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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Automated Generation of Microkinetics for Heterogeneously Catalyzed Reactions Considering Correlated Uncertainties**

Abstract The study presents an ab‐initio based framework for the automated construction of microkinetic mechanisms considering correlated uncertainties in all energetic parameters and estimation routines. 2000 unique microkinetic models were generated within the uncertainty space of the BEEF‐vdW functional for the oxidation reactions of representative exhaust gas emissions from stoichiometric combustion engines over Pt(111) and compared to experiments through multiscale modeling. The ensemble of simulations stresses the importance of considering uncertainties. Within this set of first‐principles‐based models, it is possible to identify a microkinetic mechanism that agrees with experimental data. This mechanism can be traced back to a single exchange‐correlation functional, and it suggests that Pt(111) could be the active site for the oxidation of light hydrocarbons. The study provides a universal framework for the automated construction of reaction mechanisms with correlated uncertainty quantification, enabling a DFT‐constrained microkinetic model optimization for other heterogeneously catalyzed systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

New prospects for PV powered water desalination plants: case studies in Saudi Arabia: New prospects for PV powered water desalination plants

Increased water demand and increased drought episodes in the Middle East and other regions necessitate an expansion in desalination projects and create a great market opportunity for photovoltaics (PV). PV-powered desalination has previously been regarded as not being a cost-competitive solution when compared with conventionally powered desalination; however, the decline in PV costs over the last few years has changed this outlook. Here, this article presents up-to-date performance and cost analysis of reverse osmosis (RO) desalination powered with PV connected to the Saudi Arabian grid. Reference cases include relatively small (i.e., producing 6550 m 3 water per day) and large (i.e., 190 000 m 3 /day) desalination plants using seawater at a salinity of 40 000 ppm. We used data from a King Abdullah University for Science and Technology presentation and Hybrid Optimization Model for Electric Renewables 2.81 Energy Modeling Software (HOMER Energy LLC) in tandem with Desalination Economic Evaluation Program 4.0 (International Atomic Energy Agency) desalination software to analyze the techno-economic feasibility of these plants. The first phase of our work entailed a comparison between dual-axis high concentration PV (CPV) equipped with triple junction III/V solar cells and CdTe PV-powered RO systems. The estimated levelized cost of electricity from CPV is 0.16/kWh dollars, whereas that from CdTe PV is $0.10/kWh dollars and 0.09/kWh dollars for fixed-tilt and one-axis tracking systems, respectively. These costs are higher than the price of diesel-based grid electricity in the region because diesel fuel is heavily subsidized in Saudi Arabia.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

A TTL-based Approach for Content Placement in Edge Networks

Edge networks are promising to provide better services to users by provisioning computing and storage resources at the edge of networks. However, due to the uncertainty and diversity of user interests, content popularity, distributed network structure, cache sizes, it is challenging to decide where to place the content, and how long it should be cached. In this paper, we study the utility optimization of content placement at edge networks through timer-based (TTL) policies. We propose provably optimal distributed algorithms that operate at each network cache to maximize the overall network utility. Our TTL-based optimization model provides theoretical answers to how long each content must be cached, and where it should be placed in the edge network. Extensive evaluations show that our algorithm significantly outperforms path replication with conventional caching algorithms over some network topologies.

Panigrahy, Nitish K.↗
DOE OSTI2017

Morse-Smale Analysis of Ion Diffusion in Ab Initio Battery Materials Simulations

Ab initio molecular dynamics (AIMD) simulations are increasingly useful in modeling, optimizing and synthesizing materials in energy sciences. In solving Schrödinger’s equation, they generate the electronic structure of the simulated atoms as a scalar field. However, methods for analyzing these volume data are not yet common in molecular visualization. The Morse-Smale complex is a proven, versatile tool for topological analysis of scalar fields. In this paper, we apply the discrete Morse-Smale complex to analysis of first-principles battery materials simulations. We consider a carbon nanosphere structure used in battery materials research, and employ Morse-Smale decomposition to determine the possible lithium ion diffusion paths within that structure. Our approach is novel in that it uses the wavefunction itself as opposed distance fields, and that we analyze the 1-skeleton of the Morse-Smale complex to reconstruct our diffusion paths. Furthermore, it is the first application where specific motifs in the graph structure of the complete 1-skeleton define features, namely carbon rings with specific valence. We compare our analysis of DFT data with that of a distance field approximation, and discuss implications on larger classical molecular dynamics simulations.

25 ENERGY STORAGE↗
DOE OSTI2020

Tighter reformulations using classical Dawson and Sankoff bounds for approximating two-stage chance-constrained programs

We extend and improve recent results given by Singh and Watson on using classical bounds on the union of sets in a chance-constrained optimization problem. Specifically, we revisit the so-called Dawson and Sankoff bound that provided one of the best approximations of a chance constraint in the previous analysis. Next, we show that our work is a generalization of the previous work, and in fact the inequality employed previously is a very relaxed approximation with assumptions that do not generally hold. Computational results demonstrate on average over a 43% improvement in the bounds. As a byproduct, we provide an exact reformulation of the floor function in optimization models.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

The value of concentrating solar power in ancillary services markets

Ancillary services, such as spinning reserves, can provide grid reliability and contribute to profitability of an energy resource. We exercise an existing dispatch optimization model to estimate the profitability of a concentrating solar power plant by incorporating the sale of spinning reserves in the ancillary service market using the National Renewable Energy Laboratory's System Advisor Model to simulate operations within a 72-h rolling horizon framework. Assuming a price-taker approach with day-ahead energy and spinning reserve prices from both the California Independent System Operator and the Electricity Reliability Council of Texas, we find that selling spinning reserves in addition to electric energy increases plant profitability by up to 7% with perfect knowledge of day-ahead pricing and solar resource availability. Here, this finding suggests that spinning reserve markets provide significant value streams to concentrating solar power plants that can leverage thermal energy storage to offer reliable production in the short-to-medium term.

14 SOLAR ENERGY↗
DOE OSTI2023

Quantifying agricultural productive use of energy load in Sub-Saharan Africa and its impact on microgrid configurations and costs

The use of advanced energy technologies for agricultural purposes—such as irrigation, refrigeration, crop processing, and egg incubation—has the potential to increase crop yield, reduce vulnerability to changing precipitation patterns, increase shelf life, strengthen income and employment opportunities in rural areas, and reduce emissions by displacing fossil fuel-based technologies. These productive uses of energy (PUE) in remote areas could potentially be powered by microgrids that additionally serve otherwise unelectrified communities, most of which are located in rural Sub-Saharan Africa. Here, in this paper, we use high-resolution geospatial data to estimate the end-use electricity demand for a range of agricultural PUE across Sub-Saharan Africa, and we share these data in an open-access mapping tool. Next, we use REopt®, a techno-economic optimization model of energy systems, to determine the cost and system sizing implications of incorporating agricultural PUE into microgrid designs in Kenya and Zambia. We estimate the upper bound of agricultural PUE demand for irrigation, milling, shelling, refrigeration, and egg incubation across Sub-Saharan to be 16.8 TWh/yr. We find that incorporating local agricultural PUE into microgrid system designs increases the required system sizing while having minimal impact on the levelized cost of energy of these systems. Our analysis is the first to demonstrate the PUE potential in the agricultural sector at a 10x10-kilometer resolution across Sub-Saharan Africa and to show, at scale, how site-specific PUE can impact the cost and sizing of microgrids that are otherwise deployed to serve local household and community load.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Evaluating advanced nuclear fission technologies for future decarbonized power grids

Advanced nuclear fission, which encompasses various innovative nuclear reactor designs, could contribute to the decarbonization of the United States electricity sector. However, little is known about how cost-competitive these reactors would be compared to other technologies, or about which aspects of their designs offer the most value to a decarbonized power grid. We employ an electricity system optimization model and a case study of a decarbonized U.S. Eastern Interconnection circa 2050 to generate initial indicators of future economic value for advanced reactors and the sensitivity of future value to various design parameters, the availability of competing technologies, and the underlying policy environment. These results can inform long-term cost targets and guide near-term innovation priorities, investments, and reactor design decisions. We find that advanced reactors should cost $\$5.7$–$\$7.3$/W to gain an initial market share (assuming 30 year asset life and 3.5 %–6.5 % real weighted average cost of capital), while those that include thermal storage in their designs can cost up to $\$6.0$/W–$\$7.7$/W (not including cost of storage). Since the marginal value of advanced fission reactors declines as market penetration increases, break-even costs fall ~32 % at 100 GW of cumulative capacity and ~51 % at 300 GW. Additionally, policies that provide investment tax credits for nuclear energy create the most favorable environment for advanced nuclear fission. In conclusion, these findings can inform near-term resource allocation decisions by stakeholders, innovators and investors working in the energy technology sector.

Capacity expansion↗
DOE OSTI2026

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↗
DOE OSTI2019

The long-term impacts of carbon and variable renewable energy policies on electricity markets

We present a computationally-efficient optimization model that finds the least-cost generation unit expansion, commitment, and dispatch plan to serve hourly electricity demand and ancillary service requirements. We apply the model to a case study based on data from the electricity market in Texas (ERCOT) to analyze the market and investment impacts of several incentive mechanisms that support variable renewable energy (VRE) investments and carbon emission reductions. In contrast to many previous studies, the model determines least-cost VRE investments under different cost and incentive assumptions rather than analyzing scenarios where VRE expansion is pre-determined. We find that electricity prices can vary significantly under different incentive mechanisms, even when comparable generation portfolios result. Therefore, the preferred incentive mechanism depends on stakeholder objectives as well as the prevailing electricity market framework. Our results indicate that a carbon tax is more system cost-efficient for reducing emissions, while production and investment tax credits are more system cost-efficient for increasing VRE investments. Similarly, incentive mechanisms that reduce electricity prices may increase the need for separate revenue sufficiency mechanisms (e.g. a capacity market) more than a policy that increases electricity prices. Moreover, the impacts on consumer payments are not always aligned with changes in system costs. Overall, the analysis illustrates the importance of considering electricity market impacts in assessing the economic efficiency of VRE and carbon incentive mechanisms.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Designing robust energy policy packages under deep uncertainty: A multi-metric decision support framework

The complexity of transitioning to sustainable energy systems requires policy frameworks capable of balancing multiple objectives while addressing deep uncertainty. However, existing approaches often lack systematic methods to identify combinations of policy levers that remain effective across a wide range of uncertain futures. This paper presents a novel decision support framework that guides the selection of robust policy packages based on their performance across multiple objectives under uncertainty. Our method leverages a large ensemble of scenarios and applies scenario discovery techniques to identify influential policy levers. Here, we introduce new indicators to assess the robustness of policies by evaluating their ability to mitigate adverse outcomes across metrics. These indicators support an iterative process to build a robust policy package. Finally, we map the technological and energy pathways associated with the robust policy package by leveraging an energy system optimization model. We illustrate the application of this framework to the Spanish energy system, providing insights into how specific combinations of policy levers shape decarbonization pathways under uncertainty.

Decision-support method↗
DOE OSTI2017

Artificial neural network based predictions of cetane number for furanic biofuel additives

The next generation of alternative fuels is being explored through advanced chemical and biological production techniques for the purpose of finding suitable replacements for diesel and gasoline while lowering production costs and increasing process yields. Chemical conversion of biomass to fuels offers a plethora of pathways with a variety of fuel molecules, both novel and traditional, which may be targeted. In the search for new fuels, an initial, intuition-driven evaluation of fuel compounds with desired properties is required. Due to the high cost and significant production time needed to synthesize these materials at a scale sufficient for exhaustive testing, a predictive model would allow chemists to preemptively screen fuel properties of potentially desirable fuel candidates. Current work has shown that predictive models, in this case artificial neural networks (ANN's) analyzing quantitative structure property relationships (QSPR's), can predict the cetane number (CN) of a proposed fuel molecule with relatively small error. A fuel's CN is a measure of its ignition quality, typically defined using prescribed ASTM standards and a cetane testing engine. Alternatively, the analogous derived cetane number (DCN), obtained using an Ignition Quality Tester (IQT), is a direct measurement alternative to the CN that uses an empirical inverse relationship to the ignition delay found in the constant volume combustion chamber apparatus. DCN data points acquired using an IQT were utilized for model validation and expansion of the experimental database used in this study. The present report improves on an existing model by optimizing the model architecture along with the key learning variables of the ANN and by making the model more generalizable to a wider variety of fuel candidate types, specifically the class of furans and furan derivatives, by including specific molecules for the model to incorporate. The new molecules considered include tetrahydrofuran, 2-methylfuran, 2-methyltetrahydrofuran, 5,5'-(furan-2-ylmethylene)bis(2-methylfuran), 5,5'-((tetrahydrofuran-2-yl)methylene)bis(2-methyltetrahydrofuran), tris(5-methylfuran-2-yl)methane, and tris(5-methyltetrahydrofuran-2-yl)methane. Model architecture adjustments improved the overall root-mean-square error (RMSE) of the base database predictions by 5.54%. Additionally, through the targeted database expansion, it is shown that the predicted cetane number of the furan-based molecules improves on average by 49.21% (3.74 CN units) and significantly for a few of the individual molecules. This indicates that a selected subset of representative molecules can be used to extend the model's predictive accuracy to new molecular classes. The approach, bolstered by the improvements presented in this paper, enables chemists to focus on promising molecules by eliminating less favorable candidates in relation to their ignition quality.

09 BIOMASS FUELS↗
DOE OSTI2024

New opportunities in produced water management: A market-based approach to produced water trading

Produced water (PW) is a byproduct of oil and gas (O&G) production. Obtained alongside the more valuable energy products, PW is usually characterized by high levels of salinity and often contains many contaminants (chemicals, soluble and insoluble oil, organics, etc.) making it unsuitable for release without substantial treatment. Couple this with the fact that PW is typically obtained at multiple times the rate of oil or gas, and the added transport, treatment, and disposal costs become a serious challenge for operators. These realities have led to ad-hoc practices including cooperation between industry competitors to recycle, share, or otherwise mitigate PW costs. The National Energy Technology Laboratory (NETL) in partnership with the Ground Water Protection Council (GWPC) is pursuing novel technology solutions to address PW issues that complement or improve ad-hoc practices adopted by operators. In this paper, we observe that well-established market management practices used in electrical power generation have natural analogues in the PW supply chain. These parallels open up a new line of research where we view PW management as a market equilibrium problem, and explore solutions that foster active and data-based collaboration among operators through market structures similar to power markets, with the ultimate objective of improving PW management costs and recycling rates. Here, we make a case for our observations, present a PW market clearing optimization model that shows how such a market system could operate in the O&G space, and provide an illustrative case study for demonstration.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

A scalable planning framework of energy storage systems under frequency dynamics constraints

As the penetration of renewables increases in power systems, the declining system inertia can cause frequency stability issues. Battery energy storage systems (BESSs) respond fast and therefore can relieve the low inertia difficulty but need to be appropriately sized considering the associated cost. This paper presents a novel stochastic optimization model for economically planning BESS capacity while considering the spatial–temporal correlation of wind generation and generator outages under frequency stability constraints, which include the rate-of-change of frequency (RoCoF), frequency nadir (FN), and quasi-steady-state (QSS) frequency. A set of new FN constraints that can be easily linearized is developed. To account for renewable uncertainties, a realistic uncertainty modeling approach, Random Field, is adopted to generate wind generation scenarios by considering both spatial and temporal evolutions of wind speed profiles. The ESS sizing is formulated as a mixed-integer linear programming problem and solved by using a scalable decomposition-and-coordination approach, Surrogate Absolute Value Lagrangian Relaxation (SAVLR). To further improve the scalability and reduce computational burdens, a rolling-horizon-based update is developed and incorporated into SAVLR for providing a practical solution to the long-term planning of very large-scale power systems. Finally, a modified IEEE 118-bus system and the Polish system are used to validate the effectiveness and scalability of the model and solution methodology.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

The geospatial and economic viability of CO 2 storage in hydrocarbon depleted fractured shale formations

Hydrocarbon depleted fractured shale (HDFS) formations could be attractive for geologic carbon dioxide (CO 2 ) storage. Shale formations may be able to leverage existing infrastructure, have larger capacities, and be more secure than saline aquifers. We compared regional storage capacities and integrated CO 2 capture, transport, and storage systems that use HDFS with those that use saline aquifers in a region of the United States with extensive shale development that overlies prospective saline aquifers. We estimated HDFS storage capacities with a production-based method and costs by adapting methods developed for saline aquifers and found that HDFS formations in this region might be able to store with less cost an estimated ~14× more CO 2 on average than saline aquifers at the same location. The potential for smaller Areas of Review and less investment in infrastructure accounted for up to 84% of the difference in estimated storage costs. We implemented an engineering-economic geospatial optimization model to determine and compare the viability of storage capacity for these two storage resources. Across the state-specific and regional scenarios we investigated, our results for this region suggest that integrated CCS systems using HDFS could be more centralized, require less pipelines, prioritize different routes for trunklines, and be 6.4–6.8% ($5-10/tCO 2 ) cheaper than systems using saline aquifers. In conclusion, overall, CO 2 storage in HDFS could be technically and economically attractive and may lower barriers to large scale CO 2 storage if they can be permitted.

42 ENGINEERING↗
DOE OSTI2014

Alpha/Beta Ratio for Normal Lung Tissue as Estimated From Lung Cancer Patients Treated With Stereotactic Body and Conventionally Fractionated Radiation Therapy

Purpose: To estimate the α/β ratio for which the dose-dependent lung perfusion reductions for stereotactic body radiation therapy (SBRT) and conventionally fractionated radiation therapy (CFRT) are biologically equivalent. Methods and Materials: The relations between local dose and perfusion reduction 4 months after treatment in lung cancer patients treated with SBRT and CFRT were scaled according to the linear-quadratic model using α/β ratios from 0 Gy to ∞ Gy. To test for which α/β ratio both treatments have equal biological effect, a 5-parameter logistic model was optimized for both dose–effect relationships simultaneously. Beside the α/β ratio, the other 4 parameters were d{sub 50}, the steepness parameter k, and 2 parameters (M{sub SBRT} and M{sub CFRT}) representing the maximal perfusion reduction at high doses for SBRT and CFRT, respectively. Results: The optimal fitted model resulted in an α/β ratio of 1.3 Gy (0.5-2.1 Gy), M{sub SBRT} = 42.6% (40.4%-44.9%), M{sub CFRT} = 66.9% (61.6%-72.1%), d{sub 50} = 35.4 Gy (31.5-9.2 Gy), and k = 2.0 (1.7-2.3). Conclusions: An equal reduction of lung perfusion in lung cancer was observed in SBRT and CFRT if local doses were converted by the linear-quadratic model with an α/β ratio equal to 1.3 Gy (0.5-2.1 Gy)

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2017

Life cycle assessment and life cycle costs for pre-disaster waste management systems

Highlights: • Disaster waste management should include disaster waste response. • Environmental and economic disaster waste management system must be constructed. • Temporary incinerators have environmental and economic disadvantages. • Regional air pollution reduction is vital in disaster waste management planning. - Abstract: This study develops a method of environmental and economic evaluation of an integrated disaster waste management system that considers the spatial scale of removal, transport, and treatment of disaster waste. A case study was conducted on combustibles, which is a type of disaster waste derived from dwellings, in Mie Prefecture, Japan. First, we calculated the quantity and the spatial distribution of disaster waste derived from dwellings and tsunami debris produced as a result of a large-scale earthquake. The quantity of disaster waste was estimated as 7,178,000 t with functioning flood-preventing facilities and 11,956,000 t without functioning flood prevention facilities. Ensuring resilience in the face of earthquakes and tsunamis by renovating flood-preventing facilities is extremely important in decreasing the production of wastes, especially in coastal regions. Next, the transportation network for transporting combustibles in disaster waste to temporary storage sites, incineration plants, and landfill was constructed using an optimization model. The results showed that if flood-preventing facilities do not function properly, the installation of temporary incineration facilities becomes essential. Life-cycle emissions of CO{sub 2}, SO{sub x}, NO{sub x}, and PM and the costs of removal, storage, and treatment of combustibles were calculated as 258,000 t, 618 t, 1705 t, 7.9 t, and 246 million USD, respectively, in the case of functioning flood-preventing facilities. If flood-preventing facilities do not function, the quantity of environmentally unfriendly emissions and the costs increase. This result suggested the significance of renovation in order to maintain the conditions of flood-preventing facilities to decrease the environmental burden and costs as well as keep the production of disaster waste at a minimum.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Refinery Perspective on Decarbonizing with Marine Biofuels

This work seeks to understand what biofuel production pathways a refinery might prefer to produce very low sulfur fuel oil (VLSFO) for marine applications. A comprehensive refinery optimization model was modified to allow for (1) direct blending of soy biodiesel, renewable diesel, Fischer-Tropsch diesel, and several pyrolysis oils and (2) indirect blending of all pyrolysis oils via co-processing in a fluidized catalytic cracker (FCC) and diesel hydrotreater into the marine fuel pool. Results showed that preferred pathways to bio-VLSFO production included co-processing low-quality pyrolysis oil in a FCC to blend the resulting biogenic light cycle oil, directly blending soy biodiesel, and directly blending small quantities of pyrolysis oil. Bio-VLSFO production costs were compared to those of fossil VLSFO subject to different marine fuel demands, benchmark crude oil prices, and biogenic fractions in the finished product. Given benchmark crude oil prices over 60 $/bbl, bio-VLSFO production appeared to be significantly cheaper than fossil VLSFO. Corresponding marginal abatement costs of CO 2 mostly ranging from -300 to 350 $/ton of CO 2 were also determined using a simplified but novel approach to allow for a comparison to other decarbonization strategies. In conclusion, this work indicates that low-sulfur contents in biofuels, relatively relaxed specifications for marine fuels, and current difficulties in meeting VLSFO specifications with crude oils can combine to make bio-VLSFO production cost-effective. Moreover, marine fuels appear to be a good entry point for refiners to start decarbonizing with biofuel pathways that could eventually be extended to other product pools.

09 BIOMASS FUELS↗