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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 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Maximising the investment returns of a grid‐connected battery considering degradation cost

Energy storage systems (ESSs) are being deployed widely due to numerous benefits including operational flexibility, high ramping capability, and decreasing costs. This study investigates the economic benefits provided by battery ESSs when they are deployed for market‐related applications, considering the battery degradation cost. A comprehensive investment planning framework is presented, which estimates the maximum revenue that the ESS can generate over its lifetime and provides the necessary tools to investors for aiding the decision making process regarding an ESS project. The applications chosen for this study are energy arbitrage and frequency regulation. Lithium‐ion batteries are considered due to their wide popularity arising from high efficiency, high energy density, and declining costs. A new degradation cost model based on energy throughput and cycle count is developed for Lithium‐ion batteries participating in electricity markets. The lifetime revenue of ESS is calculated considering battery degradation and a cost–benefit analysis is performed to provide investors with an estimate of the net present value, return on investment and payback period. The effect of considering the degradation cost on the estimated revenue is also studied. The proposed approach is demonstrated on the IEEE Reliability Test System and historical data from PJM Interconnection.

25 ENERGY STORAGE↗
DOE OSTI2024

Quantifying Capital Cost Reduction Pathways for Advanced Nuclear Reactors

The framework developed in this study is provided both as an excel sheet (https://inl.gov/content/uploads/2023/11/Nuclear-Reactor-Cost-Reduction-Pathway-Spreadsheet-Tool.xlsx) and a Python (Jupyter) Notebook (link: https://github.com/accert-dev/ACCERT/tree/main/Cost%20Reduction). Capital cost considerations are one of the primary inhibitors to the large-scale deployment of nuclear power plants. While it is widely accepted that first units will likely be expensive and relatively uncompetitive, it is reasonable to expect that subsequent units, built in relative quick succession, will be cheaper as they benefit from the so-called “learning effects”. However, the large degree of uncertainty associated with this parameter renders it challenging for first movers to invest in the first few expensive units. To resolve this impasse, the U.S. Department of Energy’s Advanced Nuclear Liftoff study advocated for the formation of large, committed order books of plants of the same technology to spread the costs across several units and kickstart the nuclear supply chain. The study also advocated best practices for avoiding overruns and keeping reactors on budget. This report builds on these key recommendations by attempting to quantify specific pathways toward cost reduction for nuclear energy. A capital cost estimation framework was built to untangle the effect of learning into a subset of key cost drivers, referred to as “levers”. Collectively, the choice of these levers is intended to reflect the decision-making of high-level stakeholders like plant owners and the government. In addition to the size of the firm orderbook, these levers included (a) cost drivers that are most often attributed to cost overruns such as architect/engineering (A/E) proficiency, construction proficiency, procurement service proficiency, design completion prior to the start of construction, and design maturity, and (b) cost reduction strategies such as modular construction, cross-site standardization, safety classification of the reactor building, and of the balance of plant. Two advanced reactor designs were leveraged as use cases and bottom-up cost estimates made with assumptions consistent with a well-executed first-of-a-kind project (WE-FOAK, i.e., almost no overruns) were used as baselines for the models. Cost correlations were surveyed from the literature to determine the impact of important variables on projected timelines and costs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2003

Evaluation of Human vs. Teleoperated Robotic Performance in Field Geology Tasks at a Mars Analog Site

Exploration mission designers and planners have costing models used to assess the affordability of given missions - but very little data exists on the relative science return produced by different ways of exploring a given region. Doing cost-benefit analyses for future missions requires a way to compare the relative field science productivity of spacesuited humans vs. virtual presence/teleoperation from a nearby habitat or orbital station, vs. traditional terrestrial-controlled rover operations. The goal of this study was to define science-return metrics for comparing human and robotic fieldwork, and then obtain quantifiable science-return performance comparisons between teleoperated rovers and spacesuited humans. Test runs with a simulated 2015-class rover and with spacesuited geologists were conducted at Haughton Crater in the Canadian Arctic in July 2002. Early results imply that humans will be 1-2 orders of magnitude more productive per unit time in exploration than future terrestrially-controlled robots.

Glass, B.↗
DOE OSTI2019

An Integrated Techno-economic Modeling Tool for sCO 2 Brayton Cycles

The supercritical CO 2 (sCO 2 ) Brayton Economics Tool (sBET) was developed to evaluate and perform sensitivity studies on recompression closed Brayton cycles (RCBCs). This integrated techno-economic tool calculates key system performance and levelized cost of energy (LCOE) based on user-defined input on key variables such as system size, recuperator effectiveness, turbine inlet temperature, etc. The goal of this integrated tool is to allow system designers to understand the tradeoffs associated with various key design decisions, such as recuperator effectiveness and overall system cost. This work includes a description of LCOE calculation methodology, component system cost models for turbomachinery and heat exchangers based on vendor quotes and published literature, and the results of several parameter studies to identify desirable system parameters.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Optimized Carbon Fiber Composites in Wind Turbine Blade Design

The objective of this study is to assess the commercial viability to develop cost-competitive carbon fiber composites specifically suited for the unique loading experienced by wind turbine blades. The wind industry is a cost-driven market, while carbon fiber materials have been developed for the performance-driven aerospace industry. Carbon fiber has known benefits for reducing wind turbine blade mass due to the significantly improved stiffness, strength, and fatigue resistance per unit mass compared to fiberglass; however, the high relative cost has prohibited broad adoption within the wind industry. Novel carbon fiber materials derived from the textile industry are studied as a potentially more optimal material for the wind industry and are characterized using a validated material cost model and through mechanical testing. The novel heavy tow textile carbon fiber is compared with commercial carbon fiber and fiberglass materials in representative land-based and offshore reference wind turbine models. Some of the advantages of carbon fiber spar caps are observed in reduced blade mass and improved fatigue life. The heavy tow textile carbon fiber is found to have improved cost performance over the baseline carbon fiber and performed similarly to the commercial carbon fiber in wind turbine blade design, but at a significantly reduced cost. This novel carbon fiber was observed to even outperform fiberglass when comparing material cost estimates for spar caps optimized to satisfy the design constraints. This study reveals a route to enable broader carbon fiber usage by the wind industry to enable larger rotors that capture more energy at a lower cost.

17 WIND ENERGY↗
DOE OSTI2016

Economically sustainable scaling of photovoltaics to meet climate targets

To meet climate targets, power generation capacity from photovoltaics (PV) in 2030 will have to be much greater than is predicted from either steady state growth using today's manufacturing capacity or industry roadmaps. Analysis of whether current technology can scale, in an economically sustainable way, to sufficient levels to meet these targets has not yet been undertaken, nor have tools to perform this analysis been presented. Here, we use bottom-up cost modeling to predict cumulative capacity as a function of technological and economic variables. We find that today's technology falls short in two ways: profits are too small relative to upfront factory costs to grow manufacturing capacity rapidly enough to meet climate targets, and costs are too high to generate enough demand to meet climate targets. We show that decreasing the capital intensity (capex) of PV manufacturing to increase manufacturing capacity and effectively reducing cost (e.g., through higher efficiency) to increase demand are the most effective and least risky ways to address these barriers to scale. We also assess the effects of variations in demand due to hard-to-predict factors, like public policy, on the necessary reductions in cost.Lastly, we review examples of redundant technology pathways for crystalline silicon PV to achieve the necessary innovations in capex, performance, and price.

14 SOLAR ENERGY↗
DOE OSTI2018

The Use of Statistically Based Rolling Supply Curves for Electricity Market Analysis: A Preliminary Look

In light of the changing electricity resource mixes across the United States, an important question in electricity modeling is how additions and retirements of generation, including additions in variable renewable energy (VRE) generation could impact markets by changing hourly wholesale energy prices. Instead of using resource-intensive production cost models (PCMs) or building and using simple generator supply curves, this analysis uses a 'top-down' approach based on regression analysis of hourly historical energy and load data to estimate the impact of supply changes on wholesale electricity prices, provided the changes are not so substantial that they fundamentally alter the market and dispatch-order driven behavior of non-retiring units. The rolling supply curve (RSC) method used in this report estimates the shape of the supply curve that fits historical hourly price and load data for given time intervals, such as two-weeks, and then repeats this on a rolling basis through the year. These supply curves can then be modified on an hourly basis to reflect the impact of generation retirements or additions, including VRE and then reapplied to the same load data to estimate the change in hourly electricity price. The choice of duration over which these RSCs are estimated has a significant impact on goodness of fit. For example, in PJM in 2015, moving from fitting one curve per year to 26 rolling two-week supply curves improves the standard error of the regression from 16 dollars/MWh to 6 dollars/MWh and the R-squared of the estimate from 0.48 to 0.76. We illustrate the potential use and value of the RSC method by estimating wholesale price effects under various generator retirement and addition scenarios, and we discuss potential limits of the technique, some of which are inherent. The ability to do this type of analysis is important to a wide range of market participants and other stakeholders, and it may have a role in complementing use of or providing calibrating insights to PCMs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

Parametric Study of Lithium-Ion Batteries using BatPaC (Final Report)

The Battery Performance and Cost Model (BatPaC) is a tool developed by Argonne National Laboratory to design lithium-ion battery (LIB) packs for automotive applications. The material demand and design specifications are used to estimate the cost of manufacturing the battery pack in a large volume production plant (5-50 GWh/year). With the option to select from various electrode chemistries and materials with their associated properties and prices, the resultant battery pack mass, volume, and cost can vary considerably. This report is the result of a parametric sensitivity study that helps identify the key parameters and prices that affect the battery metrics – the specific energy (Wh/kg) and the pack cost ($/kWh). The study was conducted with LiNi 0.6 Mn 0.2 Co 0.2 O 2 (NMC622) and graphite (G) electrodes as the baseline materials used in a battery pack for a 300-mile range battery electric vehicle (BEV300) and a 50-mile range plug-in hybrid electric vehicle (PHEV50).

25 ENERGY STORAGE↗
DOE OSTI2013

NV Energy Electricity Storage Valuation

This study examines how grid-level electricity storage may benefit the operations of NV Energy, and assesses whether those benefits are likely to justify the cost of the storage system. To determine the impact of grid-level storage, an hourly production cost model of the Nevada Balancing Authority ("BA") as projected for 2020 was created. Storage was found to add value primarily through the provision of regulating reserve. Certain storage resources were found likely to be cost-effective even without considering their capacity value, as long as their effectiveness in providing regulating reserve was taken into account. Giving fast resources credit for their ability to provide regulating reserve is reasonable, given the adoption of FERC Order 755 ("Pay-for-performance"). Using a traditional five-minute test to determine how much a resource can contribute to regulating reserve does not adequately value fast-ramping resources, as the regulating reserve these resources can provide is constrained by their installed capacity. While an approximation was made to consider the additional value provided by a fast-ramping resource, a more precise valuation requires an alternate regulating reserve methodology. Developing and modeling a new regulating reserve methodology for NV Energy was beyond the scope of this study, as was assessing the incremental value of distributed storage.

Ellison, James F.↗
DOE OSTI2023

Hybrid Power Plant Bidding in Models of Future Electricity Systems

This paper proposes a stochastic model for hybrid power plants participation in day-ahead electricity markets, considering uncertainty in market prices and renewable generation. Additionally, it presents a methodology to incorporate this hybrid participation into existing production cost models (PCM), allowing the analysis and market design of future systems with high penetration of hybrids. These developments are illustrated using a wind-battery hybrid located in New York Independent System Operator (NYISO) footprint.

Kemp, Julie Mulvaney↗
DOE OSTI2026

Techno-Economic Comparison of Molten-Salt Electrolysis and Carbothermic Reduction for the Production of Metallurgical-Grade Silicon

Metallurgical-grade silicon (MG-Si) is an important source material for many industrial applications, including the manufacture of alloys, solar photovoltaics, and electronics. The process to refine raw materials into MG-Si is energy-intensive, with the predominant method of submerged-arc furnaces requiring energy consumption of approximately 11–13 kWh/kg Si. Recent research has discussed promising methods for reducing the energy required for the silicon production process, including the use of molten-salt electrolysis (MSE), a technique that offers potential savings in energy consumption without requiring carbon inputs for the process. This paper presents a techno-economic study of a potential industrial-scale MSE plant for MG-Si production to evaluate the trade-offs between capital and operating costs of the system. Capital costs are sourced from recent MG-Si plants and an existing cost model developed for MSE processes that includes the size of the plant and the operating temperature among its inputs. The results show that MSE technology has the potential to be an economically cost-competitive option for MG-Si production if the technology successfully scales to industrial production and matures enough to allow for financing costs similar to that of a comparably sized submerged-arc furnace plant.

14 SOLAR ENERGY↗
DOE OSTI2022

Modeling Global Carbon Costs of Plant Nitrogen and Phosphorus Acquisition

Abstract Most Earth system models (ESMs) do not explicitly represent the carbon (C) costs of plant nutrient acquisition, which leads to uncertainty in predictions of the current and future constraints to the land C sink. We integrate a plant productivity‐optimizing nitrogen (N) and phosphorus (P) acquisition model (fixation & uptake of nutrients, FUN) into the energy exascale Earth system (E3SM) land model (ELM). Global plant N and P uptake are dynamically simulated by ELM‐FUN based on the C costs of nutrient acquisition from mycorrhizae, direct root uptake, retranslocation from senescing leaves, and biological N fixation. We benchmarked ELM‐FUN with three classes of products: ILAMB, a remotely sensed nutrient limitation product, and CMIP6 models; we found significant improvements in C cycle variables, although the lack of more observed nutrient data prevents a comprehensive level of benchmarking. Overall, we found N and P co‐limitation for 80% of land area, with the remaining 20% being either predominantly N or P limited. Globally, the new model predicts that plants invested 4.1 Pg C yr −1 to acquire 841.8 Tg N yr −1 and 48.1 Tg P yr −1 (1994–2005), leading to significant downregulation of global net primary production (NPP). Global NPP is reduced by 20% with C costs of N and 50% with C costs of NP. Modeled and observed nutrient limitation agreement increases when N and P are considered together ( r 2 from 0.73 to 0.83).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2000

Space Resources Roundtable 2

Contents include following: Developing Technologies for Space Resource Utilization - Concept for a Planetary Engineering Research Institute. Results of a Conceptual Systems Analysis of Systems for 200 m Deep Sampling of the Martian Subsurface. The Role of Near-Earth Asteroids in Long-Term Platinum Supply. Core Drilling for Extra-Terrestrial Mining. Recommendations by the "LSP and Manufacturing" Group to the NSF-NASA Workshop on Autonomous Construction and Manufacturing for Space Electrical Power Systems. Plasma Processing of Lunar and Planetary Materials. Percussive Force Magnitude in Permafrost. Summary of the Issues Regarding the Martian Subsurface Explorer. A Costing Strategy for Manufacturing in Orbit Using Extraterrestrial Resources. Mine Planning for Asteroid Orebodies. Organic-based Dissolution of Silicates: A New Approach to Element Extraction from LunarRegohth. Historic Frontier Processes Active in Future Space-based Mineral Extraction. The Near-Earth Space Surveillance (NIESS) Mission: Discovery, Tracking, and Characterization of Asteroids, Comets, and Artificial Satellites with a microsatellite. Privatized Space Resource Property Ownership. The Fabrication of Silicon Solar Cells on the Moon Using In-Situ Resources. A New Strategy for Exploration Technology Development: The Human Exploration and Development of Space (HEDS) Exploratiori/Commercialization Technology Initiative. Space Resources for Space Tourism. Recovery of Volatiles from the Moon and Associated Issues. Preliminary Analysis of a Small Robot for Martian Regolith Excavation. The Registration of Space-based Property. Continuous Processing with Mars Gases. Drilling and Logging in Space; An Oil-Well Perspective. LORPEX for Power Surges: Drilling, Rock Crushing. An End-To-End Near-Earth Asteroid Resource Exploitation Plan. An Engineering and Cost Model for Human Space Settlement Architectures: Focus on Space Hotels and Moon/Mars Exploration. The Development and Realization of a Silicon-60-based Economy in CisLunar Space. Our Lunar Destiny: Creating a Lunar Economy. Cost-Effective Approaches to Lunar Passenger Transportation. Lunar Mineral Resources: Extraction and Application. Space Resources Development - The Link Between Human Exploration and the Long-term Commercialization of Space. Toward a More Comprehensive Evaluation of Space Information. Development of Metal Casting Molds by Sol-Gel Technology Using Planetary Resources. A New Concept in Planetary Exploration: ISRU with Power Bursts. Bold Space Ventures Require Fervent Public Support. Hot-pressed Iron from Lunar Soil. The Lunar Dust Problem: A Possible Remedy. Considerations on Use of Lunar Regolith in Lunar Constructions. Experimental Study on Water Production by Hydrogen Reduction of Lunar Soil Simulant in a Fixed Bed Reactor.

Ignatiev, A.↗
NASA NTRS2005

Operations and Modeling Analysis

The Reliability and Maintainability Analysis Tool (RMAT) provides NASA the capability to estimate reliability and maintainability (R&M) parameters and operational support requirements for proposed space vehicles based upon relationships established from both aircraft and Shuttle R&M data. RMAT has matured both in its underlying database and in its level of sophistication in extrapolating this historical data to satisfy proposed mission requirements, maintenance concepts and policies, and type of vehicle (i.e. ranging from aircraft like to shuttle like). However, a companion analyses tool, the Logistics Cost Model (LCM) has not reached the same level of maturity as RMAT due, in large part, to nonexistent or outdated cost estimating relationships and underlying cost databases, and it's almost exclusive dependence on Shuttle operations and logistics cost input parameters. As a result, the full capability of the RMAT/LCM suite of analysis tools to take a conceptual vehicle and derive its operations and support requirements along with the resulting operating and support costs has not been realized.

Ebeling, Charles↗
DOE OSTI2019

Direct health-care cost of head and neck cancers: a population-based study in north-eastern Italy

Improvements in prognosis of head-and-neck squamous cell carcinoma (HNSCC) have paralleled with an increase in health-care costs, so that an economic evaluation is of growing importance. Presently, most of the evidence is from insurance-based studies in the USA. Between 2007 and 2010, 879 HNSCC patients were identified through the population-based cancer registry of the Friuli Venezia Giulia region, including 266 oral, 187 oropharyngeal, 136 hypopharyngeal, and 290 laryngeal cancers. Health-care costs from diagnosis to treatment initiation and in the following 2 years were retrieved through a record linkage with the regional health data warehouse. This database collected comprehensive health information on all resident citizens. Generalized linear models with a gamma distribution and log-link function were applied to model costs. The average health-care cost from diagnosis up to 2 years after treatment initiation was €20,184 (95% confidence interval: €19,634 − 20,733). Heterogeneity emerged according to cancer site, elective treatment, and retreatment for cancer persistence/recurrence (no: €13,896; yes: €24,599; p < 0.001). An advanced stage was associated with increased costs stage (I: €12,969; II: €18,276; III: €26,229; IV: €25,574; p < 0.001) as the result of treatment complexity and elevated frequency of patients retreatment due to recurrence. These findings further support strategies to diagnose patients at an earlier cancer stage and the accurate definition of diagnostic and treatment pathways, to start treating patients when radical unimodal approach is still feasible. Besides the advantage in prognosis due to timely curative treatments, this would reduce the economic burden of cancer treatment.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Computational Design and Development of a New, Lightweight Cast Alloy for Advanced Cylinder Heads in High-Efficiency, Light-duty Engines

The objective of the collaborative multi-year Cast Lightweight Alloy program was to develop a new, lightweight, cast aluminum alloy for automotive engines with better high temperature properties than the incumbent alloys (B319, A356, A356+0.5Cu) to allow for more efficient engine operation. The program kicked off with the generation of alloy concepts and selecting alloy models with specific milestones for establishing property requirements, generating design concepts and selecting models for casting design. Following this, sub-scale prototypes of the promising design concepts were cast and characterized in order to validate the design concepts and develop data for subsequent model calibration and improvement. Using the calibrated models, a set of alloy designs were created. This first generation set of designs were validated through production and characterization of lab-scale castings. With the learnings from the lab-scale prototypes and the improvements in the computational models, final embodiment design of the new alloy was completed. The final alloy designs were cast at lab-scale and also at component-scale to characterize its final properties. An alloy recyclability analysis and cost modelling was also performed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Acquire and Test IDAES Framework Components

The cooperation under the Grid Modernization Initiative and the Applied Energy Tri-Laboratory umbrellas requires mutual understanding of capabilities and a common effort to identify gaps existing in the available computational modeling and analysis tools. In this work, we report acquisition and testing of the National Energy Technology Laboratory’s Institute for the Design of Advanced Energy Systems (IDAES) framework, particularly including both electric power systems production cost model simulator Prescient as well as system optimization IDAES itself. Further, we consider the methods in which developments in Prescient and IDAES for grid-energy simulation and optimization may be included in the Framework for Optimization of ResourCes and Economics (FORCE) ecosystem that has been under collaborative development by Idaho National Laboratory, Argonne National Laboratory, and Oak Ridge National Laboratory. We propose two integration methods to introduce Prescient and IDAES into existing FORCE automated workflows. One integration involves using Prescient as a market reduced-order model and IDAES models similar to how existing Modelica models are used. The other integration involves wrapping the Prescient-IDAES dispatch optimization process with the stochastic capacity optimization workflow in FORCE.

24 POWER TRANSMISSION AND DISTRIBUTION↗