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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Towards cost-competitive middle distillate fuels from ethanol within a market-flexible C2 platform-based biorefinery concept

Ethanol to middle distillates (ETMD) is a promising pathway to produce sustainable liquid fuels to decarbonize the hard-to-electrify transportation sectors due to (1) the abundant sugar/starch and lignocellulosic biomass, (2) the existing deployment scale of fuel ethanol production (similar to 29 billion gallons per year globally), and (3) emerging opportunities in C2+ alcohol synthesis from CO2. Here we report a conceptual market-responsive biorefinery centered around a new ETMD pathway based on one-step ethanol to butene-rich olefins (ETO) over a Cu-Zn-Y/Beta catalyst. Specifically, this ethanol conversion pathway comprises one-step ETO, oligomerization, and hydrotreating. This ETO is distinct from that in the conventional ethanol-to-jet process which is based on two-step ethanol to ethylene and ethylene oligomerization to butenes. Butene-rich olefins can be shifted to butadiene-rich products by simply changing the reaction atmosphere from hydrogen to inert gas over the same ETO catalyst. Leveraging the experimental results, baseline techno-economic analysis (TEA) and sensitivity analysis indicate that the ethanol conversion cost is $0.60 per gallon gasoline equivalent (GGE), with opportunities for further cost reduction via improving the liquid hydrocarbon yield and space velocities, and process optimization on balancing dewatering of ethanol feed prior to the ETO step. The minimum fuel selling price (MFSP) of liquid hydrocarbons derived from corn starch ethanol with butadiene as coproduct is $1.64 per GGE, in the range that is cost competitive with petroleum kerosene-type jet fuel. Projected MFSP for cellulosic ethanol (corn stover) derived hydrocarbons is below $3.00 per GGE and co-production of butadiene further reduces the MFSP to $1.70 per GGE. The Well-to-Wake life-cycle analysis indicates that 85% greenhouse gas emission reduction can be achieved when using corn stover compared to petroleum reference and the associated carbon credits will provide significant economic incentives to favor the cellulosic ethanol-derived hydrocarbon fuels. This study demonstrates a low-cost pathway to middle distillate fuels leveraging existing ethanol infrastructure, where catalysis innovation drives the reduction of process complexity and flexible coproduction of a value-added chemical product.

Zhang, Junyan↗
NASA NTRS1972

General methodology: Costing, budgeting, and techniques for benefit-cost and cost-effectiveness analysis

The general concepts of costing, budgeting, and benefit-cost ratio and cost-effectiveness analysis are discussed. The three common methods of costing are presented. Budgeting distributions are discussed. The use of discounting procedures is outlined. The benefit-cost ratio and cost-effectiveness analysis is defined and their current application to NASA planning is pointed out. Specific practices and techniques are discussed, and actual costing and budgeting procedures are outlined. The recommended method of calculating benefit-cost ratios is described. A standardized method of cost-effectiveness analysis and long-range planning are also discussed.

Stretchberry, D. M.↗
DOE OSTI2025

CPUC Avoided Transmission and Distribution Cost Study to Support the Avoided Cost Calculator: Avoided Transmission Costs Draft Research Plan

Pacific Northwest National Laboratory (PNNL) and Lawrence Berkeley National Laboratory (LBNL) have been contracted by the California Public Utilities Commission (CPUC) Energy Division (ED) to perform a study which explores and selects an improved methodology to estimate avoided electricity transmission and distribution (T&D) infrastructure costs that can be attributed to the presence of distributed energy resources (DERs). PNNL is performing the study for avoided electricity transmission infrastructure costs and LBNL is performing the study for avoided electricity distribution infrastructure costs. This document summarizes CPUC’s research questions related to avoided transmission infrastructure costs and PNNL’s proposed technical approach to answer these questions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Manufacturing Cost Analysis for PEM Electrolyzers and Perspectives for Future Cost Reduction

Electrolyzer capital costs strongly influence the total levelized cost of hydrogen production and have implications for hydrogen deployment. Current electrolyzer costs are high, and large cost reductions may be needed to achieve competitive hydrogen costs and targets. Understanding pathways for cost reduction via R&D and deployment is a critical research area for informed energy planning and enabling hydrogen use. This work presents bottom-up cost estimates of polymer electrolyte membrane (PEM) electrolyzer systems tied to design specifications and discusses perspectives for cost reduction opportunities based on ongoing research. We use a detailed manufacturing and process model for a 1 MW PEM electrolyzer stack and balance of plant (BOP) for rigorous cost estimation. This allows for robust estimates of component and manufacturing costs and examination of key cost contributors. Stack costs are dominated by material costs such as iridium and platinum catalysts, especially at high manufacturing rates; power electronics and hydrogen purification equipment are the largest contributors to BOP cost. At higher manufacturing rates, better equipment utilization could reduce stack costs significantly, and we estimate that experience and bulk purchasing will allow for cost reductions to some BOP components. Still, many well-established BOP technologies and stack material costs are less likely to see significant cost reductions at high manufacturing rates. As such, manufacturing scale is limited in how much it can reduce electrolyzer costs, and additional advances for cost reduction may be needed to achieve cost targets. It will likely take many combined strategies to achieve significant cost reductions for electrolyzers and enable low-cost hydrogen production. We can use our manufacturing cost model to quantify potential cost reductions from the considerations described above and demonstrate pathways to lower cost electrolyzers. This allows for better understanding of cost reduction strategies and enables more informed research, development, and deployment for electrolyzers.

cost↗
DOE OSTI2025

Soft costs and EVSE – Knowledge gaps as a barrier to successful projects

There has been a recent push to increase access to electric vehicle (EV) charging infrastructure. The National Electric Vehicle Infrastructure (NEVI) program, part of the Bipartisan Infrastructure Law (BIL) has made significant funding available for major charging infrastructure projects along state thruways, and many state and local incentives exist for EV owners to install chargers in their homes. However, deployment of these chargers has not kept up with demand, primarily due to issues in project planning, permitting processes, and unforeseen delays. This paper serves as a review of the current understanding of these and other non-hardware costs in EV charging infrastructure projects (collectively known as “soft costs”). We found that soft costs in EV charging infrastructure projects are not well understood. Specifically, there is little agreement on how soft costs should be categorized and tracked, and less agreement still on best practices for controlling these costs and lowering barriers to infrastructure deployment. A broader review of EV charging infrastructure cost analyses shows that these costs can have significant impacts on project outcomes. EV charging infrastructure projects may be able to examine the success of the solar industry in lowering soft costs, and a similar effort may lower project costs significantly. Further work on standardizing and collecting data on EV charging infrastructure costs is required to begin addressing and controlling these costs.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗
NASA NTRS1992

Modeling the Deep Space Network costs for future space missions by using major cost drivers

This paper develops a cost model to do long range planning cost estimates for Deep Space Network (DSN) support of future space missions. The model is a function of eight major mission cost drivers such as uplink frequency upgrade, telemetry upgrade, and antenna gain/noise temperature upgrade. This paper focuses on the costs required to modify and/or enhance the DSN to prepare for supporting future space missions. Two models are derived from actual cost data from three space missions: Voyager (Uranus), Voyager (Neptune), and Magellan. Model A makes it possible to estimate the total cost, and Model B makes it possible to estimate the time profile cost and total cost for DSN support of a similar future space mission. The models were back tested against the total cost and the time profile cost for DSN support of the three projects, and gave cost estimates which range from 17 percent below to 19 percent above actual costs for Model A, and 22.5 percent below to 17.5 percent above for Model B. The total cost Model A was also applied to estimate the total costs for DSN support of two other independent projects: Mariner Jupiter/Saturn (MJS later became Voyager), and Viking. This model gave total cost estimates for DSN support which range from 15 percent to 4 percent above actual total costs for MJS and Viking, respectively.

Remer, Donald S.↗
DOE OSTI2020

Knowledge Spillovers and Cost Reductions in Solar Soft Costs

Despite the commonly acknowledged importance of knowledge spillovers in reducing solar soft costs, we are only beginning to answer a fundamental question: who learns what (knowledge acquisition), from whom (knowledge production), and how (spillover mechanisms)? Until recently, this important topic has been largely unexplored in the case of solar soft costs. Thus, this project set out to identify how knowledge spillovers affect soft costs in the U.S. photovoltaic (PV) installation industry, specifically how important spillovers are, what types of knowledge are most likely to spillover, and how networks of actors affect spillovers. Our findings offer insights for designing solutions that address problems associated with knowledge spillovers and that leverage spillovers to reduce solar soft costs. Recognizing the ambiguity in the definition of soft costs, i.e., “non-hardware costs,” and variability in soft cost categories, we developed the Solar Soft Cost Ontology (SSCO) to systematically identify key concepts related to soft costs, network actors, learning processes, and the relationships between them. This ontology served as a foundational organizational structure for the methodology of the remaining tasks: case studies, surveys, pricing analysis, patent analysis, network analysis, and project integration across tasks. While there is substantial learning among installers that is reducing the soft costs for PV installations, most of that learning is retained by firms rather than spread across the industry. The positive relationship between experience accumulation and cost reductions is typically explained as learning by doing (LBD), but we find that LBD effects are mediated by other learning mechanisms, including learning by searching and learning by interacting. Knowledge spillovers have significant potential to reduce solar PV soft costs, but successful knowledge spillover pathways are complex and non-trivial. There are a wide variety of ways to construct an installation business, thus categories of firms that can effectively cross-learn directly are small and what knowledge is relevant to whom is challenging and costly for firms to assess. This fragmentation limits the critical mass needed for spillover related soft cost reductions. Knowledge does not flow directly between installers. Indirect knowledge transfer pathways are critical: distributors, software providers, collaboratives, and hiring. Furthermore, diverse, more integrated knowledge networks tend to promote successful learning by organizations and across the system as a whole. Accordingly, we find the need to supporting the whole ecosystem using an integrated policy and programmatic approach to support installers, distributors, complementary sector, and facilitators. Overall, a deliberate policy-mix design is needed to reduce the solar PV deployment barrier in terms of installation cost reductions, because deployment policies could potentially interact with policies that facilitate network-building and technological innovation. A combination of deployment policies, innovation-support policies, and network-facilitating policies could potentially lead to a more desired market outcome through achieving higher joint learning rates from firms’ cumulative experiences developed in a more integrated production and deployment ecosystem.

14 SOLAR ENERGY↗
NASA NTRS1980

Low cost Czochralski crystal growing technology. Near implementation of the flat plate photovoltaic cost reduction of the low cost solar array project

Equipment developed for the manufacture of over 100 kg of silicon ingot from one crucible by rechanging from another crucible is described. Attempts were made to eliminate the cost of raising the furnace temperature to 250 C above the melting point of silicon by using an RF coil to melt polycrystalline silicon rod as a means of rechanging the crucible. Microprocessor control of the straight growth process was developed and domonstrated for both 4 inch and 6 inch diameter. Both meltdown and melt stabilization processes were achieved using operator prompting through the microprocessor. The use of the RF work coil in poly rod melting as a heat sink in the accelerated growth process was unsuccessful. The total design concept for fabrication and interfacing of the total cold crucible system was completed.

Roberts, E. G.↗
DOE OSTI2019

Solar soft cost ontology: a review of solar soft costs

The continued deployment of renewable energy is critical to the energy transition necessary for climate change mitigation. Since cost is one of the primary drivers of solar adoption, we must continue to reduce the cost of solar to hasten the transition to clean energy. Currently, solar soft costs account for 52%–70% of the cost of an installed residential solar photovoltaic (PV) system in the U.S. These costs are persistent and an increasing share of the costs, since hardware costs continue to decline. The consensus on a definition of soft costs is 'non-hardware costs', but defining something by what it is not does not tell us what it is, which makes it difficult to study and understand. To this end, we developed the solar soft cost ontology (SSCO) to provide a comprehensive view of the complex and variable knowledge domain of solar soft costs. In this work, we identify the main categories of solar soft costs, how they relate to each other, how that knowledge is created, shared, and acquired, and the relevant actors in the solar soft cost knowledge ecosystem. Developed by coding a corpus of nearly 130 academic articles, the resulting ontology in web ontology language (OWL) includes 136 classes and 87 properties. The SSCO can facilitate and enhance knowledge transfer of research findings and best practices within and between stakeholder communities, including researchers, practitioners, and policy makers, that seek to address solar soft costs. We conclude with a discussion of potential applications and use cases for the SSCO among this diverse stakeholder community.

14 SOLAR ENERGY↗
DOE OSTI2020

An Evaluation of Energy Storage Cost and Performance Characteristics

The energy storage industry continues to expand globally as costs continue to fall and opportunities in consumer, transportation and grid applications are defined. As the rapid evolution of the industry continues, it has become increasingly important to understand how varying technologies compare in terms of cost and performance. This paper defines and evaluates cost and performance parameters of six battery energy storage technologies (BESS) - lithium-ion batteries, lead-acid batteries, redox flow batteries, sodium-sulfur batteries, sodium metal halide batteries, and zinc-hybrid cathode batteries - four non-BESS storage technologies - pumped storage hydropower, flywheels, compressed air energy storage, and ultracapacitors - and combustion turbines. Cost and performance information was compiled based on an extensive literature review, conversations with vendors and stakeholders, and costs of systems procured at sites across the United States. Detailed cost and performance estimates are presented for 2018 and projected out to 2025. Annualized costs were also calculated for each technology.

Mongird, Kendall↗
NASA NTRS1984

Sensitivities of projected 1980 photovoltaic system costs to major system cost drivers

The sensitivity of projected 1990 photovoltaic (PV) system costs to major system cost drivers was examined. It includes: (1) module costs and module efficiencies; (2) area related balance of system (BOS) costs; (3) inverter costs and efficiencies; and (4) module marketing and distribution markups and system integration fees. Recent PV system cost experiences and the high costs of electricity from the systems are reviewed. The 1990 system costs are projected for five classes of PV systems, including four ground mounted 5-MWp systems and one residential 5-kWp system. System cost projections are derived by first projecting costs and efficiencies for all subsystems and components. Sensitivity analyses reveal that reductions in module cost and engineering and system integration fees seem to have the greatest potential for contributing to system cost reduction. Although module cost is clearly the prime candidate for fruitful PV research and development activities, engineering and system integration fees seem to be more amenable to reduction through appropriate choice of system size and market strategy. Increases in inverter and module efficiency yield significant benefits, especially for systems with high area related costs.

Zimmerman, L. W.↗
NASA NTRS1971

Integrated operations/payloads/fleet analysis. Volume 3: System costs. Appendix A: Program direct costs

Individualized program direct costs for each satellite program are presented. This breakdown provides the activity level dependent costs for each satellite program. The activity level dependent costs, or, more simply, program direct costs, are comprised of the total payload costs (as these costs are strictly program dependent) and the direct launch vehicle costs. Only those incremental launch vehicle costs associated directly with the satellite program are considered. For expendable launch vehicles the direct costs include the vehicle investment hardware costs and the launch operations costs. For the reusable STS vehicles the direct costs include only the launch operations, recovery operations, command and control, vehicle maintenance, and propellant support. The costs associated with amortization of reusable vehicle investment, RDT&E range support, etc., are not included.

Source record↗
NASA NTRS2004

An Exploratory Study of Cost Engineering in Axiomatic Design: Creation of the Cost Model Based on an FR-DP Map

Large complex projects cost large sums of money throughout their life cycle for a variety of reasons and causes. For such large programs, the credible estimation of the project cost, a quick assessment of the cost of making changes, and the management of the project budget with effective cost reduction determine the viability of the project. Cost engineering that deals with these issues requires a rigorous method and systematic processes. This paper introduces a logical framework to a&e effective cost engineering. The framework is built upon Axiomatic Design process. The structure in the Axiomatic Design process provides a good foundation to closely tie engineering design and cost information together. The cost framework presented in this paper is a systematic link between the functional domain (FRs), physical domain (DPs), cost domain (CUs), and a task/process-based model. The FR-DP map relates a system s functional requirements to design solutions across all levels and branches of the decomposition hierarchy. DPs are mapped into CUs, which provides a means to estimate the cost of design solutions - DPs - from the cost of the physical entities in the system - CUs. The task/process model describes the iterative process ot-developing each of the CUs, and is used to estimate the cost of CUs. By linking the four domains, this framework provides a superior traceability from requirements to cost information.

Lee, Taesik↗
DOE OSTI2020

Distributed Minimization of the Power Generation Cost in Prosumer-Based Distribution Networks: Preprint

Traditionally, electrical power was generated in big power plants. The cost of producing energy was related to the cost of fuel, e.g., carbon or gas, and by the cost of maintaining the power plants. With the advent of distributed energy resources, power can be produced directly at the edge of the electrical network by a new type of agents: the prosumers. Prosumers are entities that both consume and generate power, e.g., by means of photovoltaic panels. The cost of the power produced by prosumers is no longer related to fuel consumption since energy coming from distributed generators is essentially free. Rather, the cost is related to the remuneration that is due to the prosumers for the services they provide. The proposed control strategy minimizes the active power generation cost in the aforementioned scenario. The control scheme requires that the prosumers measure their voltage and then adjust the amount of injected power, according to a continuous time feedback control law that is indeed a projected gradient descent strategy. Simulations are provided in order to illustrate the algorithm behavior.

distributed control↗
NASA NTRS1977

A life cycle cost economics model for projects with uniformly varying operating costs

A mathematical model is developed for calculating the life cycle costs for a project where the operating costs increase or decrease in a linear manner with time. The life cycle cost is shown to be a function of the investment costs, initial operating costs, operating cost gradient, project life time, interest rate for capital and salvage value. The results show that the life cycle cost for a project can be grossly underestimated (or overestimated) if the operating costs increase (or decrease) uniformly over time rather than being constant as is often assumed in project economic evaluations. The following range of variables is examined: (1) project life from 2 to 30 years; (2) interest rate from 0 to 15 percent per year; and (3) operating cost gradient from 5 to 90 percent of the initial operating costs. A numerical example plus tables and graphs is given to help calculate project life cycle costs over a wide range of variables.

Remer, D. S.↗
DOE OSTI2022

Manufacturing Cost Analysis of Advanced Parabolic Trough Collector

The research team performed a detailed bottom-up manufacturing cost estimate for an advanced parabolic trough design - the Solar Dynamics Sunbeam-MT (Sunbeam Mid-Term). This includes all components for manufacturing and assembly in a manufacturing facility (e.g. space frame and arms), and the purchased parts (e.g. mirrors and receiver tubes). Estimates of the construction and assembly activities have been made to then determine an estimated installed cost. Prior analysis has already undertaken detailed bottom-up manufacturing, assembly, and construction analysis for the Ultimate Trough from schlaich bergermann partner (sbp), and this work updates the solar field cost estimates based on a similar aperture area as the SunBeam-MT. For this analysis, the Ultimate Trough is considered the commercial parabolic trough and the Sunbeam-MT as the advanced parabolic trough. For similarity, both the Sunbeam-MT and the Ultimate Trough have been modelled with a solar field with approximately 800,000 square meters (m2) in aperture area - the equivalent of a large CSP plant. The analysis has found a potential installed cost estimate of the Sunbeam-MT could be $120/m2 but must be built at scale to confirm this estimate. Compared to prior analysis, the commercial Ultimate Trough using U.S. conditions, has reduced in installed cost from $178/m2 to $152/m2. Both designs could be even cheaper with Chinese steel.

cost analysis↗
DOE OSTI2020

The Cost of Saving Electricity: A Multi-Program Cost Curve for Programs Funded by U.S. Utility Customers

This study analyzed the cost performance of electricity efficiency programs implemented by 116 investor-owned utilities between 2009 and 2015 in 41 states, representing about three-quarters of the total spending on U.S. efficiency programs. We applied our typology to characterize efficiency programs along several dimensions (market sector, technology, delivery approach, and intervention strategy) and report the costs incurred by utilities and other program administrators to achieve electricity savings as a result of the programs. Such cost performance data can be used to compare relative costs of different types of efficiency programs, evaluate efficiency options alongside other electricity resources, benchmark local efficiency programs against regional and national cost estimates, and assess the costs of meeting state efficiency policies. The savings-weighted average cost of saved electricity for the period was $0.025/kilowatt-hour (kWh). The cost of saved electricity for programs that targeted residential customers was $0.021/kWh, compared to $0.025/kWh for programs for commercial and industrial customers. Ultimately, we developed an aggregate program savings “cost curve” for the actual electricity efficiency resource during the period that provides insights into the relative costs of various types of efficiency programs and the savings contribution of each program type to the efficiency resource at a national level.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗