Search NASA⌕ Search

SEARCH · Search NASA

Results for “PROFITS”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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

At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Opportunities for Industry to Provide Flexibility While Increasing Profitability

Supply and demand flexibility will both be needed to ensure the electricity system functions properly as the share from variable renewable generation continues to grow. Industrial manufacturing currently consumes about a third of primary energy worldwide, and electricity is projected to supply an increasing share of this demand as the global economy decarbonizes. Therefore, the ability for industry to flex demand poses an enticing opportunity to enable grid flexibility. However, large capital outlays prevent industry from voluntarily altering demand. Here we show that as battery costs continue to fall, industry will soon be able to profitably alter demand in accordance with electricity price variations. Focusing on two established industries– chlor-alkali and electric arc furnaces – and two industries with large future potential – methane pyrolysis and atmospheric CO 2 capture, we use a linear program (LP) optimization to assess the technoeconomic feasibility of flexible industrial demand across both historical and future-looking wholesale day-ahead marginal prices for the Electricity Reliability Council of Texas (ERCOT). We find positive net present values (NPV) from $\$$400K to $\$$50M using projected 2050 battery prices for industrial purchase of behind-the-meter batteries, using only arbitrage as a source of value. These results indicate that, with projected battery prices, profit-seeking industrial players could voluntarily play a future role in stabilizing a high-renewables grid where electricity prices act as accurate signals of grid needs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Profitability, Scalability and Optimized Siting for Waste-to-Energy Supply Chains: A Case Study on Hydrothermal Liquefaction

Waste-to-Energy (WtE) conversion technologies have the potential to simultaneously reduce waste volumes, treatment-related emissions, and carbon intensity while producing valuable energy services. However, questions remain regarding under which conditions emerging WtE technologies are feasible to deploy. In this project, we develop an optimized siting method for WtE technologies to assess cost-effective WtE processor locations, throughput scales, and profitability. We apply the model using Hydrothermal Liquefaction (HTL) as an example WtE technology. We develop calibrated capital and operating expense cost curves based on literature data to study the techno-economic characteristics of WtE supply chains. Prior to solving the siting optimization, we analyze the model parameters to describe organic waste management system behavior under four different HTL deployment configurations: Co-Processing, where HTL plants send biocrude to existing conventional refineries via assumed pipelines; Co-Location, where biorefineries are co-located with HTL plants; and two alternative Standalone Biorefining cases, where distributed HTL plants transport biocrude intermediate via either assumed pipelines or trucking to centralized biorefineries. We also define and apply several feedstock gate fee calculations, representing different revenue distribution options, to investigate how bioproduct value could impact WtE supply chain economics in terms of waste producer and processor profit or cost reduction.

09 BIOMASS FUELS↗
DOE OSTI2023

Agro-IBIS/THMB Modeled Yield, Nitrogen Loss, and Profitability Maps for the Raccoon River Basin, Iowa, USA

This data was used to assess the potential for improving water quality in this watershed when integrating miscanthus, a bioenergy perennial grass, on to areas of low profit under current corn-soybean management and areas of high nitrogen leaching under both current and future climate conditions. This dataset includes all observations (yield, streamflow, nitrogen loads) and model simulation data used from Dr. Kelsie Ferin’s (former PhD student with Dr. Andy VanLoocke, ISU Dept. of Agronomy) dissertation and publication in Global Change Biology – Bioenergy (DOI: 10.1111/gcbb.13078). Modeled output included in this dataset includes corn, soybean, and miscanthus yields, nitrogen leaching rates, net mineralization rates, land use cover fractions with and without the inclusion of miscanthus, profitability maps, additional soil property maps, and simulated streamflow and nitrogen loads near the outlet of the Raccoon River Basin (Van Meter, Iowa) for both historical and future climate conditions. This dataset includes a mixture of netCDF, .tiff, .csv, and .xlsx files. See README.pdf for more information.

Ferin, Kelsie↗
DOE OSTI2019

Machine Learning for Solar Accessibility: Implications for Low-Income Solar Expansion and Profitability

The solar industry in the US typically uses a credit score such as the FICO score as an indicator of consumer utility payment performance and credit worthiness to approve customers for new solar installations. Using data on over 800,000 utility payment performance and over 5,000 demographic variables, we compare machine learning and econometric models to predict the probability of default to credit-score cutoffs. Here, we compare these models across a variety of measures, including how they affect consumers of different socio-economic backgrounds and profitability. We find that a traditional regression analysis using a small number of variables specific to utility repayment performance greatly increases accuracy and LMI inclusivity relative to FICO score, and that using machine learning techniques further enhances model performance. Relative to FICO, the machine learning model increases the number of low-to-moderate income consumers approved for community solar by 1.1% to 4.2% depending on the stringency used for evaluating potential customers, while decreasing the default rate by 1.4 to 1.9 percentage points. Using electricity utility repayment as a proxy for solar installation repayment, shifting from a FICO score cutoff to the machine learning model increases profits by 34% to 1882% depending on the stringency used for evaluating potential customers.

Davuluri, Sruthi↗
DOE OSTI2014

Opportunities for Energy Crop Production Based on Subfield Scale Distribution of Profitability

Incorporation of dedicated herbaceous energy crops into row crop landscapes is a promising means to supply an expanding biofuel industry while benefiting soil and water quality and increasing biodiversity. Despite these positive traits, energy crops remain largely unaccepted due to concerns over their practicality and cost of implementation. This paper presents a case study for Hardin County, Iowa, to demonstrate how subfield decision making can be used to target candidate areas for conversion to energy crop production. Estimates of variability in row crop production at a subfield level are used to model the economic performance of corn (Zea mays L.) grain and the environmental impacts of corn stover collection using the Landscape Environmental Analysis Framework (LEAF). The strategy used in the case study integrates switchgrass (Panicum virgatum L.) into subfield landscape positions where corn grain is modeled to return a net economic loss. Results show that switchgrass integration has the potential to increase sustainable biomass production from 48% to 99% (depending on the rigor of conservation practices applied to corn stover collection), while also improving field level profitability of corn. Candidate land area is highly sensitive to grain price (0.18 to 0.26 $·kg−1) and dependent on the acceptable subfield net loss for corn production (ranging from 0 to −1000 $·ha−1) and the ability of switchgrass production to meet or exceed this return. This work presents the case that switchgrass may be economically incorporated into row crop landscapes when management decisions are applied at a subfield scale within field areas modeled to have a negative net profit with current management practices.

09 BIOMASS FUELS↗
NASA NTRS1976

Methods utilized in evaluating the profitability of commercial space processing

Profitability analysis is applied to commercial space processing on the basis of business concept definition and assessment and the relationship between ground and space functions. Throughput analysis is demonstrated by analysis of the space manufacturing of surface acoustic wave devices. The paper describes a financial analysis model for space processing and provides key profitability measures for space processed isoenzymes.

Bloom, H. L.↗
NASA NTRS1978

Propulsion/flight control integration technology (PROFIT) software system definition

The Propulsion Flight Control Integration Technology (PROFIT) program is designed to develop a flying testbed dedicated to controls research. The control software for PROFIT is defined. Maximum flexibility, needed for long term use of the flight facility, is achieved through a modular design. The Host program, processes inputs from the telemetry uplink, aircraft central computer, cockpit computer control and plant sensors to form an input data base for use by the control algorithms. The control algorithms, programmed as application modules, process the input data to generate an output data base. The Host program formats the data for output to the telemetry downlink, the cockpit computer control, and the control effectors. Two applications modules are defined - the bill of materials F-100 engine control and the bill of materials F-15 inlet control.

Carlin, C. M.↗
DOE OSTI2022

Characterizing the Payback and Profitability for Automated Heavy Duty Vehicle Platooning

Heavy duty vehicle platooning under highway operating conditions has been projected to provide significant fuel economy gains based on aerodynamic drag improvements of the platooning vehicles. Realizing these benefits and the economic viability under real-world operating conditions presents several challenges. The objective of this paper (the third as part of a series) is to analytically quantify the payback and profitability of heavy-duty vehicles platooning across the U.S. Interstate highway system. In this paper, a rigorous assessment of several factors that influence the platooning system payback for an end-user as well as the revenue potential for suppliers who may be utilizing an equipment lease model dependent on end-user savings, is presented. In this assessment key interactions explored include market adoption rates, platooning velocities, platoon-able daily mileage, platooning likelihood, variations in baseline powertrain fuel economy (diesel or electric), price of fuel (diesel or electricity), platooning fuel economy benefits, price of the added technology, and the impact of natural platooning due to traffic interactions. Further, the paper explores the economic impact of higher levels of vehicle automation for the trailing vehicles in the platoon, where extending the driver Hours of Service (HoS) may provide additional financial benefits. While the approach makes use of a limited fidelity vehicle analytical model for longitudinal dynamics and operations economics, the narrative provides application decision personnel with a mechanism and well-defined set of impact factors to consider as part of their architectural selection process.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2025

Determining the profitability of energy storage over its life cycle using levelized cost of storage

Levelized cost of storage (LCOS) can be a simple, intuitive, and useful metric for determining whether a new energy storage plant would be profitable over its life cycle and to compare the cost of different energy storage technologies. However, researchers and industry decision makers still use conflicting definitions of LCOS. For example, some include charging cost, while others only include round trip efficiency (RTE) losses. Additionally, inputs to the existing formulations are not specific enough to generate repeatable results across studies, which reduces trust in the metric. To push for standardization in economic assessment of batteries and other energy storage devices, the authors review existing definitions of LCOS and identify the desired characteristics for a standard. They then propose a new definition and demonstrate that it fits these characteristics very well relative to other prominent options. Unit analysis is applied to this proposed definition to provide a deeper understanding of the equations and to demonstrate its effectiveness. Finally, the sensitivity of LCOS to different input parameters is investigated to help users understand how to compare analyses from literature to their own. The authors also provide a spreadsheet and a Python script to streamline adoption of the proposed definition.

25 ENERGY STORAGE↗
DOE OSTI2022

Designing an innovation system to support profitable electro- and bio-catalytic carbon upgrade

Carbon capture, utilisation, and storage (CCUS) can mitigate an estimated 14–20% of CO 2 emissions by 2050. Here, we evaluate an integrated electrocatalysis and biocatalysis CCUS pathway, using externally-supplied renewable electricity to convert over 12 MtCO 2 to poly(3-hydroxybutyrate) via methanol and formate intermediates. A techno-economic and policy-innovation analysis provides insight into global CCUS innovation. Results suggest that innovation should focus on improving methanol faradaic efficiency, formate biocatalysis efficiency, electrocatalysis current density, and catalyst performance. Methanol and formate composition influences performance, but higher formate content can improve economics by US$3.8B over a 30 year lifetime. Profitable scenarios hinge on reducing methanol separation costs – through innovation or reduced energy usage – along with cheap renewable electricity and/or carbon pricing. Our evaluation of the global innovation status signifies that coordinated strategies are required to realise emissions cuts from CCUS. Innovation can be spurred by targeted investments and policies that promote emissions reductions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Ensuring Profitability of Energy Storage

Energy storage (ES) is a pivotal technology for dealing with the challenges caused by the integration of renewable energy sources. It is expected that a decrease in the capital cost of storage will eventually spur the deployment of large amounts of ES. These devices will provide transmission services, such as spatiotemporal energy arbitrage, i.e., storing surplus energy from intermittent renewable sources for later use by loads while reducing the congestion in the transmission network. This paper proposes a bilevel program that determines the optimal location and size of storage devices to perform this spatiotemporal energy arbitrage. This method aims to simultaneously reduce the system-wide operating cost and the cost of investments in ES while ensuring that merchant storage devices collect sufficient profits to fully recover their investment cost. Finally, the usefulness of the proposed method is illustrated using a representative case study of the ISO New England system with a prospective wind generation portfolio.

25 ENERGY STORAGE↗
DOE OSTI2013

Financing, Overhead, and Profit: An In-Depth Discussion of Costs Associated with Third-Party Financing of Residential and Commercial Photovoltaic Systems

Previous work quantifying the non-hardware balance-of-system costs -- or soft costs -- associated with building a residential or commercial photovoltaic (PV) system has left a significant portion unsegmented in an 'other soft costs' category. This report attempts to better quantify the 'other soft costs' by focusing on the financing, overhead, and profit of residential and commercial PV installations for a specific business model. This report presents results from a bottom-up data-collection and analysis of the upfront costs associated with developing, constructing, and arranging third-party-financed residential and commercial PV systems. It quantifies the indirect corporate costs required to install distributed PV systems as well as the transactional costs associated with arranging third-party financing.

14 SOLAR ENERGY↗
DOE OSTI2026

Hybrid-Energy-Powered Electrochemical Ocean Alkalinity Enhancement Model: Plant Operation, Cost, and Profitability

Electrochemical ocean alkalinity enhancement is a form of marine carbon dioxide removal, a rapidly growing industry that is powered by efficient onshore or offshore energy sources. As more and larger deployments are being planned, it is important to consider how variable energy sources like tidal energy can impact plant performance and costs. An open-source Python-based generalizable model for electrodialysis-based ocean alkalinity enhancement has been developed that can capture key system-level insights of the electrochemistry, ocean chemistry, acid disposal, and co-product creation of these plants under various conditions. The model additionally accounts for hybrid energy system performance profiles and costs via the National Laboratory of the Rockies’ H2Integrate tool. The model was used to analyze an example theoretical plant deployment in North Admiralty Inlet, including how the plant is impacted by the available energy sources in the region and the scale at which plant costs are covered by the co-products it generates, such as recycled concrete aggregates, without requiring carbon credits. The results show that the example plant could be profitable without carbon credits at commercial scales of 100,000 to 1 million tons of carbon dioxide removal per year, so long as it uses low-cost electricity sources and either sells acid or recovers recycled concrete aggregates with about 1 molar acid concentrations, though more research is needed to confirm these results.

hybrid energy↗