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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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NASA NTRS2005

XML technology planning database : lessons learned

A hierarchical Extensible Markup Language(XML) database called XCALIBR (XML Analysis LIBRary) has been developed by Millennium Program to assist in technology investment (ROI) analysis and technology Language Capability the New return on portfolio optimization. The database contains mission requirements and technology capabilities, which are related by use of an XML dictionary. The XML dictionary codifies a standardized taxonomy for space missions, systems, subsystems and technologies. In addition to being used for ROI analysis, the database is being examined for use in project planning, tracking and documentation. During the past year, the database has moved from development into alpha testing. This paper describes the lessons learned during construction and testing of the prototype database and the motivation for moving from an XML taxonomy to a standard XML-based ontology.

prototype databases↗

NASA NTRS2004

XML hierarchical database for missions and technologies

A hierarchical XML database is being developed by the New Millennium Program to assist in technology Return on Investment (ROI) analysis and technology portfolio optimization.

Some, Raphael R.↗

NASA NTRSDate not supplied

Framework for NASA Space Relay Satellite Services over the Next Decade: Development and Demonstration of the Commercial Successors to TDRS

• NASA SCaN Program plans to pursue commercial services for communications with Spacecrafts in near-earth Orbit • The Communications Services Project (CSP) formulated at GRC to establish partnerships with commercial SATCOM companies to develop and demonstrate the feasibility of providing SATCOM capabilities that could be offered as a service for future spacecraft users • CSP pursued an Announcement of Proposals (AFP) in 2021 • Awarded 6 industry vendors out of 14 (~ $278 million) • Viasat, SES Government Solutions, SpaceX; Kuiper Government Solutions (KGS), Telesat U.S. Services, Inmarsat Government. (4 RF and 2 Optical) • AFP’s objectives to develop and demonstrate end-to-end operational capabilities that could meet the needs of Government and private sector customers and maximize interoperability between them. • NASA completed assessment and analysis of the 6 industry proposals. • Results identified optimal portfolio that best meet AFP’s Objectives when considering capability coverage, risk spread, levels of confidence, U.S. domestic market stimulation, price and NASA budget.

George Haddad↗

NASA NTRS2024

Cost and Benefit Analysis of Mitigating, Tracking, and Remediating Orbital Debris

Orbital debris may collide with crewed and robotic spacecraft, placing them at risk. The wide range of debris, from 9,000-kilogram rocket bodies to millions of millimeter-size debris, has led to a similarly wide range of proposed actions for addressing the risks posed by debris. However, the costs and benefits of these actions have historically been unknown. This is a challenge for decision makers who are choosing which actions to support through technology development or policy changes. NASA’s Office of Technology, Policy, and Strategy is addressing these technical and economic uncertainties by building a capability to (1) complete rigorous calculations of the net present value of each action, (2) identify an optimal portfolio of actions to reduce risk, and (3) quantitatively analyze policies related to space sustainability. This report describes our progress toward that capability and to solicit feedback from the space and economic communities. Our previous work, referred to here as Phase 1, assessed the costs and benefits of performing debris remediation on operationally relevant timescales. The current analysis contains major updates to the risk model used in Phase 1 and expands the breadth of actions considered to include mitigating the creation of debris, improving the ability to track debris, and more methods for cleaning up existing debris. We demonstrate that our approach of measuring risks in dollars allows for the effectiveness of seemingly incommensurate actions to be compared and generates insights that other approaches to measuring risk have missed.

Jericho Locke↗

NASA NTRS2024

Cost and Benefit Analysis of Mitigating, Tracking, and Remediating Orbital Debris

Presentation accompanying the technical report with the same name. The abstract for the report and the full study is repeated below. Orbital debris may collide with crewed and robotic spacecraft, placing them at risk. The wide range of debris, from 9,000-kilogram rocket bodies to millions of millimeter-size debris, has led to a similarly wide range of proposed actions for addressing the risks posed by debris. However, the costs and benefits of these actions have historically been unknown. This is a challenge for decision makers who are choosing which actions to support through technology development or policy changes. NASA’s Office of Technology, Policy, and Strategy is addressing these technical and economic uncertainties by building a capability to (1) complete rigorous calculations of the net present value of each action, (2) identify an optimal portfolio of actions to reduce risk, and (3) quantitatively analyze policies related to space sustainability. This report describes our progress toward that capability and to solicit feedback from the space and economic communities. Our previous work, referred to here as Phase 1, assessed the costs and benefits of performing debris remediation on operationally relevant timescales. The current analysis contains major updates to the risk model used in Phase 1 and expands the breadth of actions considered to include mitigating the creation of debris, improving the ability to track debris, and more methods for cleaning up existing debris. We demonstrate that our approach of measuring risks in dollars allows for the effectiveness of seemingly incommensurate actions to be compared and generates insights that other approaches to measuring risk have missed.

Jericho Locke↗

NASA NTRSDate not supplied

A Cost and Benefit Analysis of Orbital Debris Remediation, Mitigation,Tracking, and Characterization

Orbital debris may collide with crewed and robotic spacecraft, placing them at risk. The wide range of debris, from 9,000-kilogram rocket bodies to millions of millimeter-size debris, has led to a similarly wide range of proposed actions for addressing the risks posed by debris. However, the costs and benefits of these actions have historically been unknown. This is a challenge for decision makers who are choosing which actions to support through technology development or policy changes. NASA’s Office of Technology, Policy, and Strategy is addressing these technical and economic uncertainties by building a capability to (1) complete rigorous calculations of the net present value of each action, (2) identify an optimal portfolio of actions to reduce risk, and (3) quantitatively analyze policies related to space sustainability. This report describes our progress toward that capability and to solicit feedback from the space and economic communities. Our previous work(Colvin, Karcz, and Wusk. 2023), referred to here as Phase 1, assessed the costs and benefits of performing debris remediation on operationally relevant timescales. The current paper summarizes the work of Locke and Colvin (2024), which contains major updates to the risk model used in Phase 1 and expands the breadth of actions considered to include mitigating the creation of debris, improving the ability to track debris, and more methods for cleaning up existing debris. We demonstrate that our approach of measuring risks in dollars allows for the effectiveness of seemingly incommensurate actions to be compared and generates insights that other approaches to measuring risk have missed.

Orbital Debris↗

DOE OSTI2023

Nuclear's Role in the U.S. Electricity System: A Multi-Model Inter-Comparison Analysis

A variety of US electric power sector capacity expansion models are used by decision makers and analysts to evaluate competition among generation, transmission, and storage technologies to meeting the demands of the system. CEMs use least-cost optimization to identify optimal portfolios of investments capable of satisfying all specified requirements. While CEMs are a useful tool to inform pathways to meet future needs, projections can differ significantly between tools for apparently similar scenario assumptions. Differences in model structure, scope, and input assumption contribute to this issue. This work compares model response with harmonization between four modeling teams on issues significant to the representation and development of nuclear energy.

capacity expansion model↗

DOE OSTI2023

Insights on Nuclear Energy from Long-Term System Models: Inter-Model Comparison Results

capacity expansion model↗

DOE OSTI2021

Optimal energy storage portfolio for high and ultrahigh carbon-free and renewable power systems

Achieving 100% carbon-free or renewable power systems can be facilitated by the deployment of energy storage technologies at all timescales, including short-duration, long-duration, and seasonal scales; however, most current literature focuses on cost assessments of energy storage for a given timescale or type of technology. In this work, we use an optimization framework with high spatial and temporal resolution to simultaneously assess the variable renewable power deployment and the optimal storage portfolio for seven independent system operators in the United States. Results indicate that achieving high (75–90%) and ultrahigh (>90%) energy mixes requires combining several flexibility options, including renewable curtailment, short-duration, long-duration, and seasonal storage. For instance, carbon-free and renewable energy mix targets of up to 80% are achieved with economic curtailment and a combination of short- and long-duration energy storage for the performance and cost assumptions used. After that, there is a point between 80% and 95% where seasonal storage becomes cost-competitive, depending on the specific power system. Moreover, our results indicate that storage-to-storage operation—one storage device used to charge another storage device—and the decoupling of charging and discharging storage power capacity are cost-effective options for the integration of high and ultrahigh shares of carbon-free or renewable power sources. Additionally, the results from this study show that an 85% carbon-free or renewable energy mix can be achieved at a cost of avoided CO 2 emissions of US$66.0 per tonne or less, regardless of the power system.

25 ENERGY STORAGE↗

DOE OSTI2019

Including operational aspects in the planning of power systems with large amounts of variable generation: A review of modeling approaches

In the past, power system planning was based on meeting the load duration curve at minimum cost. The increasing share of variable generation (VG) makes operational constraints more important in the planning problem, and there is more and more interest in considering aspects such as sufficient ramping capability, sufficient reserve procurement, power system stability, storage behavior, and the integration of other energy sectors often through demand response assets. In VG integration studies, several methods have been applied to combine the planning and operational timescales. We present a four-level categorization for the modeling methods, in order of increasing complexity: (1a) investment model only, (1b) operational model only, (2) unidirectionally soft-linked investment and operational models, (3a) bidirectionally soft-linked investment and operational models, (3b) operational model with an investment update algorithm, and (4) co-optimization of investments and operation. The review shows that using a low temporal resolution or only few representative days will not suffice in order to determine the optimal generation portfolio. In addition, considering operational effects proves to be important in order to get a more optimal generation portfolio and more realistic estimations of system costs. However, operational details appear to be less significant than the temporal representation. Furthermore, the benefits and impacts of more advanced modeling techniques on the resulting generation capacity mix significantly depend on the system properties. Thus, the choice of the model should depend on the purpose of the study as well as on system characteristics.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2017

The CPAT 2.0.2 Domain Model - How CPAT 2.0.2 "Thinks" From an Analyst Perspective.

To help effectively plan the management and modernization of their large and diverse fleets of vehicles, the Program Executive Office Ground Combat Systems (PEO GCS) and the Program Executive Office Combat Support and Combat Service Support (PEO CS &CSS) commissioned the development of a large - scale portfolio planning optimization tool. This software, the Capability Portfolio Analysis Tool (CPAT), creates a detailed schedule that optimally prioritizes the modernization or replacement of vehicles within the fleet - respecting numerous business rules associated with fleet structure, budgets, industrial base, research and testing, etc., while maximizing overall fleet performance through time. This report contains a description of the organizational fleet structure and a thorough explanation of the business rules that the CPAT formulation follows involving performance, scheduling, production, and budgets. This report, which is an update to the original CPAT domain model published in 2015 (SAND2015 - 4009), covers important new CPAT features. This page intentionally left blank

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2017

The Capability Portfolio Analysis Tool (CPAT): A Mixed Integer Linear Programming Formulation for Fleet Modernization Analysis (Version 2.0.2).

In order to effectively plan the management and modernization of their large and diverse fleets of vehicles, Program Executive Office Ground Combat Systems (PEO GCS) and Program Executive Office Combat Support and Combat Service Support (PEO CS&CSS) commis- sioned the development of a large-scale portfolio planning optimization tool. This software, the Capability Portfolio Analysis Tool (CPAT), creates a detailed schedule that optimally prioritizes the modernization or replacement of vehicles within the fleet - respecting numerous business rules associated with fleet structure, budgets, industrial base, research and testing, etc., while maximizing overall fleet performance through time. This paper contains a thor- ough documentation of the terminology, parameters, variables, and constraints that comprise the fleet management mixed integer linear programming (MILP) mathematical formulation. This paper, which is an update to the original CPAT formulation document published in 2015 (SAND2015-3487), covers the formulation of important new CPAT features.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2006

Postoptimality analysis in the selection of technology portfolios

This paper describes an approach for qualifying optimal technology portfolios obtained with a multi-attribute decision support system. The goal is twofold: to gauge the degree of confidence in the optimal solution and to provide the decision-maker with an array of viable selection alternatives, which take into account input uncertainties and possibly satisfy non-technical constraints.

portfolios↗

DOE OSTI2025

Decision-Dependent Uncertainty-Aware Distribution System Planning Under Wildfire Risk

The interaction between power systems and wildfires can be dangerous and costly. Distribution grids can be liable for the outbreak of wildfires during extreme weather. In wildfire-prone areas, investment planning should consider the impact of operational actions on wildfire-related uncertainties affecting line failure likelihood. Here, in this case, endogenous-based uncertainty modeling should comprise the backbone of the investment planning model viz-a-viz the inability of standard exogenous-based uncertainty modeling. Therefore, we propose a decision-dependent uncertainty (DDU) aware methodology to optimize investment portfolios for distribution systems, considering that high power-flow levels in high-threat areas can ignite wildfires and increase line failure probability. The methodology identifies the best combination of upgrades (new lines, hardening existing lines, and placing switching devices). Methodologically, we propose a two-stage distributionally robust planning optimization problem with DDU that considers the distribution system's multiperiod operation. The first stage determines optimal switching actions and line investments, and the second stage evaluates the worst-case expected operational cost under a DDU framework designed to account for the endogenous impact of power-flow levels and hardening investment decisions in the line failure probabilities. An iterative method is tailored to handle the problem and numerical experiments demonstrate a more prepared grid to deal with wildfire risk.

Power systems investment planning↗

DOE OSTI2025

The value of hydropower flexibility for electricity system decarbonization

Hydropower is an abundant, dispatchable, clean energy resource that will play an important role in supporting the clean energy transition. In particular, dispatchable hydropower can provide the operational flexibility that will be required in future systems with high variable renewable energy penetrations. However, the theoretical operational flexibility of hydropower can be restricted in practice by various non-power constraints. In this paper, we quantify how increasing the operational flexibility of dispatchable hydropower resources with reservoirs impacts least-cost generation portfolios and supports power system decarbonization. Specifically, we conduct a capacity expansion analysis of a two-zone system: a hydro-dominated region and a neighboring region with aggressive decarbonization targets that are represented by the United States Pacific Northwest and California respectively. We then introduce a quantifiable index for characterizing the operational flexibility of reservoir hydropower and assess how changes in this metric impact the system-optimal generation portfolio. We find that increasing hydropower flexibility leads to more investment in wind generation, less investment in natural gas generation, lower system costs, and lower system emissions. We further demonstrate a substitution effect between the grid services provided by flexible hydropower operation, increased transmission capacity on a congested line, and energy storage resources. Finally, we show that increasing the operational flexibility of hydropower increases the effective load carrying capability of both hydropower and wind resources. This research supports a more nuanced understanding of how hydropower can support electricity system decarbonization and may motivate reassessing the cost-benefit tradeoffs of non-power constraints that restrict operational flexibility.

Capacity expansion modeling↗

DOE OSTI2025

Energy storage in combined gas-electric energy transitions models: The case of California

California’s vision for a net-zero future by 2045 relies heavily on variable renewable energy systems. Thus, energy storage - particularly long-duration storage - could play a fundamental role in reliably supplying low-carbon electricity. We study energy storage using the BRIDGES model, a combined gas-electric capacity expansion model for California across multiple investment periods (2025-2045), modeled with progressively decreasing carbon emission targets to a zero emissions by 2045. This least-cost optimization model includes renewable gas production via power-to-gas, long-term storage of energy in gaseous form, electric energy storage such as through batteries and hydrogen storage, and renewable energy generation, all with capacity tracking and investment. Multiple scenarios are evaluated to examine the sensitivity of the optimal storage portfolio to system-level and sector-level parameters. The scenario results show that all electric energy storage systems - which vary in storage duration - are deployed and required in a net-zero California in 2045, amounting to around 75 GW of storage capacity. Lithium ion systems make up approximately 80% of this power capacity and supply most short-run storage needs. Hydrogen storage - in the form of a power-to-gas-to-power system - emerges as a replacement to conventional natural gas storage, comprising most of the total energy storage capacity (~ 4 TWh). This capacity is less than 5% of the current natural gas storage capacity (94 TWh), indicating sufficient room for repurposing part of the gas infrastructure. A demand-side sensitivity analysis proves that higher electricity demand correlates with more builds of Li-ion batteries, while higher industrial heat demand leads to more builds of long-duration storage systems in a net-zero economy. Furthermore, power-to-gas systems satisfy part of the industrial heat demand by locally supplying renewable gas, which overtakes the traditional centralized gas storage and transfers through pipelines, casting significant doubts on the future of the large-scale gas infrastructure.

03 NATURAL GAS↗

DOE OSTI2021

Energize: An Interactive Evaluation Tool for Engaging the General Public with Energy Decision Making - Final Report

The public has an ever-increasing interest in the economic, environmental, and social impacts of global energy production. To support informed decision making, the scientific community has a responsibility to communicate reliable and straight-forward information to the general public, in an engaging way, regarding energy systems and how choices made at different stages of an energy technology life cycle can impact the cost, amount of materials used, and waste produced. Our objective is to enhance public engagement via an interactive electrical energy game (Energ!ze) through which players interact with one another in their quest to develop an electrical energy portfolio that optimizes economic (e.g., company profit), environmental (e.g., reduced CO 2 emissions), and social (e.g., public opinion) impacts. The design and development of Energ!ze was an iterative process involving an interdisciplinary team of engineers, discipline-based scientists, computer scientists, and education experts. The development objectives were two-fold: (1) Accurate and quantifiable modeling of electrical energy systems and (2) Engaging and interactive user interface within the construct of the game narrative. The major game mechanics in the current playable Energ!ze version focus on economic metrics, and the database is scaffolded to add environmental and social metrics for future versions. This report details the outcome of the funding period (Section 2 and 3) and describes the development process, along with recommendations for future development (Section 4).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2022

Impact of Transport Electrification Demand and Charging Schedules on Electricity Markets and Nuclear Generators

As the U.S. pursues deep decarbonization targets, electric vehicles (EVs) are likely to become a major driver of demand growth and a major determinant of daily demand patterns. This study analyzes a possible future ERCOT-like electricity grid, and examines the impact of different types of EV charging schedules on grid and market outcomes. This analysis demonstrates the significant impact of EV charging patterns on capacity expansion simulations. Even without EVs, the overall daily demand profile in a market can have significant impacts on prices and grid stability in that system, especially if non-dispatchable renewable generators (e.g. wind and solar) make up a significant fraction of the generation mix. EV demand will not necessarily follow this preexisting demand profile, so its daily trends may significantly change what generation portfolio would optimally serve the system. Furthermore, the effects of EV demand can alter the profitability of different types of units, by altering the frequency of market events like extreme-demand hours or zero-price hours. These effects are explored in this study. The EV demand levels were derived from MARKAL simulations of the West-South-Central North American Electric Reliability Corporation (NERC) region for the year 2050, using a carbon tax of $100/ton. The baseline MARKAL simulation forecasted that 23% of the region’s annual electricity demand in 2050 would be attributable to EVs, and broke out demand projections for EV and non-EV end-use in that year. To model lower EV penetration into the system, an additional case was explored which assumed that EVs only achieved 75% of the demand level projected by MARKAL.

24 POWER TRANSMISSION AND DISTRIBUTION↗