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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Techno-Economic Wind Blade Manufacturing Model to Identify Opportunities for Cost Improvements Phase II IACMI Project 4.6/4.8

In IACMI Project 4.6 and IACMI Project 4.8, an Excel-based Techno-Economic Model (TEM) of the manufacturing process for composite wind turbine blades and a DELMIA Factory Flow Simulation of a generic wind blade manufacturing facility was developed. Together, these two tools provide a combined economic modeling capability that accounts for the material, labor, overhead and full-lifecycle operating costs associated with wind blade manufacturing as well as the impact of process flow and factory layout on overall manufacturing efficiency. The tools provide a novel means of detailed comparative analysis of the economic feasibility of proposed technologies and process changes for blade manufacturing. The modeling tools were developed with close support from members of industry and visits to multiple blade manufacturing facilities. With industry oversight, a detailed generalized manufacturing process plan and facility layout were developed with manufacturing parameters, material costs and economic factors based on historical data. Dassault Systèmes and the University of Texas at Dallas (UTD) contributed to the development of the Techno-Economic Model by providing macros to enable the generation of Bill of Material (BOM) data from a 3D blade design in either CATIA or NuMAD format, respectively. The TEM was built with the capability to directly import a Bill of Materials for economic analysis, and with the addition of the macros provided by Dassault and UTD, the TEM can directly import blade designs from both CATIA and NuMAD file formats. The modeling tools developed in Project 4.6 were used to investigate four wind blade manufacturing concepts in detail and select one to explore with laboratory-scale experimentation in Project 4.8. The four manufacturing concepts that were investigated were down-selected by the full project team from a larger list of concepts. The selections were made based on a number of criteria ranking viability and level of interest for each concept. The ‘One-Step Close’ manufacturing concept was ultimately selected for investigation in Project 4.8 and the demonstration was performed at the NREL CoMET facility. The TPI advanced manufacturing facility in Warren, RI contributed the production of several prototype components, the designs for which were developed by Janicki Industries. The demonstration project provided clear indication of the viability of the One-Step Close manufacturing concept for blade manufacturing and good validation of the Techno-Economic Model’s prediction of its economic impact.

17 WIND ENERGY↗
DOE OSTI2021

10 New Insights in Climate Science 2020 - a Horizon Scan

We summarize some of the past year’s most important findings within climate change-related research. New research has improved our understanding of Earth’s sensitivity to carbon dioxide, finds that permafrost thaw could release more carbon emissions than expected and that the uptake of carbon in tropical ecosystems is weakening. Adverse impacts on human society include increasing water shortages and impacts on mental health. Options for solutions emerge from rethinking economic models, rights-based litigation, strengthened governance systems and a new social contract. The disruption caused by COVID-19 could be seized as an opportunity for positive change, directing economic stimulus towards sustainable investments.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Climate-Driven Divergence in Biophysical and Economic Impacts of Agrivoltaics

Increasing global demands for food and energy necessitate innovative land-use solutions. Agrivoltaics, colocating solar photovoltaics with agriculture, shows promise, but its widespread adoption faces complex biophysical and economic trade-offs in a changing climate. Here, we develop an integrated biophysical-economic modeling framework to quantify how agrivoltaics affect biophysical and economic impacts across the Midwestern United States under both current and project climate conditions. We find strong regional divergences driven by climate gradients. In the humid eastern Midwest, solar panel shading limits photosynthesis, leading to reduced yields (maize -24%; soybean -16%) and lower farmers' profitability (maize -16%; soybean -2%) compared to conventional agriculture. Conversely, in the semiarid western region, shading alleviates heat and water stress, moderating yield reductions for maize (-12%) and even boosting soybean yields (+6%), resulting in improved economic returns (-6% for maize; +9% for soybean), for a scenario with 33% photovoltaic ground coverage ratio. Although agrivoltaics generate substantial electrical energy across all regions, high upfront installation costs challenge solar developers compared to standalone solar photovoltaics. However, our analysis identifies “win-win” opportunities where soybean-based agrivoltaics in the semiarid region produce economic benefits for both farmers and solar developers, highlighting the necessity for region-specific designs tailored to local climate conditions. Critically, future climate projections indicate eastward expansion of semiarid conditions, broadening areas where agrivoltaics can mitigate crop yield penalties (even boosting yield) and improve overall profitability, especially under high-emission scenarios. The results provide a mechanistic and economically integrated understanding essential for developing evidence-based and region-specific strategies to scale agrivoltaics in a changing climate.

14 SOLAR ENERGY↗
DOE OSTI2023

Jobs and Economic Development Impact (JEDI) Models

The Jobs and Economic Development Impact (JEDI) models (https://www.nrel.gov/analysis/jedi/) are publicly available, user-friendly tools designed to estimate the economic impacts of both construction and operation of power generation and biofuel plants at a local (usually state) level. Based on project-specific and default inputs (from techno-economic analysis data and NREL's expertise), these models estimate the number of jobs and economic benefits to a region that could reasonably be supported by a particular project. Underlying these calculations is an input-output framework that models the local economy as a network of sectors buying and selling to one-another, creating a multiplier effect. Over the last decade, JEDI has been widely used by both the academic and private sectors, serving as the foundations for multiple peer-reviewed publications and impact analysis reports.

economic impact analysis↗
NASA NTRS2018

Using Remote Sensing Mapping and Growth Response to Environmental Variability to Aide Aquatic Invasive Plant Management

Management of aquatic weeds in complex watersheds and river systems present many challenges to assessment, planning and implementation of management practices for floating and submerged aquatic invasive plants. The Delta Region Areawide Aquatic Weed Project (DRAAWP), a USDA sponsored area-wide project, is working to enhance planning, decision-making and operational efficiency in the California Sacramento-San Joaquin Delta. Satellite and airborne remote sensing are used map (area coverage and biomass density), direct operations, and assess management impacts on plant communities. Archived satellite records enable review of results following previous climate and management events and aide in developing long-term strategies. Examples of remote sensing aiding effectiveness of aquatic weed management will be discussed as well as areas for potential technological improvement. Modeling at local and watershed scales using the SWAT modeling tool provides insight into land-use effects on water quality (described by Zhang in same Symposium). Controlled environment growth studies have been conducted to quantify the growth response of invasive aquatic plants to water quality and other environmental factors. Environmental variability occurs across a range of time scales from long-term climate and seasonal trends to short-term water flow mediated variations. Response time for invasive species response are examined at time scales of weeks, day, and hours using a combination of study duration and growth assessment techniques to assess water quality, temperature (air and water), nitrogen, phosphorus, and light effects. These provide response parameters for plant growth models in response to the variation and interact with management and economic models associated with aquatic weed management. Plant growth models are to be informed by remote sensing and applied spatially across the Delta to balance location and type of aquatic plant, growth response to altered environments and phenology. Initial utilization of remote sensing tools developed for mapping of aquatic invasive plants improved operational efficiency in management practices. These assessment methods provide a comprehensive and quantitative view of aquatic invasive plants communities in the California Delta.

Remote Sensing↗
NASA NTRS2018

Using Remote Sensing to Assess of Growth and Distribution for Floating Invasive Plants and Growth Response Times to Altered Environments

Management of aquatic weeds in complex watersheds and river systems present many challenges to assessment, planning and implementation of management practices for aquatic invasive plants. The Delta Region Areawide Aquatic Weed Project (DRAAWP), a USDA (U. S. Dept. of Agriculture)-sponsored area-wide project, is working to enhance planning, decision-making and operational efficiency of invasive plant management in the California Sacramento-San Joaquin Delta. Satellite and airborne remote sensing are used to map area of plant coverage and estimate biomass density to aid operations and assess management impacts on plant communities. Modeling at local and watershed scales using the SWAT (Soil Water Assessment Tool) modeling tool provides insight into land-use effects on water quality. Environmental variability in the Delta occurs across a range of time scales from long-term climate and seasonal trends to short-term water flow mediated variations. Controlled environment growth studies have been conducted to quantify the growth response of invasive aquatic plants to water quality and other environmental factors. Response time for invasive species response are examined at time scales of weeks, day, and hours using a combination of study duration and growth assessment techniques to assess water quality, temperature (air and water), and light effects. These provide response parameters for plant growth models in response to environmental variation and interact with management and economic models associated with aquatic weed management. Plant growth models are to be informed by remote sensing and applied spatially across the Delta to balance location and type of aquatic plant, growth response to altered environments and phenology. Initial utilization of remote sensing tools developed for mapping of aquatic invasive plants improved operational efficiency in management practices. These assessment methods provide a comprehensive and quantitative view of aquatic invasive plant communities in the California Delta.

Floating↗
NASA NTRS2019

Growth Response of Water Hyacinth to Environmental Ranges in the California Sacramento-San Joaquin River Delta

Management of aquatic weeds in complex watersheds and river systems present many challenges to assessment, planning, and implementation of management for aquatic invasive plants. The Delta Region Areawide Aquatic Weed Project (DRAAWP), a USDA sponsored area-wide project including NASA Ames Research Center and State of California Department of Boating and Waterways, is working to enhance decision-making and operational efficiency of invasive plant management in the California Sacramento-San Joaquin Delta. Expansion of invasive aquatic plants has been detrimental to water management and the ecosystem complex in the San Francisco Bay/California Delta. The portion of DRAAWP reported here focuses on parametrizing the environmental response inputs for the Delta models for prominent invasive aquatic plants. Changing climate, long-term drought, shifts in land use, and variation in water flow and quality from input watersheds lead to wide and unique variation in environmental conditions. Environmental variability occurs across a range of time scales from long-term climate and seasonal trends to short-term water flow mediated variations. Response of invasive aquatic plants are examined using controlled environment growth facilities at time scales of weeks, day, and hours using a combination of study duration and growth assessment techniques to assess water quality, temperature, nutrient, and light effects. These provide response parameters for plant growth models in response to the variation and interact with management and economic models associated with aquatic weed management. Plant growth models are informed by remote sensing and applied spatially across the Delta to balance location and type of aquatic plant, growth response to altered environments and phenology.

Sacramento-San Joaquin River Delta.v↗
DOE OSTI2023

A2E2G (Atmosphere to Electrons to the Grid platform) [SWR-23-22]

A2E2G is a platform that integrates 1) forecasting tools to account for weather uncertainty, with 2) aerodynamic wind plant models to account for wake dynamics and wind plant operation, and 3) economic models to advise on operation for a wind power plant that offers grid services in addition to energy. The A2E2G platform can be used as a high-level controller for a wind plant for market participation and real-time wind plant control. The A2E2g platform is a holistic Python tool with modules that can be run to 1) advise on market participation and 2) control and operate a wind power plant in real time. The A2E2g framework assumes two stages: the first stage is in day-ahead and the second stage is in real-time. Managing uncertainty is key in the first stage and managing variability is key in the second stage. The different components have models written and developed in the Python programming language. The code is assembled into a Python package and can be easily downloaded and installed from the A2E2g repository (https://github.com/NREL/a2e2g).

Sinner, Michael↗
DOE OSTI2026

Climate impacts in scenarios: time to close the loop?

Reaching a full understanding of the consequences of climate change for society and ecosystems, and the ensuing needs for adaptation, requires a consideration of the interactions between human and Earth systems. Currently, however, climate research largely separates the influence of society on climate from the influence of climate on society; that is, it doesn’t “close the loop.” A primary example of this approach is the generation and use of earth system model (ESM) simulations in the climate change research community. Large-scale socio-economic models, known as integrated assessment models (IAMs), are used to project emissions and land use change which serve as input to ESMs. ESM projections then serve as input to models of impacts on society and ecosystems. But, according to this modeling chain, those impacts do not affect the emissions and land use that drove the ESMs in the first place. Previous work has not drawn firm conclusions on whether this feedback would be large enough to warrant explicitly accounting for it. Two prominent possibilities, however, are that emissions and land use scenarios representing the high and low ends of the plausible range of future climate change are both too extreme. The high-end scenario may miss damaging impacts that would reduce economic activity, and therefore emissions, while the low-end scenario may ignore climate feedbacks that would make large-scale land-based carbon removal ineffective and therefore would hamper mitigation at the level assumed by the scenario. In this piece, we identify the opportunities and challenges that implementing such feedback loops would face. We argue that recent developments in climate impact research, human system modeling and ESM emulation make the time ripe to use IAMs in a structured model intercomparison exercise. Model intercomparison projects have benefitted the climate modeling community for decade snow, and more recently have also benefitted the impact modeling community. An IAM intercomparison focused on integrating impacts could make large strides in testing the implications of these feedbacks and assessing whether closing the loop would fundamentally change our outlook on future climate changes and their consequences.

Tebaldi, Claudia↗
DOE OSTI2022

Techno-Economic Analysis of Recuperated Joule-Brayton Pumped Thermal Energy Storage

This article describes a techno-economic model for pumped thermal energy storage systems based on recuperated Joule-Brayton cycles and two-tank liquid storage. Models have been developed for each component, with particular emphasis on the heat exchangers. Economic metrics such as the power and energy capital costs (i.e., per-kW and per-kWh capacity) and levelized cost of storage are evaluated by gathering numerous cost correlations from the literature, thereby enabling estimates of uncertainty. It is found that the use of heat exchangers with effectivenesses up to 0.95 is economically worthwhile, but higher values lead to rapidly escalating component size and system cost. Several hot storage fluids are considered; those operating at the highest temperatures (chloride salts) improve the round-trip efficiency but the benefit is marginal and may not warrant the additional material costs and risk when compared to lower-temperature nitrate salts. Cost-efficiency trade-offs are explored using a multi-objective optimization algorithm, yielding optimal designs with round-trip efficiencies in the range 59-72% and corresponding levelized storage costs of 0.12 0.03 and 0.38 0.10 $/kWhe. Lifetime costs are competitive with lithium-ion batteries for discharging durations greater than 6 h under current scenarios.

Carnot battery↗
DOE OSTI2022

Estimating production cost for large-scale seaweed farms

Seaweed farming has the potential to produce feedstocks for many applications, including food, feeds, fertilizers, biostimulants, and biofuels. Seaweeds have advantages over land-based biomass in that they require no freshwater inputs and no allocation of arable land. To date, seaweed farming has not been practiced at scales relevant to meaningful biofuel production. Here we describe a techno-economic model of large-scale seaweed farms and its application to the cultivation of the cool temperate species Saccharina latissima (sugar kelp) and the tropical seaweed Eucheumatopsis isiformis. At farm scales of 1000 ha or more, our model suggests that farm gate production costs in waters up to 200 km from the onshore support base are likely to range between $\$$200 and $\$$300 per dry tonne. The model also suggests that production costs below $\$$100 per dry tonne may be achievable in some settings, which would make these seaweeds economically competitive with land-based biofuel feedstocks. While encouraging, these model results and some assumptions on which they are based require further field validation.

09 BIOMASS FUELS↗
DOE OSTI2023

Thermal & Electrochemical Power Plant Design and Cost Estimation

Public textbook for "Thermal & Electrochemical Power Plant Design and Cost Estimation: Version#1" This public textbook is an extension of class notes from Carnegie Mellon University courses: Energy System Modeling (24-722) and Fuel Cell Systems (24-262), taught by Dr. Nicholas Siefert between 2010-2021. Textbook includes some references to class notes from Dr. Shawn Litster, Department of Mechanical Engineering, Carnegie Mellon University. Textbook covers the equilibrium and nonequilibrium thermodynamics of power systems as well as an overview of system and economic modeling of these systems. There is in-depth coverage of (a) entropy generation, (b) exergy and (c) the redox state of molecules in equilibrium with the natural environment. This textbook is integrated with other materials (such as lecture slides, solved homeworks, and solved exams) that will be posted to the PowerShare: Energy Systems Modeling group on EDX. Publication Number: DOE/NETL-2023/3913

30 DIRECT ENERGY CONVERSION↗
DOE OSTI2023

Modeling and simulation to investigate the electrification potential of medium- and heavy-duty vehicle fleets

This project involves developing and integrating new modeling tools to simulate the dynamics of electric medium- and heavy-duty fleet vehicle adoption. A technical and economic modeling tool, combining a data-driven hardware cost model with a cost-optimal charging strategy microsimulation, enables tailored analysis of the costs and benefits of electrifying individual fleets. Next, a novel text synthesis process, applied to a curated corpus of literature, quantifies trade-offs between technical, economic, and other factors in the fleet vehicle procurement decision. The outcomes of these tasks combine with knowledge from recent literature on fleet decision processes to specify the vehicle procurement model used by fleets in an agent-based model of the medium- and heavy-duty electric vehicle market. This model embodies an especially disaggregated approach to adoption modeling, internalizing factors and dynamics that conventional adoption models externalize. In particular, explicitly modeling the formation and diffusion of opinions among agents enables experiments that conventional models cannot support. Demonstrations show, for example, that increasing the extent of interactions between populations with different proclivities to electric vehicles has an asymmetrical outcome. High-proclivity electric vehicle adoption is generally unaffected as interactions increase, but low-proclivity adoption is accelerated. By representing individual fleets' requirements and costs at a high level of detail, incorporating an adoption decision model informed by a wide body of empirical research, and broadening the array of variables and dynamics available for experimentation, this integrated model offers a new way to understand the urgent challenge of eliminating emissions from the most emissions-intensive transportation sectors.

Trinko, David A.↗
NASA NTRS1969

The stability of coupled renewal-differential equations with econometric applications

Concepts and results are presented in the fields of mathematical modeling, economics, and stability analysis. A coupled renewal-differential equation structure is presented as a modeling form for systems possessing hereditary characteristics, and this structure is applied to a model of the Austrian theory of business cycles. For realistic conditions, the system is shown to have an infinite number of poles, and conditions are presented which are both necessary and sufficient for all poles to lie strictly in the left half plane.

Rhoten, R. P.↗
NASA NTRS1981

Economic evaluation of a solar hot-water system--Palm Beach County, Florida

Report projects solar-energy costs and savings for residential hot-water system over 20 year period. Evaluation uses technical and economic models with inputs based on working characteristics of installed system. Primary analysis permits calculation of economic viability for four other U.S. sites.

Source record↗
NASA NTRS2018

Interplanetary Supply Chain Risk Management

Emphasis on KSC ground processing operations, reduced spares up-mass lift requirements and campaign-level flexible path perspective for space systems support as Regolith-based ISM is achieved by; Network modeling for sequencing space logistics and in-space logistics nodal positioning to include feedstock. Economic modeling to assess ISM 3D printing adaption and supply chain risk.

Galluzzi, Michael C.↗
DOE OSTI2020

Building the Foundation for Assessing GOM Offshore CO 2 EOR and CO 2 Storage [Slides]

This PowerPoint Presentation was used in a seminar given to headquarters personnel as well as other stakeholders. The seminar took place on August 7, 2020. The presentation introduces three offshore oil field case studies: Cognac, Petronius, and Horn Mountain. The NETL/ARI Gulf of Mexico (GOM) offshore large oil fields data base provides a strong foundation for the upcoming offshore GOM CO 2 storage and enhanced oil recovery (EOR) assessment. The three Case Studies show that significant volumes of CO 2 can be securely stored in the offshore GOM and that notable volumes of addition oil can be recovered from this area with CO 2 EOR. The Case Studies also show that the CO 2 Prophet Model can serve as an excellent assessment tool. The “next steps” include building the cost and economics models for offshore CO 2 transportation and particularly for conducting seafloor CO 2 EOR and CO 2 storage.

02 PETROLEUM↗