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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Operando study of mechanical integrity of high-volume expansion Li-ion battery anode materials coated by Al 2 O 3

Group IV elements and their oxides, such as Si, Ge, Sn and SiO have much higher theoretical capacity than commercial graphite anode. However, these materials undergo large volume change during cycling, resulting in severe structural degradation and capacity fading. Al 2 O 3 coating is considered an approach to improve the mechanical stability of high-capacity anode materials. To understand the effect of Al 2 O 3 coating directly, we monitored the morphology change of coated/uncoated Sn particles during cycling using operando focused ion beam–scanning electron microscopy. Here, the results indicate that the Al 2 O 3 coating provides local protection and reduces crack formation at the early stage of volume expansion. The 3 nm Al 2 O 3 coating layer provides better protection than the 10 and 30 nm coating layer. Nevertheless, the Al 2 O 3 coating is unable to prevent the pulverization at the later stage of cycling because of large volume expansion.

25 ENERGY STORAGE↗
NASA NTRS1983

Effect of denervation and reinnervation on oxidation of 6-(C-14) glucose by rat skeletal muscle homogenates

The effects of denervation and reinnervation of the rat extensor digitorum longus muscle on the oxidation of 6-(C-14) glucose to (C-14)O2 is investigated. Results show that the rate of (C-14)O2 production decreased dramatically following denervation and the decrease became significant 20 days after nerve section. The changes which occurred prior to day 20 apparently reflected the decline of muscle mass. The decreased (C-14)O2 production was found to be due to reduced capacity of the enzymatic system, while there was no change in the apparent affinity for glucose. Results of mixing experiments showed that the loss of oxidative capacity following denervation is not caused by the production of soluble inhibitors by degenerating muscle. Measurements of the (C-14)O2 revealed that oxidative metabolism recovered during reinnervation. The specific activity in reinnervated muscles displayed an 'overshoot' of approximately 50 percent, which returned to control levels by day 60. The time-course of the denervation-mediated change indicates that altered oxidative capacity is secondary to events that initiate dennervation changes in muscle, although diminished oxidative capacity may be of considerable metabolic significance in denervated muscle.

Dubois, D. C.↗
DOE OSTI2023

Boron coordination change in barium borate melts and glasses and its contribution to configurational heat capacity, entropy, and fragility

High-energy x-ray diffraction from molten and glassy BaB 2 O 4 and BaB 4 O 7 has been performed using aerodynamic levitation and laser heating over a wide range of temperatures. Remarkably, even in the presence of a heavy metal modifier dominating x-ray scattering, it was possible to extract accurate values for the tetrahedral, sp 3 , boron fraction, N 4 , which declines with increasing temperature, using bond valence-based mapping from the measured mean B–O bond lengths while accounting for vibrational thermal expansion. These are used within a boron-coordination-change model to extract enthalpies, ΔH, and entropies, ΔS, of isomerization between sp 2 and sp 3 boron. The results for BaB 4 O 7 , ΔH = 22(3) kJ mol -1 boron, ΔS = 19(2) J mol -1 boron K -1 , agree quantitatively with those found previously for Na 2 B 4 O 7 . Analytical expressions for N 4 (J, T) and associated configurational heat capacity, $C_{P}^{conf}$(J, T), and entropy, S conf (J, T), contributions are extended to cover a wide composition range 0 ≤ J = BaO/B 2 O 3 ≤ 3 using a model for ΔH(J) and ΔS(J) derived empirically for lithium borates. Maxima in the $C_{P}^{conf}$(J, T g ) and fragility index contributions are thereby predicted for J ≲ 1, higher than the maximum observed and predicted in N 4 (J, T g ) at J ≃ 0.6. We discuss the utility of the boron-coordination-change isomerization model in the context of borate liquids containing other modifiers and the prospect of neutron diffraction to aid in empirical determinations of modifier-dependent effects, illustrated by new neutron diffraction data on Ba 11 B 4 O 7 glass, its well-known α-polymorph, and lesser-known δ-phase.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1998

GCM Studies on the Interactions Between Photosynthesis and Climate at Diurnal to Decadal Time Scales

Transpiration, a major component of total evaporation from vegetated surfaces, is an unavoidable consequence of photosynthetic carbon fixation. Because of limiting soil moisture and competition for solar radiation plants invest most of their fixed carbon into structural and hydraulic functions (roots and stems) and solar radiation absorption (leaves). These investments permit individuals to overshadow competitors and provide for transport of water from the soil to the leaves where photosynthesis and transpiration occur. Often low soil moisture or high evaporative demand limit the supply of water to leaves reducing photosynthesis and thus transpiration. The absorption of solar radiation for photosynthesis and dissipation of this energy via radiation, heat, mass and momentum fluxes represents the link between photosynthesis and climate. Recognition of these relationships has led to the development of hydro/energy balance models that are based on the physiological ecology of photosynthesis. We discuss an approach to study vegetation-climate interactions using photosynthesis-centric models embedded in a GCM. The rate at which a vegetated area transpires and photosynthesizes is determined by the physiological state of the vegetation, its amount and its type. The latter two are specified from global satellite data collected since 1982. Climate simulations have been carried out to study how this simulated climate system responds to changes in radiative forcing, physiological capacity, atmospheric CO2, vegetation type and variable vegetation cover observed from satellites during the 1980's. Results from these studies reveal significant feedbacks between the vegetation activity and climate. For example, vegetation cover and physiological activity increases cause the total latent heat flux and precipitation to increase while mean and maximum air temperatures decrease. The reverse occurs if cover or activity'decreases. In general climate response of a particular region was dominated by local processes but we also find evidence that plausible climate-vegetation scenarios lead to changes in global atmospheric circulation and strong non-local influences in some cases.

Collatz, G. James↗
DOE OSTI2023

Cost-constrained adaptive simulations of transient spray combustion in a gas turbine combustor

Predictive high-fidelity simulations of turbulent spray combustion must capture the combined effects of complex chemistry, multiphase evaporating flow and spray-flame interactions to achieve physical accuracy. Finite-rate chemistry (FRC) combined with a realistic chemical mechanism is a combustion model well-suited for this purpose, but has a high computational cost due to the large number and stiffness of transported chemical species. In contrast, flamelet-based models achieve lower cost by transporting a small number of quantities of reduced stiffness, but assumptions regarding local flame topology, boundary conditions and inter-phase coupling limit their physical accuracy. Recently, the Pareto-efficient combustion (PEC) framework was developed to dynamically assign combustion models based on local cost and accuracy metrics in gas-phase reacting flows. In this work, we extend this PEC framework to spray combustion through the rigorous analysis of the multiphase coupling terms in the governing equations. The derivation shows that spray evaporation causes errors in the prediction of species mass fractions for flamelet-based models due to the sensitivity of the local thermo-chemical state to changes in composition caused by fuel vaporization across combustion regimes present in practical spray combustion devices. Sub-model assignment is formulated as a multiple-choice knapsack problem, where computational cost is directly controlled through the fraction of the domain assigned to the FRC sub-model. The extended PEC formulation is applied to the simulation of a realistic rich-quench-lean gas turbine combustor at steady-state conditions, as well as transient operation resulting in lean blow-out (LBO). Analysis of transient simulations during LBO demonstrates the extended PEC formulation’s capacity to dynamically adapt to changing conditions within the combustor. Transient combustor dynamics are shown to approach convergence with limited increases in computational cost, while retaining substantial computational cost reduction compared to monolithic FRC simulations. Through PEC simulations with increasing fractions of the domain assigned to FRC, monolithic flamelet simulations are shown to over-predict flame stability during LBO. Finally, the extended PEC formulation is thus shown to overcome deficiencies of monolithic models by controlling modeling error for multiphase combustion modeling.

33 ADVANCED PROPULSION SYSTEMS↗
NASA NTRS2019

Importance of Tree- and Species-Level Interactions With Wildfire, Climate, and Soils in Interior Alaska: Implications for Forest Change Under A Warming Climate

The boreal zone of Alaska is dominated by interactions between disturbances, vegetation, and soils. These interactions are likely to change in the future through increasing permafrost thaw, more frequent and intense wildfires, and vegetation change from drought and competition. We utilize an individual tree-based vegetation model, the University of Virginia Forest Model Enhanced (UVAFME), to estimate current and future forest conditions across sites within interior Alaska. We updated UVAFME for application within interior Alaska, including improved simulation of permafrost dynamics, litter decay, nutrient dynamics, fire mortality, and post-fire regrowth. Following these updates, UVAFME output on species-specific biomass and stem density was comparable to inventory measurements at various forest types within interior Alaska. We then simulated forest response to climate change at specific inventory locations and across the Tanana Valley River Basin on a 2 × 2 km2 grid. We derived projected temperature and precipitation from a five-model average taken from the CMIP5 archive under the RCP 4.5 and 8.5 scenarios. Results suggest that climate change and the concomitant impacts on wildfire and permafrost dynamics will result in overall decreases in biomass (particularly for spruce (Picea spp.)) within the interior Tanana Valley, despite increases in quaking aspen (Populus tremuloides) biomass, and a resulting shift towards higher deciduous fraction. Simulation results also predict increases in biomass at cold, wet locations and at high elevations, and decreases in biomass in dry locations, under both moderate (RCP 4.5) and extreme (RCP 8.5) climate change scenarios. These simulations demonstrate that a highly detailed, species interactive model can be used across a large region within Alaska to investigate interactions between vegetation, climate, wildfire, and permafrost. The vegetation changes predicted here have the capacity to feed back to broader scale climate-forest interactions in the North American boreal forest, a region which contributes significantly to the global carbon and energy budgets.

forest modeling↗
NASA NTRS2000

Nondestructive Characterization Techniques Used for Ceramic Matrix Composite Life Determination

Recent results indicate that the specific damping capacity and resonant frequency measurements taken periodically during a component's lifetime is able to quantify the mechanical fatigue of CMCS. This gives hope for the potential of determining the actual and residual life of CMC materials using a combination of nondestructive techniques. If successful, then this new paradigm for life prediction of CMCs could revolutionize the approach for designing and servicing CMC components, thereby significantly reducing costs for design, development, health monitoring, and maintenance of CMC components and systems. The Nondestructive Characterization (NDC) life prediction approach would complement life prediction using micromechanics and continuum finite element models. This paper reports on the initial concept of NDC life prediction, a review of the C/SiC blisk damping data, and how changes in the specific damping capacity & ultrasonic elastic modulus data have established the concept as a possibility.

Effinger, Michael↗
DOE OSTI2021

2020 Cost Analysis of Hydropower Options at Non-Powered Dams

This report provides a cost analysis of potential hydropower development for representative non-powered dam (NPD) sites in the United States. The overarching objective is to support the establishment of a basis for evaluating progress towards improving the competitiveness of new hydropower development for electricity generation. The representative sites, herein referred to as “reference sites”, were selected from sites with detailed water resource data to support the cost analysis. Facility designs, capital costs, plant generation and efficiency profiles, capacity factors, and levelized costs of energy (LCOE) are presented for the sites under baseline and near-term innovation cases. The baseline case represents facility configurations using technologies that are already widely applied in the hydropower industry, whereas near-term innovations are technologies likely to reach wide acceptance within the next 5 to 10 years. Cost savings in the near-term relative to the baseline are discussed to illustrate the potential benefits to the hydropower industry from research and development (R&D) and adoption of these innovations. Medium- to long-term innovation options expected from ongoing private and government R&D efforts are also highlighted but are not quantified in this report because of a current lack of complete information on these options. The key findings of the cost analysis in this study imply that near-term innovations could reduce the baseline costs of hydropower development at US NPD sites. Thus, if remaining R&D issues with these near-term innovations can be resolved within the next 5 to 10 years, industry-wide adoption of these technologies and improved competitiveness of NPD hydropower development can be expected. Specific key findings of the analysis include the following: 1) Potential installed capacity at the NPD sites evaluated in this study vary from 200 kW to 70 MW, representing two orders of magnitude variation across nearly 20 sites; 2) Capital costs, not including development costs, for the sites evaluated in this study vary from $2,200/kW to $34,000/kW but are below $12,000/kW for most sites; 3) Baseline LCOE estimates for lake dams are from $79/MWh to $790/MWh with most sites under $400/MWh, whereas estimates for lock dams are from $134/MWh to $289/MWh with most sites under $200/MWh; 4) Reductions in capital cost per kilowatt under the near-term innovation case are from −77% to −14% for lake dams and −21% to −2.1% for lock dams (excluding one site with a 14% increase in per-kilowatt capital costs); 5) Combined changes in capital costs and capacity factors in the near-term case relative to the baseline lead to reductions in LCOE of −71% to −14% for lake dams and −21% to −14% for lock dams; 6) Overall, LCOE reductions lead to 8 of the 18 sites under the near-term case having LCOE values below $150/MWh compared with only 2 of 18 sites in the baseline case.

13 HYDRO ENERGY↗
DOE OSTI2023

Techno-Economic Assessment of Residential Heat Pump Integrated with Thermal Energy Storage

Phase change material (PCM)-based thermal energy storage (TES) can provide energy and cost savings and peak demand reduction benefits for grid-interactive residential buildings. Researchers established that these benefits vary greatly depending on the PCM phase change temperature (PCT), total TES storage capacity, system configuration and location and climate of the building. In this study, preliminary techno-economic performance is reported for a novel heat pump (HP)-integrated TES system using an idealized approach. A simplified HP-TES was modeled for 1 year of space heating and cooling loads for a residential building in three different climates in the United States. The vapor compression system of the HP was modified to integrate with TES, and all heat transfer to and from the TES was mediated by the HP. A single PCM was used for heating and cooling, and the PCT and TES capacity were varied to observe their effects on the building’s energy consumption, peak load shifting and cost savings. The maximum reduction in electric consumption, utility cost and peak electric demand were achieved at a PCT of 30 °C for New York City and 20 °C for Houston and Birmingham. Peak energy consumption in Houston, New York City, and Birmingham was reduced by 47%, 53%, and 70%, respectively, by shifting peak load using a time-of-use utility schedule. TES with 170 MJ storage capacity allowed for maximum demand shift from on-peak to off-peak hours, with diminishing returns once the TES capacity equaled the daily building thermal loads experienced during the most extreme ambient conditions.

25 ENERGY STORAGE↗
DOE OSTI2021

Climate Change Mitigation Potential of Wind Energy

Global wind resources greatly exceed current electricity demand and the levelized cost of energy from wind turbines has shown precipitous declines. Accordingly, the installed capacity of wind turbines grew at an annualized rate of about 14% during the last two decades and wind turbines now provide ~6–7% of the global electricity supply. This renewable electricity generation source is thus already playing a role in reducing greenhouse gas emissions from the energy sector. Here we document trends within the industry, examine projections of future installed capacity increases and compute the associated climate change mitigation potential at the global and regional levels. Key countries (the USA, UK and China) and regions (e.g., EU27) have developed ambitious plans to expand wind energy penetration as core aspects of their net-zero emissions strategies. The projected climate change mitigation from wind energy by 2100 ranges from 0.3–0.8 °C depending on the precise socio-economic pathway and wind energy expansion scenario followed. The rapid expansion of annual increments to wind energy installed capacity by approximately two times current rates can greatly delay the passing of the 2 °C warming threshold relative to pre-industrial levels. To achieve the required expansion of this cost-effective, low-carbon energy source, there is a need for electrification of the energy system and for expansion of manufacturing and installation capacity.

17 WIND ENERGY↗
DOE OSTI2024

Mercury Detection Utilizing an Aquatic Animal as a Remote-Sensing Platform

Mercury species in open water, especially the accumulated methylmercury ion, pose a threat to fish and environment. Therefore, it is important to develop a small sensor package that can be integrated into a biotelemetry sensor carried by an aquatic animal, enhancing the ability to detect mercury contamination in large water areas. A quartz crystal microbalance (QCM) sensor using metal-organic framework (MOF) as sensing material was developed to detect mercury and methylmercury ions in real time based on acoustic wave perturbation. Thiol groups were introduced into the MOF UiO-66 through the organic linker to prepare the UiO-66-SH which was confirmed by infrared spectroscopy results. Batch adsorption experiments were conducted for the Hg 2+ , CH 3 Hg + , and Ca 2+ ions adsorption in the UiO-66-SH. The adsorption capacities of the mercury ions were more than an order of magnitude higher than those of the competing Ca 2+ ions at the same concentration. The frequency changes of the QCM sensor with the UiO-66-SH sensing film were an order of magnitude higher than those of the controlled baseline QCM sensor without a sensing film. Additionally, the frequency change can be tailored by adjusting the thickness of the MOF film and the adsorption properties of the sensing material. The sensor frequency change correlates well with ion adsorption capacities.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Probing Sources of Capacity Fade in LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622): An Operando XRD Study of Li/NMC622 Batteries during Extended Cycling

LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622) is one of the most promising Li-ion battery cathodes as it delivers high capacity at high potentials. However high potentials also lead to decreases in capacity retention where the disintegration of the secondary particles has been implicated as a major driving force of this capacity fade. This has been attributed to anisotropic lattice changes and increased microstrain during cycling. To probe how these factors affect capacity fade, Li/NMC622 batteries were cycled from 3-4.3 or 4.7 V and probed with operando X-ray diffraction over the 1st, 2nd, and 101st cycles. Further characterization with scanning electron microscopy, and inductively coupled plasmaoptical emission spectroscopy was also performed. The use of operando XRD over many cycles allowed for the collection of detailed structural information in real time over a time frame in which fading can be observed. During the first two cycles, the cells charged to 4.7 V exhibit increased anisotropic lattice changes as compared to the cells charged to 4.3 V. Upon the 101st cycle, when significant fade has been observed, the cells charged to 4.3 and 4.7 V show identical lattice changes to one another, while the 4.7 V charge limit induces more microstrain. This shows that elevated microstrain at high charge limits is a major driver for particle disintegration in NMC622 cathodes. This study provides important insights into the mechanisms of particle disintegration and capacity fade in NMC/Li-ion batteries, which will enable the design of NMC electrodes that deliver both higher capacities and exhibit better capacity retention.

25 ENERGY STORAGE↗
NASA NTRS2020

Indicators and Monitoring Systems for Urban Climate Resiliency

Cities in the USA and around the world have begun to take an active role in responding to climate change. A central requirement for effective urban climate strategies is the capacity to understand and measure how the climate is changing, the physical, environmental, and social impacts of the changes, and whether adaptation and resiliency policies and programs put in place in response are working. The objective of this paper is to review and assess how urban climate change and resiliency efforts can be measured and to define what might serve as meaningful indicator and monitoring protocols. The New York City Panel on Climate Change (NPCC) is used as a case study along with a reviews of the emerging literature of urban climate change indicators to analyze the requirements and processes needed for a successful urban climate resiliency indicator and monitoring (I and M) system. In the paper, the basic requirements of a proposed Urban Climate Resilience Indicators and Monitoring System are presented. A specific illustration of an I and M system for tracking the urban heat island highlights challenges as well as potential solutions embedded within such systems. Discussions how these protocols can be translated to other locales and settings, as well as the relationship to the US National Climate Assessment indicator process, are presented.

New York City Panel on Climate Change↗
DOE OSTI2023

Highly swollen ROMP-based gels

In this study, the leakage of organic solvent during the transportation and storage is one of the major threats to the environment. Networks/gels acting as the absorbing materials for organic solvents are the most promising solution for the organic solvent pollution. Here, we report the synthesis of highly swollen networks/gels in high yield (≥95%) via ring opening metathesis polymerization (ROMP) using Grubbs’ first generation catalyst/initiator (G1), a crosslinker (1,1'-(methylenedi-4,1-phenylene)bis-exo-7-oxanorbornenecarboximide) and monofunctional monomer/diluent (exo-N-phenyl-7-oxanorbornenecarboximide). The mesh size of the network was varied by keeping the concentration of monomer constant while changing the concentrations of crosslinker and G1 (initiator). The swelling capacity of the network in N,N-dimethylformamide (DMF) solvent increased from 41 to 53 and to 61 with the increase of theoretical mesh size (molar ratio of monomer to crosslinker) from 20 to 40 and to 60, respectively. By further increasing the mesh size from 60 to 80 there was no significant change in swelling capacities (63). Thus, the gel with the mesh size of 60 was selected for swelling capacity analysis in other polar organic solvents such as dimethyl sulfoxide (DMSO), dichloromethane (DCM), chloroform and lithium-ion battery electrolyte solution (1.0 M LiPF 6 in ethylene carbonate (EC)/diethyl carbonate (DEC) = 50/50 (v/v)). They showed the decreased swelling capacity value from 61 to 57, 40, 31 and 5, respectively. For a controlled mesh size ROMP-based gel, we observed the highest swelling capacity values to date.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Scalability analysis of heavy-duty gas turbines using data-driven machine learning

With the increasing integration of variable renewable energy sources into power systems, the role of flexible power generation technologies like gas turbines (GT) in rapid grid balancing remains crucial. This sustained importance underscores the need for scaled and precise modeling of GT to ensure effective integration within evolving energy frameworks. While physics-driven GT models integrate thermodynamics, fluid dynamics, and combustion principles, they often rely on approximate mathematical representations to accommodate scaling that may not capture the actual complex dynamics for GTs and inertial effects associated to GTs with different ratings. In this study, a data-driven model is proposed using machine learning (ML) techniques to conduct GT scalability analysis and performance evaluation with high accuracy. The ML model, trained on data from various operating conditions and performance parameters, aims to uncover intricate relationships and patterns, resembling GT characteristics at different scales (ratings). The model is developed to capture complex system interaction and to adapt to changing operational scenarios at different capacities, providing valuable insights of power system dynamics. In this study, the real-time digital simulator platform was employed to generate training data for the ML model and assess its dynamic characteristics. The ultimate objective was to develop a detailed modeling framework based on governing equations and data-driven ML capable of predicting key performance indicators, in thermal systems such as GTs, including power output, speed, fuel consumption, and exhaust temperature under diverse operating conditions at different scales. The developed ML framework demonstrated high accuracy, with mean relative errors for GT power prediction, reference speed, exhaust temperature, and compressor pressure ratio (CPR) parameters consistently below 0.1% across typical load fluctuation scenarios. Maximum deviations were limited to approximately 0.5 K for exhaust temperature and 0.009 for CPR, underscoring the model’s ability to replicating dynamic GT behavior with high precision. The adaptability of the ML model enables its application across diverse operational conditions and its extension to other thermal systems. By leveraging advanced ML techniques, this study presents a robust and scalable modeling framework that enhances GT simulation precision, facilitating improved integration into evolving power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Mechanistic insights into sulfate and phosphate-mediated hexavalent chromium removal by tea polyphenols wrapped nano-zero-valent iron

Nano zero-valent iron via green synthesis (g-nZVI) has great potential in removing toxic hexavalent Cr(VI) from industrial wastewater. Sulfate and phosphate in wastewater can influence Cr(VI) removal by g-nZVI. Here, in this study, the Cr(VI) removal kinetics by different g-nZVI materials were investigated with the existence of sulfate and/or phosphate, and the corresponding mechanisms were first revealed using multiple characterizations, including X-ray absorption near-edge spectra (XANES) and X-ray photoelectron spectroscopy (XPS). The results showed that Cr(OH) 3 was the dominant species initially formed on the surface of g-nZVI particles before transforming to Cr 2 O 3 during the reaction of g-nZVI with Cr(VI). Sulfate in wastewater can promote the reduction from Cr(VI) to Cr(OH) 3 by g-nZVI, because sulfate triggers the release of Fe(II) and tea polyphenols (from tea extracts) from the g-nZVI surface due to the corrosion of Fe 0 core, which is in line with an obvious increase in pseudo-second-order rate constant (k 2 ) and subtle change in Cr(VI) removal capacity (q e ). However, phosphate impedes the g-nZVI corrosion and inhibits q e because of the inner-sphere complexation of phosphate onto g-nZVI decreasing the released Fe(II) for Cr 2 O 3 production. When sulfate and phosphate coexisted in contaminated water, the inhibition effect of phosphate in Cr(VI) removal by g-nZVI was stronger than the promotion of sulfate. Accordingly, q e value of g-nZVI declined from 93.4 mg g –1 to 77.5 mg g –1 , while k 2 remained constant as the molar ratio of phosphate/sulfate increased from 0.1 to 10 in water. This study provides new insights into applying g-nZVI in efficient Cr(VI) removal from contaminated water with enrichment of sulphates and phosphates.

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

Parametric analysis on optimized design of hybrid solar power plants

There is increasing interest in utility-scale solar power plants with storage which can flexibly dispatch renewable energy to the grid. However, plant design possesses many degrees of freedom and non-obvious trade-offs in performance. Software tools can estimate or optimize the performance of a specific plant configuration under market and weather conditions of interest; the associated cost parameters and operating assumptions strongly influence estimates of plant performance and decisions regarding optimal sizing. We employ the National Renewable Energy Laboratory's Hybrid Optimization and Performance Platform, which incorporates optimal dispatch when evaluating plant performance, and investigate the sensitivity to weather and market conditions, operating limitations, and the presence of a capacity-based incentive. We demonstrate changes in plant performance and optimal sizing with respect to these inputs and discuss implications. Here results show that PV-with-battery designs are more profitable under our assumptions, but that designs including a concentrated solar power (CSP) system produce significantly greater annual energy; and that CSP-with-thermal energy storage designs maximizing the benefit-to-cost ratio have an input-dependent linear relationship between the CSP field solar multiple and the hours of storage as the project budget varies.

14 SOLAR ENERGY↗