkets vary significantly across the United States. Non-technical factors -- including electricity rates, rate structures, incentives, and the availability of system financing -- drive break-even prices more than technical factors like solar resource or system orientation. In 2020 (where we assume higher electricity prices and lower PV incentives), under base-case assumptions, we estimate that about 17% of supermarkets will be in utility territories where breakeven conditions exist at a PV system price of $\$$3/W; this increases to 79% at $\$$1.25/W (the DOE SunShot Initiative's commercial PV price target for 2020). These percentages increase to 26% and 91%, respectively, when rate structures favorable to PV are used.

14 SOLAR ENERGY↗

Manufacturing Thermal Energy Use in 2014

The first data set estimates thermal energy use (i.e., fuels combusted for process heating, boilers, and combined heat and power/cogeneration) by end use, temperature, county, and facility employment size class for all U.S. manufacturing industries in 2014. The estimation methodology builds off of prior estimates of industrial energy use (https://dx.doi.org/10.7799/1481899, https://dx.doi.org/10.7799/1461488). The second data set estimates hourly heat load (as a fraction of annual energy used for heat) using hourly observations of industrial boiler and combined heat and power/cogeneration heat load from EPA's Air Markets Program Data (https://ampd.epa.gov/ampd/), weekly operating hours in 2014 from Census Quarterly Survey of Plant Capacity Utilization (https://www.census.gov/programs-surveys/qpc/data.html), and annual production hours reported by assessments conducted by Industrial Assessment Centers (https://iac.university/).

14 SOLAR ENERGY↗

Manufacturing Thermal Energy Use in 2014

The first data set estimates thermal energy use (i.e., fuels combusted for process heating, boilers, and combined heat and power/cogeneration) by end use, temperature, county, and facility employment size class for all U.S. manufacturing industries in 2014. The estimation methodology builds off of prior estimates of industrial energy use (https://dx.doi.org/10.7799/1481899, https://dx.doi.org/10.7799/1461488). The second data set estimates hourly heat load (as a fraction of annual energy used for heat) using hourly observations of industrial boiler and combined heat and power/cogeneration heat load from EPA's Air Markets Program Data (https://ampd.epa.gov/ampd/), weekly operating hours in 2014 from Census Quarterly Survey of Plant Capacity Utilization (https://www.census.gov/programs-surveys/qpc/data.html), and annual production hours reported by assessments conducted by Industrial Assessment Centers (https://iac.university/).

14 SOLAR ENERGY↗

SAMICS Validation. SAMICS Support Study, Phase 3

SAMICS provides a consistent basis for estimating array costs and compares production technology costs. A review and a validation of the SAMICS model are reported. The review had the following purposes: (1) to test the computational validity of the computer model by comparison with preliminary hand calculations based on conventional cost estimating techniques; (2) to review and improve the accuracy of the cost relationships being used by the model: and (3) to provide an independent verification to users of the model's value in decision making for allocation of research and developement funds and for investment in manufacturing capacity. It is concluded that the SAMICS model is a flexible, accurate, and useful tool for managerial decision making.

Source record↗

Solar pond power plant feasibility study for Davis, California

The feasibility of constructing a solar pond power plant at Davis, California was studied. Site visits, weather data compilation, soil and water analyses, conceptual system design and analyses, a material and equipment market survey, conceptual site layout, and a preliminary cost estimate were studied. It was concluded that a solar pond power plant is technically feasible, but economically unattractive. The relatively small scale of the proposed plant and the high cost of importing salt resulted in a disproportionately high capital investment with respect to the annual energy production capacity of the plant. Cycle optimization and increased plant size would increase the economical attractiveness of the proposed concept.

Wu, Y. C.↗

Discrimination of soil hydraulic properties by combined thermal infrared and microwave remote sensing

Using the De Vries models for thermal conductivity and heat capacity, thermal inertia was determined as a function of soil moisture for 12 classes of soil types ranging from sand to clay. A coupled heat and moisture balance model was used to describe the thermal behavior of the top soil, while microwave remote sensing was used to estimate the soil moisture content of the same top soil. Soil hydraulic parameters are found to be very highly correlated with the combination of soil moisture content and thermal inertia at the same moisture content. Therefore, a remotely sensed estimate of the thermal behavior of the soil from diurnal soil temperature observations and an independent remotely sensed estimate of soil moisture content gives the possibility of estimating soil hydraulic properties by remote sensing.

Vandegriend, A. A.↗

The effect of model uncertainty on some optimal routing problems

The effect of model uncertainties on optimal routing in a system of parallel queues is examined. The uncertainty arises in modeling the service time distribution for the customers (jobs, packets) to be served. For a Poisson arrival process and Bernoulli routing, the optimal mean system delay generally depends on the variance of this distribution. However, as the input traffic load approaches the system capacity the optimal routing assignment and corresponding mean system delay are shown to converge to a variance-invariant point. The implications of these results are examined in the context of gradient-based routing algorithms. An example of a model-independent algorithm using online gradient estimation is also included.

Mohanty, Bibhu↗

WBS 1.2.3.405 - Life Cycle Assessment of Storage Technologies

Recent commitments by the Biden administration have established targets to achieve a net-zero energy system by 2050. Meeting these targets will spur a rapid transition to clean energy technologies and a commensurate need to develop and deploy energy storage technologies at scale. Pumped Storage Hydro (PSH) is expected to be part of this solution because its ability to provide grid flexibility and stability and enable the dispatching of disparate variable renewable energy technologies. Despite PSH being a mature technology with a history of deployment dating back several decades, there is very little information on the greenhouse gas (GHG) implications of PSH as compared to other storage technologies. The objective of this project is to perform a full lifecycle assessment (LCA) of new PSH projects in the U.S. This LCA includes all project phases (resource extraction, construction, operation, maintenance, end-of-life). The functional unit for this study is 1 kWh electricity delivered by system to grid substation connection point and the estimated lifetime for our base case is 80 years. Data used in this study are based on over 30 potential PSH projects that are in preliminary planning phases and are represent a wide range of potential closed-loop PSH systems in terms of location, technology, and capacity. The project approach, data sources, and modeling assumptions have been informed by a technical review committee of stakeholders that include experts from academia, national and international government, industry, and utilities. The GHGs and energy return on investment (EROI) from PSH will be compared to other storage technologies (e.g., stationary battery storage). Results from this project will improve the PSH community's understanding of the environmental impacts and sustainability of new PSH projects and how PSH compares to other storage technologies. The approach used in this project relies on open-source programming. The analysis framework (source code and data) and will be made publicly available at the end of the project. In addition to reporting results for the base case, we will perform rigorous sensitivity analysis to identify the major drivers, understand impacts of different configurations, and future energy markets. Results from this project will be published in a suitable journal.

ENERGY PLANNING, POLICY, AND ECONOMY,HYDRO ENERGY↗

Preliminary analysis of core heat-up for ATFs under accident conditions

The accident-tolerant fuel (ATF) system is aim at upgrading safety characteristics of the nuclear fuel and cladding in a reactor core where active cooling has been lost, and is preferable or comparable to the conventional UO{sub 2}-Zr fuel system when the reactor is in normal operation. In this paper, the improved performance of UO{sub 2}-SiC, UO{sub 2}-FeCrAl fuel systems, and of fully ceramic micro-encapsulated (FCM) fuels: FCM-SiC and FCM-FeCrAl, on the core heat-up progress in a pressurized water reactor (PWR) is analyzed by using the best-estimate system code RELAP5 and severe accident analysis program. For this purpose two accident scenarios are selected: a large break LOCA as a design base accident and an extended station blackout (SBO) severe accident. For the LBLOCA with just low-pressure safety injection, larger volumetric heat capacity and thermal conductivity of ATF materials contribute to a larger safety margin in terms of the peak cladding temperature compared with UO{sub 2}-Zr. Thanks to higher melting temperatures, FCM-SiC is failed by melting almost 1200 s later than UO{sub 2}-Zr. The accumulated production of hydrogen for ATF materials is around 10 times smaller than that for UO{sub 2}-Zr. However, high temperature oxidation of SiC cladding generates carbon monoxide which is combustible, while the melting point of FeCrAl is not high enough. In the SBO scenario with mitigation measure, the advantage of ATF is more evident. If the mitigation measure could not be taken, core heatup is inevitable for all types of fuel system, but the temperature rising of ATF core is much slower. In general, improved high-temperature properties and resistance to oxidation play important roles for ATF cores.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Utility-Scale Solar, 2024 Edition: Empirical Trends in Deployment, Technology, Cost, Performance, PPA Pricing, and Value in the United States [Slides]

Berkeley Lab’s “Utility-Scale Solar, 2024 Edition” presents analysis of empirical plant-level data from the U.S. fleet of ground-mounted photovoltaic (PV), PV+battery, and concentrating solar-thermal power (CSP) plants with capacities exceeding 5 MWAC (PV plants of 5 MWAC or less, including residential rooftop systems, are covered separately in Berkeley Lab’s companion annual report, Tracking the Sun). Key findings from this year’s report include: -18.5 GWAC of new utility-scale PV capacity came online in 2023, bringing cumulative installed capacity to more than 80.2 GWAC across 47 states. Installed costs continued to fall in 2023. Relative to 2022, capacity-weighted averages decreased by 8% to -$\$1.43$/WAC (or $\$1.08$/WDC). Costs, based on a 7.1 GWAC sample of 76 plants completed in 2023, have fallen by 75% (averaging 10% annually) since 2010. Plant-level capacity factors vary widely, from 6% to 36% (on an AC basis), with a sample median of 24%. -Levelized cost of energy (LCOE) of new 2023 projects increased slightly to $\$46$/MWh prior to the application of tax credits but continued to fall to $\$31$/MWh when accounting for federal incentives. PPA prices have largely followed the decline in solar’s LCOE over time, but newly signed longer-term PPA prices have increased since 2021, to an average of $\$35$/MWh (levelized, in 2023 dollars). -Solar’s average energy and capacity value (i.e., ability to offset costs of other power generation sources) across the U.S. was $\$45$/MWh in 2023. Solar’s average market value was lowest in CAISO ($\$27$/MWh), the market with the greatest solar generation share, and highest in ERCOT ($\$67$/MWh). -Newer solar projects had greater market value in 2023 than their generation costs, yielding $\$1.1$ billion in benefits. Projects built in 2022 delivered on average $\$15$/MWh more market value than their costs in 2023. -Solar’s combined value from wholesale electricity markets, public health and climate damage reduction were greater than generation costs and incentives, yielding $\$13.7$ billion in net benefits in 2023. We estimate U.S. health benefits of $\$24$/MWh and reduced global climate damages of $\$101$/MWh. -Adding battery storage is one way to increase the value of solar. Deployment of 52 new PV+battery hybrid plants set a record with 5.3 GW installed in 2023. Our public data file tracks metadata and PPA prices from more than 100 PV+battery hybrid projects that are already online or that have secured offtake arrangements. -Looking ahead, a massive pipeline of at least 1,085 GW of solar capacity dominates the nation’s interconnection queues at the end of 2023. Nearly 571 GW, or 53%, of that total was paired with a battery – in CAISO it was a staggering 98%. Historically only 10% of the requested solar capacity is built. -For more information, and to explore related interactive data visualizations, go to utilityscalesolar.lbl.gov.

14 SOLAR ENERGY↗

Weaker land–climate feedbacks from nutrient uptake during photosynthesis-inactive periods

Terrestrial carbon–climate feedbacks depend on two large and opposing fluxes—soil organic matter decomposition and photosynthesis—that are tightly regulated by nutrients. Earth system models (ESMs) participating in the Coupled Model Intercomparison Project Phase 5 represented nutrient dynamics poorly, rendering predictions of twenty-first century carbon–climate feedbacks highly uncertain. Here, we use a new land model to quantify the effects of observed plant nutrient uptake mechanisms missing in most other ESMs. In particular, we estimate the global role of root nutrient competition with microbes and abiotic processes during periods without photosynthesis. Nitrogen and phosphorus uptake during these periods account for 45 and 43%, respectively, of annual uptake, with large latitudinal variation. Globally, night-time nutrient uptake dominates this signal. Simulations show that ignoring this plant uptake, as is done when applying an instantaneous relative demand approach, leads to large positive biases in annual nitrogen leaching (96%) and N 2 O emissions (44%). Furthermore, this N 2 O emission bias has a GWP equivalent of ~2.4 PgCO 2 yr –1 , which is substantial compared to the current terrestrial CO 2 sink. Such large biases will lead to predictions of overly open terrestrial nutrient cycles and lower carbon sequestration capacity. Both factors imply over-prediction of positive terrestrial feedbacks with climate in current ESMs.

54 ENVIRONMENTAL SCIENCES↗

Density functional theory investigation of the LiIn 1- x Ga x Se 2 solid solution

Here, the electronic structure and optical properties of the LiIn 1-x Ga x Se 2 (x=0, 0.25, 0.5, 0.75, 1) solid solution were studied by density functional theory (DFT) with pure functionals. The exchange-correlation is treated within the local density approximation (LDA) and generalized-gradient approximation (GGA). The electronic structures for each respective compound are discussed in detail. Calculations reveal that gallium incorporation can be used to tune the optical-electrical properties of the solid solution and correlates with the lattice parameter. The band gap trend of the LiIn 1-x Ga x Se 2 system follows a nonlinear behavior between the LiInSe 2 and LiGaSe 2 ternary boundaries. The bowing parameter is estimated to be on the order of 0.1- 0.3 eV at the point. Low-temperature optical absorption revealed a 30% change in the temperature dependence of the band gap for the intermediate compound LiIn 0.6 Ga 0.4 Se 2 compared to ternary boundaries and suggests the heat capacity to be another control element through strain.

36 MATERIALS SCIENCE↗

Clustering representative days for power systems generation expansion planning: Capturing the effects of variable renewables and energy storage

Decision makers rely on models to make important regulatory, policy, and investment decisions. For power systems, these models must capture (i) the future challenges introduced by the integration of large quantities of variable renewable energy sources and (ii) the role that energy storage technologies should play. In this paper, we explore several different approaches to selecting representative days for generation expansion planning models, focusing on capturing these dynamics. Further, we propose a new methodology for adjusting the outputs of clustering algorithms that provides three advantages: the targeted level of net demand is captured, the underlying net demand shapes that define ramping challenges are accurately represented, and the relationship between annual energy and peak demand is captured. This weighting methodology reduces the magnitude of the error in the representative day based generation expansion planning models estimation of costs by 61% on average. The results also demonstrate the importance of carefully performing the clustering of representative days for both system costs and technology mix. In most cases improvements to the total cost of different representative day based expansion plans are realised where conventional generation capacity is substituted for energy storage. Based on the energy storage technology selected we conclude this capacity is being used to address ramping challenges as opposed to shifting renewable generation from off to on peak periods, reinforcing the importance of capturing detailed intraday dynamics in the representative day selection process.

Clustering↗

Detecting Short Circuits: Post Accident Electric Vehicle Battery Safety Check

Fast and accurate detection of soft short circuits (SCs) in the battery packs of damaged electric vehicles is needed by first responders and mechanics to mitigate the potential risk from battery fires that may occur hours, days, or weeks after an accident. Here, this paper presents an SC-detection algorithm for potentially damaged lithium-ion batteries that works quickly and without a priori knowledge of the battery-pack chemistry, capacity, state of charge, or state of health. The proposed universal SC-detection algorithm is designed to be implemented on an inexpensive handheld device that can connect to and monitor the voltages of all cells in a pack. Transient filtering and linear-quadratic state observation provide estimates of normalized SC current for every cell in the pack. Cells with SC-current estimates outside a sigma-based threshold are detected. Simulations, experiments, and electric vehicle (EV) crash data are used to verify the speed, sensitivity, and accuracy of the method, demonstrating 96% accurate detection of 0.0027 C SCs in under 1 h for 5S cell groups in the lab and no false positives for crashed Volkswagen, Chevrolet, and Tesla vehicles without SCs.

25 - ENERGY STORAGE↗

Hydropower Capital and O&M Costs: An Exploration of the FERC Form 1 Data

This report explores the potential for using responses from the Federal Energy Regulatory Commission’s (FERC’s) “Electric Utility Annual Report,” also known as FERC Form 1, as a cost database for conventional and pumped storage hydropower (PSH). The report outlines the process used to compile an easy-to-access database from the original FERC Form 1 data and discusses the historical cost/performance data. The steps for developing the database include downloading the annual FoxPro files from the FERC website (FERC, 2020), reading them into an Excel format, and reconciling naming issues across years, repeated entries, and shared assets, among others. The cleaned and compiled Form 1 database is available on Oak Ridge National Laboratory’s (ORNL’s) HydroSource website. For this report, the compiled Form 1 database was linked to two other hydropower databases, the National Inventory of Dams and the ORNL Existing Hydropower Assets, that provide additional information on the characteristics and other features of plants in the Form 1 data. Explorations of the plant characteristics, performance, capital costs, and operation and maintenance (O&M) cost data in the combined database were presented separately for conventional hydropower and PSH projects. Form 1 has several advantages as a hydropower cost database. First, the cost data is reported directly by plant owners. Second, Form 1 provides cost breakdowns of capital and operating costs for large conventional and PSH plants enabling more detailed tracking of hydropower costs compared with typical total cost estimates. Third, although the Form 1 data is not reported by all operational hydropower plants in the United States, the available data represents a wide range of plant characteristics and a sizable proportion of the hydropower fleet (61% of PSH plants and 22% of conventional hydropower plants by capacity). The lower proportion of the conventional hydropower fleet is because Form 1 reporting requirements apply only to private utilities that meet given size thresholds, leaving out federally owned facilities and many smaller hydropower plants. Overall, the Form 1 cost database represents a unique, publicly available database on hydropower asset capital and O&M costs. This report leads to a compiled database for the reporting years 1994 to 2020 that helps resolve issues with accessibility and use of the FERC Form 1 data by hydropower plant owners, project developers, technology developers, and regulators.

13 HYDRO ENERGY↗

Uncertainty quantification for equations of state: copper as an example

Equations of state are essential for providing a fundamental description of materials properties in thermodynamic equilibrium and are used to provide closure relations for hydrodynamics simulations. Generally, equations of state rely on simple physics-based parameterized materials models to inform on the free energy of a material through out a given thermodynamic state space. Historically the parameters of these models have been tuned by hand to fit various experimental data. However, modern optimization and uncertainty quantification techniques allow us to quickly test thousands of parameter combinations and obtain meaningful uncertainty estimates on the parameters, opening opportunities for assessing systematic uncertainties in experiments, assessing model adequacy, and more. In this report, we use Bayesian inference to fit the solid (fcc) equation of state of copper. We focus on fitting five different experimental datasets, including the isobaric density, isobaric heat capacity, room temperature isotherm, principal isentrope, and principal Hugoniot. We fit all five data types simultaneously, and then explore the extent to which combinations of 2 subsets of the 5 datasets can constrain the EOS parameters, as compared to the fit to all 5. This information is useful for investigating the extent to which different datasets can con strain EOS models and thereby help guide experimental investigations in order to best constrain the EOS. We also discuss ways that the methodologies can be used to investigate systematic discrepancies between experiments, as well as how the methods can be used to assess model uncertainty. The framework we develop is general, in that it can be used with a variety of optimization or uncertainty quantification techniques and with a variety of data sources, including both experimental and ab-inito data.

97 MATHEMATICS AND COMPUTING↗