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All sources NASA NTRS DOE OSTI

NASA NTRS2012

Alabama Disasters: Leveraging NASA EOS to Explore the Environmental and Economic Impact of the April 27 Tornado Outbreak

The disastrous tornado outbreak in Alabama on April 27, 2011 greatly impacted the economy of the state. On record, the tornado outbreak was the second deadliest tornado outbreak in U.S. When considering the agricultural and value-added activities such as food and timber processing, farm inputs, manufacturing, transportation, and retail sales, the dollar value of Alabama agribusiness annually exceeds $40 billion (NASS, 2011). This research aims to examine how the timber and agriculture damage affected the state economy of Alabama and will be used to aid in long-term economic recovery. ASTER imagery was used along with ground-truthed NASS (National Agriculture Statistics Service) crop location records to verify the economic impact tornadoes had on the agricultural economy of the state. This swath damage can be calculated by correlating tornado path with NASS statistics on crop yield, precisely showing the fields affected and dollars lost to this disaster. Not only can this be executed manually using ENVI and ArcGIS, but also through the use of Python, a programming language that has the ability to automate the process, creating a product for initial damage assessment.

Herdy, Claire↗

NASA NTRS2012

Alabama Disasters: Leveraging NASA EOS to Explore the Environmental and Economic Impact of the April 27 Tornado Outbreak

Herdy, Claire↗

NASA NTRS2014

The Economics OF NEOS

NASA's Ames Research Center, in its role as partnerships lead for NASA asteroid redirect robotic missions and as a supporting Center for the Asteroid Grand Challenge, responded to increasing interest in near-Earth objects (NEOs) by holding a workshop entitled 'The Economics of NEOs' on the 6th and 7th of September 2014. The workshop was intended to serve as a catalyst for discussions and to foster collaborations between industry, academia and government. This document serves as a summary of the discussions which took place within three sessions and their respective table discussions; Session One: Background and Motivation; Session Two: Economics of NEOs; and Session Three: Policy and Legal Frameworks. This document is a collection of observations by individuals and does not express the consensus view of all participants; it does not express US Government or NASA policy.

Near Earth Objects Asteroids ISRU↗

NASA NTRS2016

Climate Change Observation Accuracy: Requirements and Economic Value

This presentation will summarize a new quantitative approach to determining the required accuracy for climate change observations. Using this metric, most current global satellite observations struggle to meet this accuracy level. CLARREO (Climate Absolute Radiance and Refractivity Observatory) is a new satellite mission designed to resolve this challenge is by achieving advances of a factor of 10 for reflected solar spectra and a factor of 3 to 5 for thermal infrared spectra. The CLARREO spectrometers can serve as SI traceable benchmarks for the Global Satellite Intercalibration System (GSICS) and greatly improve the utility of a wide range of LEO and GEO infrared and reflected solar satellite sensors for climate change observations (e.g. CERES, MODIS, VIIIRS, CrIS, IASI, Landsat, etc). A CLARREO Pathfinder mission for flight on the International Space Station is included in the U.S. Presidentâ€"TM"s fiscal year 2016 budget, with launch in 2019 or 2020. Providing more accurate decadal change trends can in turn lead to more rapid narrowing of key climate science uncertainties such as cloud feedback and climate sensitivity. A new study has been carried out to quantify the economic benefits of such an advance and concludes that the economic value is ~ $9 Trillion U.S. dollars. The new value includes the cost of carbon emissions reductions.

Wielicki, Bruce↗

NASA NTRS2016

Lunar COTS: Using the Moon's Resources to Enable An Economical and Sustainable Pathway to Mars and Beyond

To support NASAs goal of sending humans to Mars, a new plan was constructed to develop and demonstrate cislunar capabilities and services in partnership with commercial industry using the well-proven Commercial Orbital Transportation Services (COTS) Program acquisition model. The NASA COTS Program was a very successful program that developed and demonstrated cost-effective commercial cargo transportation services to the International Space Station (ISS). As a result of NASAs COTS program, two new launch vehicles and spacecraft were developed and have been successfully performing cargo transportation missions to the ISS since 2012. The COTS acquisition strategy utilized a new model than normally accepted in traditional procurement practices. This new model used Space Act Agreements where NASA entered into partnerships with industry to jointly share cost, development and operational risks to demonstrate new capabilities for mutual benefit. This model proved to be very beneficial to both NASA and its industry partners as NASA saved significantly in development and operational costs, as much as tenfold, while industry partners successfully expanded their market share of the global launch transportation business for significant economic benefit. Using the COTS acquisition model as a basis, a new plan, notionally referred to as Lunar Commercial Orbital Transfer Services (or Lunar COTS), has been developed to determine the potential benefits and challenges of a new Lunar COTS plan[1]. The proposed plan includes low-cost, commercial-enabled missions to prospect for resources, determine the economic viability of extracting those resources and assess the value proposition of using these resources in future exploration architectures such as Mars. These missions would be accomplished in partnership with industry to meet these exploration goals but will also have the capability to carry payloads to meet science goals as well.

Zuniga, Allison↗

NASA NTRS2022

AgMIP Regional Integrated Assessment of Agricultural Systems in Nioro, Senegal: Representative Agricultural Pathways, Climate, Crop and Economic Datasets

This paper describes the datasets that were used to implement an AgMIP Regional Integrated Assessment for the Nioro region of Senegal to assess the potential impacts of climate change on the principal agricultural system in the Senegal peanut basin and to assess adaptations of that system to climate change under current as well as future climate and socio-economic conditions. This dataset includes the Representative Agricultural Pathways developed for Nioro from 2000-2050; the climate data that were used to implement crop yield simulations; the data that were used to parameterize the DSSAT and APSIM crop models, including historical climate data and future climate scenarios; and the data that were used to parameterize the Tradeoff Analysis Model for Multi-dimensional Impact Assessment (TOAMD) economic simulation model, as well as simulated model outputs.

AgMIP↗

NASA NTRS2023

Operational Forecasting Inundation Extents using REOF analysis (FIER) over Lower Mekong and its Economic Impact on Agriculture

In the Lower Mekong River Basin floodplains, rice cultivation is highly crucial for regional and global food security. However, prolonged flooding can pose damage to rice cultivation and other socio-economic aspects. Yet, there is no rapid operational inundation forecasting system that can help decision-makers proactively mitigate flood damages. Here, we integrated the so-called Forecasting Inundation Extents using Rotated empirical orthogonal function analysis (FIER) framework with an altimetry-based operational Mekong River level forecasting system and built an operational web application, FIER-Mekong, (https://fier-mekong.streamlit.app/) that generates daily skillful forecasted inundation extents (>70% of critical success index) and depths in about 3 and 30 s, respectively, with up to 18-day lead times. One of its applications, predicting flood-induced rice economic losses, is also presented. Had FIER-Mekong being adopted, we estimated that the rice damages, up to 87 and 53 million US dollars during the 2020 and 2021 harvest time, respectively, could have been avoided.

Chi-Hung Chang↗

NASA NTRS2024

A Fair, Economically-Efficient, Incentive-Aligned, Scalable Airspace Auction Mechanism for UAV Traffic Management

Unmanned Aerial Vehicles (UAVs) are increasingly used in a wide range of applications such as cinematography, package delivery, and surveying. As a result, regulators have become interested in developing UAV Traffic Management (UTM) systems to coordinate UAV traffic. One possible framework for UTM is a combinatorial auction. Under this framework, airspace is modeled as a grid of space-time cells. UAV operators bid on sets of cells which collectively form flight paths for their UAVs. An ideal airspace auction should: be fair, be incentive-aligned, be scalable, allocate airspace economically-efficiently, enable price discovery, and reduce the work required to participate where possible. In this paper, we propose the first auction mechanism for airspace allocation that meets the criteria above. Our mechanism: (a) is provably economically-efficient, fair and incentive-aligned, (b) shares pricing information with bidders and (c) has features which reduce the burden of participating. We evaluate our mechanism on scenarios based on a Japan Aerospace Exploration Agency (JAXA) case study and find that it can scale to 26,000 bids.

Robert Allan Morris↗

DOE OSTI2021

Machine Learning and Economic Models to Enable Risk-Informed Condition Based Maintenance of a Nuclear Plant Asset

The primary objective of this research is to address challenges in the implementation of risk-informed, condition-based predictive maintenance (PdM), which reduces operating costs while still maintaining the safety and reliability of commercial nuclear power plants (NPPs). To achieve the objective, risk models are being developed by taking advantage of advancements in data analytics, deep learning, machine learning (ML), and artificial intelligence (AI). The notable outcomes presented in the report include ? Development of a ML models using heterogeneous plant process and vibration data collected at different spatial and temporal resolutions from the Salem?s CWS to diagnose a circulating water pump (CWP) failure based on salient fault signatures. The developed diagnostic models are extendable to other faults associated with CWPs and CWP motors given associated fault signatures. ? Development of a natural language processing (NLP) technique to automatically classify the WO data into different categories. The developed NLP technique was validated on independent WO data. This automates the tedious and time-consuming activity of mining and classifying WOs by subject matter experts. ? Estimation of mean time between downtime (i.e., time duration between time instances when 1 or more CWPs are not available) and developed an approach to establish reliability of CWS components using unstructured WO data along with CWS plant process data. ? Formulation of economic model based on Markov chain models. The parameters of associated with the transition rate between different states of Markov chain models were estimated using WO data. The economic model formulation and discussion captures both time-independent and time-dependent parameter variation, leading to risk-informed decision-making.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2021

Economic Comparison Between a Battery and Supercapacitor for Hourly Dispatching Wave Energy Converter Power: Preprint

This paper demonstrates a successful dispatching scheme of slider-crank wave energy converter (WEC) production using two different kinds of energy storage systems, namely, (i) Li-ion battery and (ii) Supercapacitors (SC). The performance of two energy storage systems has been compared in order to develop the most economical energy storage system for WEC hourly dispatching scheme. The cost optimization of the energy storage system considering both cycling and calendar aging expenses is made based on its usage of depth of discharge (DOD). In this study, the extensive simulation is conducted in MATLAB/Simulink platform, and it is found that SC is a better candidate than Li-ion battery in terms of economic assessment for hourly dispatching WEC power.

50 EE - Wind and Water Power Program - Water (EE-4↗

DOE OSTI2021

Analysis of Residential Time-of-Use Utility Rate Structures and Economic Implications for Thermal Energy Storage

Thermal energy storage (TES) is an increasingly popular tool to level out the daily electrical demand and add stability to the electrical grid as more intermittent renewable energy sources are installed. TES systems can locally decouple high thermal loads from the operation of a heat pump or reduce the electrical energy demand of the heat pump by providing a more favorable temperature gradient. In addition, many policy makers and utility providers have introduced time-of-use (TOU) rate schedules for residential customers to better reflect the price of electricity generation and demand for specific times. TOU rate schedules price grid-provided electricity differently throughout the day depending on the region’s climate, time of year, and electrical production. Large differences between on-peak and off-peak electrical prices may create an economic advantage for a residential customer to install a TES system. In this work, the economic and energy savings are calculated for a modeled 2,400 square foot residential building with water/ice-based TES using a TOU rate structure. The weather data is from Fresno County, CA, ASHRAE climate zone 3B, and a representative residential TOU utility rate structure from Pacific Gas and Electric (PG&E) was used. The results showed that total energy consumption could be reduced by 14.5% with an 87.5% reduction in on-peak energy usage when the TES is installed. The cost of operating this system for space cooling was reduced by nearly 20% using the sample utility rate plan.

Sultan, Sara↗

DOE OSTI2021

Solving the Dynamics-Aware Economic Dispatch Problem with the Koopman Operator

The dynamics-aware economic dispatch (DED) problem embeds low-level generator dynamics and operational constraints to enable near real-time scheduling of generation units in a power network. DED produces a more dynamic supervisory control policy than traditional economic dispatch (T-ED) that reduces overall generation costs. However, in contrast to T-ED, DED is a nonlinear, non-convex optimization problem that is computationally prohibitive to solve. We introduce a machine learning-based operator-theoretic approach for solving the DED problem efficiently. Specifically, we develop a novel discrete-time Koopman Operator (KO) formulation that embeds domain information into the structure of the KO to learn high-fidelity approximations of the generator dynamics. Using the KO approximation, the DED problem can be reformulated as a computationally tractable linear program (abbreviated DED-KO). We demonstrate the high solution quality and computational-time savings of the DED-KO model over the original DED formulation on a 9-bus test system.

King, Ethan↗

DOE OSTI2021

Economic and Environmental Sustainability of an Integrated Direct Air Capture System with Advanced Algal Biofuel Production

The presentation titled Economic and Environmental Sustainability of an Integrated Direct Air Capture System with Advanced Algal Biofuel Production. The background and motivation of the presentation will encompass promotion of decarbonization of the atmosphere, decouple algae production facilities from anthropogenic CO2 sources, identify key economic drivers, minimize cost and greenhouse gas emissions through process integration and optimization.

algal biofuel production↗

DOE OSTI2022

Techno-Economic Analysis

This National Energy Technology Laboratory presentation was given at the Carbon Conversion Procurement Grant Program Regional Workshops. The workshops are organized collaboratively by the DOE Office of Fossil Energy and Carbon Management and the United States Energy Association. There are a series of four workshops scheduled: 1) August 30, 2022 in Knoxville, TN (University of Tennessee) 2) September 13, 2022 in Emeryville, CA (Lawrence Berkeley National Laboratory 3) September 27, 2022 in New York, NY (Orrick, Herrington, & Sutcliffe LLP) 4) October 18, 2022 in Minneapolis, MN (TBD) The intent of the workshop is to provide potential applicants with background on the Procurement Grants program and the types of information requested. The specific purpose of this presentation is to give a high-level overview of techno-economic analysis to an audience that has little to no experience conducting them. The intent is to help the audience understand why techno-economic analysis is requested in the application process and to educate on its utility.

Hackett, Gregory↗

DOE OSTI2022

Evaluating the Feasibility of Higher Titers and Yields for 2,3-Butanediol Production to Achieve the Biofuel Industry Economic Goal of Under $3.50 GGE

To achieve the economic goal of producing biofuels that can compete with petroleum-based products, we increased titers of 2,3-butanediol (BDO) production. BDO has many advantages over ethanol; including lower toxicity, higher heat of capacity, and is a precursor to various valuable applications. To produce BDO for fuel upgrading, we have genetically modified Zymomonas mobilis (YC-1). Several materials and feed strategies were evaluated to determine the best titer and economic feasibility. Titers from DMR corn stover in a batch process were in the range of 70-80 g/L. The fully hydrolyzed material was easy to work with but suffered from dilution issues. We pushed the concentration of solids to above 25% w/w and were met with numerous challenges. This included an initial sugar concentration above 150 g/L, the high solid concentration altered the oxygen mass transfer rate and affected which products were produced, and the fermentation conditions were not optimal for the enzyme. Despite these challenges, our current results yielded 100 g/L of upgradeable products (70 g/L BDO and 30 g/L acetoin) and 83% fermentation process yield. However, the poor enzymatic hydrolysis yield of 64%, unconverted xylose, and the high acetoin levels warrant further exploration for optimization. Using unhydrolyzed solids as the feed material, we achieved titers in the range of 75-95 g/L BDO. The raw solids feed, though operationally more challenging to work with, proved to be promising as the rate of hydrolysis promoted co-utilization of the sugars. We reached 150 g/L BDO using concentrated DDR liquors under boules and continuous feeding strategies. The clarified liquors showed high titers, high productivity, high yield, and high sugar utilization with little drawback operationally. The target goal of under $3.50 GGE was achieved in several feeding strategies. Scale-up feasibility has also been demonstrated at the 100L scale using both whole slurry and liquor hydrolysates.

BIOMASS FUELS↗

DOE OSTI2022

FECM/NETL Unconventional Shale Well Economic Model (UShWEM): Description and User’s Manual

FECM/NETL Unconventional Shale Well Economic Model (UShWEM) is an Excel-based model that evaluates the economics of an unconventional shale well on a per-well and per-pad basis. This document serves as the user’s manual for the model with descriptions of the procedures the user must follow to run the model. This document also describes the capabilities of the model and provides the equations that are used by the model to calculate technical quantities and key model outputs including net cash flow, internal rate of return (IRR), net present value (NPV), earnings before interest, taxes, depreciation, and amortization (EBITDA), payout month and year, and breakeven price (for either oil- or gas-wells).

Sheriff, Alana↗

DOE OSTI2022

FECM/NETL Unconventional Shale Well Economic Model (UShWEM): Production Data for UShWEM

The Production Data for UShWEM.xlsx is an Excel file that is formatted and organized similarly to the Production Streams sheet of the FECM/NETL Unconventional Shale Well Economic Model (UShWEM). The purpose of this file is to allow the user to import completion design and time-series production data for hundreds of wells into the UShWEM easily and quickly, and have their well data saved safely in an external location. For instructions on how to use the Production Data for UShWEM.xlsx file, see section 2.3 of the FECM/NETL Unconventional Shale Well Economic Model: User’s Manual.

Sheriff, Alana↗

DOE OSTI2022

NETL’s Techno-Economic Models for Assessing CO2 Pipeline Transport and Geologic Storage

Presentation at Society of Petroleum Engineers (SPE) Workshop: Future Energy Roadmap – Navigating Through the Energy Transition, held in Galveston, Texas, August 22-23, 2022. The presentation provides an overview of the techno-economic models NETL has developed for assessing performance characteristics and cost drivers for CO2 pipeline transport (FECM/NETL CO2 Transport Cost Model or CO2_T_COM), CO2 saline storage (FECM/NETL CO2 Saline Storage Cost Model or CO2_S_COM), and oil production and CO2 storage using CO2 enhanced oil recovery (EOR) (FE/NETL CO2 Prophet Model or CO2_Prophet and FE/NETL Onshore CO2 EOR Cost Model or CO2_E_COM). A high-level description of each model is presented along with useful outputs that can be generated with each model. These tools can be used individually to evaluate the economic opportunity for specific CCUS components, or they can be used in tandem to assess an integrated CCUS value chain.

Morgan, David↗