Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Capacity”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Hawthorne Nevada Deep Direct-Use Feasibility Study - Data Used for Geothermal Resource Conceptual Modeling and Power Capacity Estimates

This data submission includes several data components that were used to develop a conceptual model and power capacity-estimates of two low-temperature geothermal resources that define geothermal prospect A at Hawthorne, Nevada. Data are sourced from a combination of legacy publicly-available data and more recent data acquisition conducted by the US Navy Geothermal Program Office (2008-2013) and the Great Basin Center for Geothermal Energy at the University of Nevada, Reno (2008-2010). Data sets include compiled fluid geochemistry data, down-hole temperature logs for wells in the vicinity of prospect A, 2 meter temperature survey data, temperature-spinner logs acquired in well HWAAD-2A, fracture picks from image log data acquired in wells HWAAD-2 and HWAAD-3, and X-Ray Diffraction (XRD) analyses on cuttings from wells HWAAD-2A and HWAAD-3. These data have been reviewed for errors and inconsistencies, but it is possible that few errors could still remain. The resource conceptual model and power capacity estimates are included in the final report to the US Department of Energy, and are presented in a manuscript by Ayling and Hinz. A link to the manuscript published in Geothermics is linked below in this submission.

15 GEOTHERMAL ENERGY↗
DOE OSTI2027

From zonal to nodal capacity expansion planning: Spatial aggregation impacts on a realistic test-case

Solving power system capacity expansion planning (CEP) problems at realistic spatial resolutions is computationally challenging. Thus, a common practice is to solve CEP over zonal models with low spatial resolution rather than over full-scale nodal power networks. Due to improvements in solving large-scale stochastic mixed integer programs, these computational limitations are becoming less relevant, and the assumption that zonal models are realistic and useful approximations of nodal CEP is worth revisiting. Here, this work is the first to conduct a systematic computational study on the assumption that spatial aggregation can reasonably be used for ISO-scale CEP. By considering a realistic, large-scale test network based on the state of California with over 8000 buses, we find that well-designed small spatial aggregations can yield good approximations but that coarser zonal models may result in large distortions of investment decisions, e.g., capacity under-investment of up to 41% for the lowest resolution model considered.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Measuring the maximum capacity and thermal resistances in phase-change thermal storage devices

Thermal energy storage can increase the efficiency of the electric grid by adding flexibility to thermal systems. The value of thermal storage is a function of its energy and power density, which are driven by the capacity and thermal resistances in the storage device. Measuring these properties in-situ at the device level is an important step to understanding the performance and improving the design of thermal storage systems. Here, we present methods to measure the total capacity and thermal resistances in heat exchangers with integrated phase change materials. These methods are demonstrated on two thermal storage devices - a 570-kWh ice-based storage tank and a 0.35-kWh graphite-tetradecane composite device. The results show how thermal resistances evolve with the state of charge and discharge rate in these devices and quantify the impact of applied pressure on the contact resistance in composite phase change material heat exchangers. The proposed method allows for easy comparison between different systems and provides information on the thermal bottlenecks limiting performance. Ultimately, these measurements will allow designers to make robust, high-performance thermal storage devices for next-generation thermal systems.

25 ENERGY STORAGE↗
DOE OSTI2025

Sparse chronology strategy for integrating seasonal energy storage in capacity expansion models

Here, this study develops the sparse chronology method to enhance the representative period framework in capacity expansion models, enabling the effective integration of long-duration energy storage modeling. Traditional representative period methods cannot capture the state of charge of seasonal energy storage systems because they do not establish effective inter-day linkages to connect the state of charge between periods. The sparse chronology approach addresses this limitation by establishing inter-day linkages that allow state of charge to shift inter-seasonally. At the same time, it groups identical representative days into partitions, applying constraints sparsely and implicitly to reduce computational load further. Validation results demonstrate that this method successfully simulates long-duration energy storage patterns, achieving close alignment with a continuous yearly benchmark model, with seasonal trends and state of charge cycles clearly represented. The computational load analysis reveals that the sparse chronology method efficiently applies constraints on maximum and minimum state of charge limits within the representative day framework, eliminating the need for detailed constraints on each individual day. By partitioning representative days and constraining only the start and end of each partition, the method significantly decreases computational requirements. Simulation results show that sparse chronology closely approximates the continuous yearly method's accuracy, even with as few as 20 representative days, achieving correlation values with the benchmark of nearly 0.9 in state of charge plots. Furthermore, it maintains computational efficiency, requiring only 4 % of the solver time compared to the continuous yearly method with 20 representative days. This approach allows capacity expansion models to incorporate long-duration energy storage with high temporal, spatial, and technological resolution, enabling more detailed modeling for large-scale power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Quantifying pH buffering capacity in acidic, organic-rich Arctic soils: Measurable proxies and implications for soil carbon degradation

Dynamic pH change promoted by biogeochemical reactions in Arctic tundra soils can be a major control on the production and release of CO 2 and CH 4 , which contribute to rising global temperatures. Large quantities of soil organic matter (SOM) in these soils are susceptible to microbial decomposition, leading to pH changes during permafrost thaw. Soil pH buffering capacity (β) modulates the extent of pH change but has not been thoroughly studied and represented in predictive ecosystem scale biogeochemical models in Arctic tundra soils. In this study, we generated titration curves for 21 acidic tundra soils from three Arctic sites across northern Alaska, United States of America. Geochemical and hydrological soil properties were evaluated, and correlations with β were developed. Strong correlations between β and both gravimetric water content (Θ g ) (R 2 = 0.847, p < 0.001) and soil water retention (SWR) (R 2 = 0.849, p = 0.001) indicate that the ability of soil to retain water could be associated with its buffering properties. Correlations between β and soil organic carbon (SOC) and cation exchange capacity (CEC) were also explored, and relationships to SWR are discussed. These correlations were then used with existing soil databases reporting SOC, CEC, and SWR to estimate β across Alaska soils. We further demonstrated the quantitative relationships between β and the simulated rates of biogeochemical reactions and show that lower β leads to higher soil pH and more CH 4 production. Overall, our study provides simple proxies for β in Arctic soils and highlights the importance and implications of representing soil buffering in predictive models, thereby enabling quantitative coupling between pH dynamics associated with biogeochemical reactions. Integrating β into predictive models of Arctic biogeochemical cycling may reduce model uncertainty and further our understanding of permafrost SOM degradation accelerated by warming.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Structural and thermodynamic effects of hydration in Na-zeolite A (LTA) from low-temperature heat capacity

Zeolite A (Linde Type A; LTA) is an industrially important porous mineral that has recently been shown to exhibit framework flexibility upon changes in hydration level. Here, to investigate the flexibility transition from a thermodynamic perspective, we have performed heat capacity measurements on sodium zeolite A at seven incremental hydration levels ranging from zero to equilibrium with ambient air. Excess low-frequency vibrations beyond the predictions of the Debye model are found in all samples, and the frequency of these vibrations increases as a function of hydration level. This suggests that an increase in hydration causes a decrease in at least one type of framework flexibility for sodium zeolite A. In addition, a subtle excess heat capacity contribution from 150 to 280 K is observed only for low and intermediate hydration levels, which may arise from a transformation tied to framework flexibility previously observed in zeolite A via gas absorption calorimetry. Values of the standard thermodynamic functions C p,m °, Δ 0 T S m °, Δ 0 T H m °, and Φ m ° are also reported.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Reversible hydrogen storage in multilayer graphane: Lattice dynamics, compressibility, and heat capacity studies

Multilayer graphane (hydride of graphite) is a crystalline hydrocarbon of composition CH, which can be synthesized from graphite and molecular hydrogen at pressures above 2GPa [V.E. Antonov et al. Carbon 100 (2016) 465]. Using X-ray diffraction, this compound was tentatively identified as the “graphane II” phase of 3D-graphane predicted by ab initio calculations [X.-D. Wen et al. PNAS 108 (2011) 6833] and consisting of layers of 2D-graphane in the “chair” conformation. When heated in a vacuum, the compound does not form any intermediate hydrocarbons and reversibly decomposes back into graphite and hydrogen at 770–920 K. In the present work, almost single-phase samples of graphite hydride and deuteride were synthesized at 7.4 GPa and 870 K. Their investigation by inelastic neutron scattering supplemented by ab initio calculations gave spectra g(E) of the phonon density of states with a gap of about 15 meV at approx. 100 meV, which is a unique identifier for the chair form of graphane. The equation of state V(P) of the hydride was studied at room temperature and hydrogen pressures up to 53 GPa by synchrotron X-ray diffraction in a diamond anvil cell. Further, the graphane II phase did not react with the surrounding hydrogen and did not undergo any phase transformations upon the compression and after heating to 1500 K at 53GPa. The high thermal and pressure stability of this exotic phase makes it an important part of the C–H system. The obtained g(E) spectra of graphite hydride and deuteride were used to calculate temperature dependences of their heat capacity. Measurements of the heat capacity at temperatures 120–673 K confirmed the good accuracy of these calculations.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Evaluation of phenolic antioxidant capacity in beverages based on laccase immobilized on screen-printed carbon electrode modified with graphene nanoplatelets and gold nanoparticles

A simple and highly sensitive electrochemical biosensor based on laccase immobilized onto a gold nanoparticles/graphene nanoplatelets-modified screen-printed carbon electrode (LACC/AuNP/GNPl/SPCE) was developed for the determination of hydroquinone (HQ) and other phenolic compounds. The biosensor shows excellent electro-catalytic activity towards oxidation of hydroquinone at a potential of -0.05 V (vs Ag/AgCl, 3 M KCl) in phosphate buffer as supporting electrolyte (0.1 M, pH 7.0) using hydrodynamic amperometry. Analytical characteristics uncover that the LACC/AuNP/GNPl/SPCE comprises a wide linear range for the dependence of the signal on HQ concentrations from 4 to 130 µM with a detection limit (3σ) of 1.5 µM. The repeatability (5 measurements, 100 µM hydroquinone) is ±2% and the reproducibility (5 biosensors, 100 µM hydroquinone) is ±3%. Interference studies of most common compounds with the determination of hydroquinone demonstrated negligible effects. Finally, the biosensor and the analytical method were applied to the determination of phenolic antioxidant capacity (AOC) in wine and blueberry syrup based on Trolox (6‑hydroxy‑2,5,7,8-tetramethylchromane-2-carboxylic acid) and hydroquinone equivalents. The results were evaluated by using their calibration curves which were satisfactory and agreed well with the results obtained by the reference method Trolox Equivalent Antioxidant Capacity assay (TEAC-Assay).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

A high-capacity cathode for rechargeable K-metal battery based on reversible superoxide-peroxide conversion

Abstract As a promising low-cost energy storage device, the development of a rechargeable potassium-ion battery (KIB) is severely hindered by the limited capacity of cathode candidates. Regarded as an attractive capacity-boosting strategy, triggering the O-related anionic redox activity has not been achieved within a sealed KIB system. Herein, in contrast to the typical gaseous open K-O2 battery (O2/KO2 redox), we originally realize the reversible superoxide/peroxide (KO2/K2O2) interconversion on a KO2-based cathode. Controlled within a sealed cell environment, the irreversible O2 evolution and electrolyte decomposition (induced by superoxide anion (O2−) formation) are effectively restrained. Rationally controlling the reversible depth-of-charge at 300 mAh/g (based on the mass of KO2), no obvious cell degradation can be observed during 900 cycles. Moreover, benefitting from electrolyte modification, the KO2-based cathode is coupled with a limited amount of K-metal anode (merely 2.5 times excess), harvesting a K-metal full-cell with high energy efficiency (∼90%) and long-term cycling stability (over 300 cycles).

25 ENERGY STORAGE↗
DOE OSTI2024

Transmission Interface Limits for High-Spatial Resolution Capacity Expansion Modeling

Large-scale capacity expansion models typically rely on estimates of the power transfer limits between modeled zones. Accurate estimation of these interface transfer limits (ITLs) requires modeling the underlying transmission network. Here we expand on a maximum flow optimization method that uses linearized power flow to estimate transfer limits. We apply this method to a data set of the U.S. transmission network to estimate ITLs between U.S. counties. By calculating ITLs using different subsets of the network, we evaluate how the size of the network used in the estimation affects the results. The results show diminishing returns to ITL accuracy after six hops, suggesting that a network subset can reasonably be used to approximate ITLs. The county-level estimates produced in this study will support more spatially resolved capacity expansion modeling and will help inform policy making at local and national levels.

capacity planning↗
DOE OSTI2024

Endogenizing Probabilistic Resource Adequacy Risks in Deterministic Capacity Expansion Models

In this work, we demonstrate how power system capacity expansion models can understate the stochastic effects of thermal outages when considering resource availabilities on an hourly expected value basis, yielding system designs with multiple orders of magnitude more shortfall risk than stated adequacy targets. We develop a novel approximation approach to efficiently endogenize awareness of this risk in a deterministic, linear capacity expansion framework. We compare this approach to exogenous tuning of an energy reserve margin, the leading alternative method to compensate for unmodeled probabilistic shortfall risk. Empirical results from a test system show that the new endogenous method cost-effectively meets all regional reliability targets with a single optimization solve, and produces a near-identical system design as the incumbent method without the need for repeated re-optimizations to find an appropriate reserve level. The endogenous method may also use iterative re-optimizations to further improve solution quality, although these incremental benefits were modest in the system studied.

capacity expansion modeling↗
DOE OSTI2022

Inference of photosynthetic capacity parameters from chlorophyll a fluorescence is affected by redox state of PSII reaction centers

Solar-induced chlorophyll fluorescence (SIF) has been used to infer photosynthetic capacity parameters (e.g., the maximum carboxylation rate V cmax , and the maximum electron transport rate J max ). However, the precise mechanism and practical utility of such approach under dynamic environments remain unclear. In this study, we used the balance between the light and carbon reactions to derive theoretical equations relating chlorophyll a fluorescence (ChlF) emission and photosynthetic capacity parameters, and formulated testable hypotheses regarding the dynamic relationships between the true total ChlF emitted from PSII (SIF PSII ) and V cmax and J max . We employed concurrent measurements of gas exchanges and ChlF parameters for 15 species from six biomes to test the formulated hypotheses across species, temperatures, and limitation state of carboxylation. Our results revealed that SIF PSII alone is incapable of informing the variations in V cmax and J max across species, even when SIF PSII is determined under the same environmental conditions. In contrast, the product of SIF PSII and the fraction of open PSII reactions q L , which indicates the redox state of PSII, is a strong predictor of both V cmax and J max , although their precise relationships vary somewhat with environmental conditions. Our findings suggest the redox state of PSII strongly influences the relationship between SIF PSII and V cmax and J max .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

A Quantitative Failure Analysis on Capacity Fade in Rechargeable Lithium Metal Cells

Rechargeable lithium battery (RLB) technology is transforming portable devices, vehicle electrification, and grid modernization. To make RLB durable, reliable and safe, conducting failure mode and effect analysis (FMEA) to identify failure mechanism under the operating conditions is very desirable. However, this ability is often overlooked or even lacking. The failure analysis (FA) is often conducted by laboratory testing and postmortem analysis, and the knowledge typically empirical. Here we present a quantitative approach for FMEA that can reveal how failure modes and effects reduce the capacity of a RLB. This approach is based on the state of the battery for FMEA, contrary to the conventional approach based on operating or testing conditions. The key aspect of this FMEA method is to convert the experimental results to a state-of-charge (SOC)-based analytic methodology. Such a conversion can separate the thermodynamic and kinetic attributes of capacity fade based on compositional correspondence in the electrode, so the loss and the decreased utilization of the active materials can be determined respectively.

25 ENERGY STORAGE↗
DOE OSTI2021

Representing DC-Coupled PV+Battery Hybrids in a Capacity Expansion Model

Recent technology cost and performance improvements and the federal investment tax credit (ITC) have driven growing interest in coupling solar photovoltaic (PV) and battery systems. Combining these technologies into co-located or hybridized PV+battery systems has the potential to lower costs and increase energy output relative to multiple independent systems. In this work, we provide an overview of PV+battery systems and demonstrate methods for incorporating them into NREL’s Regional Energy Deployment System (ReEDS) capacity expansion model. Although the methods are applied to a specific model, we anticipate that the approaches used here can be useful for informing PV+battery method development for other capacity expansion models. The implemented method relies heavily on the native representations of PV and battery technologies; therefore, the focus of this work is on capturing and parameterizing the interactions between them for a configuration in which the PV and battery technologies share a single bi-directional inverter. This work also demonstrates the impacts of including PV+battery systems in the ReEDS optimization for the conterminous United States through 2050. In particular, we perform parametric sensitivities for input assumptions that are uncertain and expected to influence PV+battery deployment levels, including (a) the cost of PV+battery systems relative to independent PV and battery systems, (b) the battery component’s qualification for the ITC, and (c) future cost trajectories for PV and battery systems. We find that PV+battery deployment could occur throughout the conterminous United States if there are cost savings associated with DC coupling PV and battery technologies. If even modest (5%) cost savings can be achieved (through a shared inverter and balance-of-system costs), then approximately one-third of utility-scale PV deployment through 2050 adopts the DC-coupled hybrid configuration, resulting in total PV+battery deployment that exceeds the magnitude of PV+battery projects in U.S. interconnection queues in 2020. If greater cost savings can be achieved through DC coupling (e.g., due to a growing amount of shared balance-of-system costs, reduced financial risk, or modularity) or more rapid cost and performance improvements are realized for PV and battery technologies, then total PV+battery deployment and the share of PV and battery deployment that adopts the hybrid configuration grows (to >50%). In all cases, growing PV+battery deployment primarily displaces independent PV and battery technologies, indicating the strong competition between the hybrid and independent configurations comprising technologies with similar performance characteristics.

14 SOLAR ENERGY↗
DOE OSTI2021

Comparing Capacity Credit Calculations for Wind: A Case Study in Texas

The degree to which wind energy can contribute to the capacity needed to meet resource adequacy requirements, also known as capacity credit (CC), varies regionally with wind resource and correlation to net load. CC is an important metric widely used for resource planning and resource adequacy assessments. However, there are multiple methods for computing and estimating CC, depending on specific needs, access to data, and computational burden. It is unclear the extent to which the CC computation method may influence the result. To address this, we use a probabilistic resource adequacy tool and multiple approximation methods to systematically assess the CC of wind for near-term wind deployment under a case study in Texas. We find that proper consideration of transmission constraints is important; some approximation methods may overestimate the CC of wind due to a lack of consideration of transmission constraints, while other approximation methods may underestimate the CC by not capturing the ability of wind to be shipped to neighboring regions. In this case study, we find that several approximation methods do come close to the CC calculated by more robust probabilistic methods. However, the best approximation method may vary on a case-by-case basis, depending on system-specific considerations.

17 WIND ENERGY↗
DOE OSTI2024

Nodal Capacity Expansion Modeling with ReEDS: A Case Study of the RTS-GMLC Test System

Test systems play an important role in power systems analysis and are used extensively for a wide range of purposes like reliability analysis, production cost modeling, studying the impacts of load shifting, and many more. These test systems have continued to evolve over the years to keep pace with changing system compositions due to technology and policy changes. In this work, we apply the Regional Energy Deployment System (ReEDS) model, a large-scale capacity expansion model (CEM), on the nodal RTS-GMLC system to perform capacity expansion of the bus-level test system. This work both demonstrates that a large-scale CEM can successfully be applied to nodal systems, and that the CEM can allow a test system to be evolved to meet desired criteria. The process allowed the coupling of CEM data not available in the test system (such as capital costs) with test system data to provide plausible system evolutions in line with scenario specifications.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Electric Vehicle Charging Management in Smart Energy Communities to Increase Renewable Energy Hosting Capacity

Abnormal climates due to global warming have emerged as a big concern in the global community. To mitigate climate change and achieve sustainability, distributed energy resources (DERs), including solar and wind, have been recently deployed in power systems. As the penetration level of DERs has increased, however, it caused a multitude of issues in the power systems, such as voltage fluctuation in the distribution network limiting renewable hosting capacity. On the other hand, the electric vehicle (EV) industry is rapidly growing to facilitate the transition to a carbon-neutral community, illuminating the potential of EVs as a flexible grid asset to mitigate some of the issues and improve grid operation, if properly exploited. To explore the potential of EVs, this paper proposes an EV scheduling strategy. By using an optimal EV charging scheduling proposed, distribution system operators (DSOs) can minimize their operating costs and stably operate the system with a high level of DERs. To validate the method, a modified IEEE 33-bus system with DERs is developed. The case study shows the proposed scheduling strategizes EV charging to reduce the cost of PV curtailment. In the study, the method outperforms the renewable-only case with curtailment by 4.97% in DSO cost. It also demonstrates its potential to increase the renewable hosting capacity by harmonizing EV charging with renewables.

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗