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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Learning with Adaptive Conservativeness for Distributionally Robust Optimization: Incentive Design for Voltage Regulation: Preprint

Information asymmetry between the Distribution System Operator (DSO) and Distributed Energy Resource Aggregators (DERAs) obstructs designing effective incentives for voltage regulation. To capture this effect, we employ a Stackelberg game-theoretic framework, where the DSO seeks to overcome the information asymmetry and refine its incentive strategies by learning from DERA behavior over multiple iterations. We introduce a model-based online learning algorithm for the DSO, aimed at inferring the relationship between incentives and DERA responses. Given the uncertain nature of these responses, we also propose a distributionally robust incentive design model to control the probability of voltage regulation failure and then reformulate it into a convex problem. This model allows the DSO to periodically revise distribution assumptions on uncertain parameters in the decision model of the DERA. Finally, we present a gradient-based method that permits the DSO to adaptively modify its conservativeness level, measured by the size of a Wasserstein metric-based ambiguity set, according to historical voltage regulation performance. The effectiveness of our proposed method is demonstrated through numerical experiments.

distribution system operator↗
DOE OSTI2025

Learning with Adaptive Conservativeness for Distributionally Robust Optimization: Incentive Design for Voltage Regulation

Information asymmetry between the Distribution System Operator (DSO) and Distributed Energy Resource Aggregators (DERAs) obstructs designing effective incentives for voltage regulation. To capture this effect, we employ a Stackelberg game-theoretic framework, where the DSO seeks to overcome the information asymmetry and refine its incentive strategies by learning from DERA behavior over multiple iterations. We introduce a model-based online learning algorithm for the DSO, aimed at inferring the relationship between incentives and DERA responses. Given the uncertain nature of these responses, we also propose a distributionally robust incentive design model to control the probability of voltage regulation failure and then reformulate it into a convex problem. This model allows the DSO to periodically revise distribution assumptions on uncertain parameters in the decision model of the DERA. Finally, we present a gradient-based method that permits the DSO to adaptively modify its conservativeness level, measured by the size of a Wasserstein metric-based ambiguity set, according to historical voltage regulation performance. The effectiveness of our proposed method is demonstrated through numerical experiments.

adaptation models↗
DOE OSTI2025

Game Theory Approaches for System-level Incentive Design

This report presents a generalized Stackelberg game framework for designing and evaluating financial incentives that enhance power system resilience through strategic deployment of distributed energy resources(DERs) under various contingencies. The proposed approach addresses the challenge of coordinating individual community investment decisions to meet system-wide resilience objectives. The framework is demonstrated in a three-community test system subjected to two transmission contingency scenarios: inter-community line failure (Case 1) and complete main grid disconnection (Case 2). In both cases, three incentive levels are compared: a Base case with no financial incentives, and low and high incentive cases. In Case 1, the Base case (no incentives) results in a total installed DER capacity of 217.2 MW, with no load shedding due to alternative routing, but community costs remain high. Increasing incentives raises DER deployment to 286.9 MW, lowers aggregate community costs by $22M annually, and completely avoids the need for costly new transmission line construction. In Case 2, the Base case results in 24.3 MWh of unserved load; introducing incentives eliminates all load shedding and ensures up to 89 MWh of battery storage is available for emergency reserve. These results demonstrate that targeted incentives can dramatically improve grid resilience and cost-effectiveness. The framework thus offers policymakers and system planners a robust tool to quantify and compare the effectiveness of incentive programs for multi-community transmission networks behavior, system resilience, and economic efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Distribution Grid Incentive Design with Unknown Agent Behavior

Motivation: During extreme events, traditional grid regulation methods (e.g., energy prices, net power injection limits) may be insufficient. While system operators typically lack control over end-user grid interactions, (e.g., energy demand), incentives can influence behavior - for example, a user that receives a grid-driven incentive may adjust their consumption or expose relevant control variables in response. Problem: Optimize for the best incentive subject to system stability constraints. However, user behavior is unknown to the SO - i.e., for a given incentive, the amount of curtailed load or control variables exposed is unknown.

feedback based control↗
DOE OSTI2024

Machine-Learning-Based Mapping and Modeling of Solar Energy with Ultra-High Spatiotemporal Granularity

Despite the rapid growth of solar energy, we still lack a dynamic, high-fidelity database that tracks the spatiotemporal variations of solar PVs and their associated infrastructures across different places at a spatially resolved scale. The absence of such data presents a barrier to various applications such as solar PV growth projection, solar energy integration, solar incentive design, and climate risk assessment. In this project, we aim to bridge this gap by developing AI-based algorithms to extract granular information about solar PV installations and their associated infrastructures (i.e., distribution grids) from widely available unstructured data like remote sensing images and street views. As a result, we have built the Solar Energy Atlas, a fine-grained, large-scale geospatial overlay of distributed solar PVs and distribution grids. On top of it, we have advanced the understanding of solar adoption and distribution grid vulnerability to climate-induced extremes. Our major contributions can be summarized as follow: (1) By developing new AI algorithms, we have built the most comprehensive solar PV spatiotemporal database covering the entire US. This is the first time we obtained the exact GPS locations, size, subtype, and installation year information for rooftop solar PVs across the US. This database can be used for solar PV growth projection, solar energy integration, solar energy policy analysis and design, and spatially-resolved climate risk assessment. (2) Leveraging this database, we have uncovered the socioeconomic driving factors that are correlated with earlier onset of solar adoption and higher saturated adoption levels. We have identified the heterogeneity in the effects of different types of financial incentives on solar adoption and provided implications for tailoring incentive design based on local income levels to promote equitable solar adoption. (3) We have developed a distribution grid GIS mapping algorithm which can obtain granular geospatial and topology information about distribution grids using multi-modal open data, reducing the dependency on hard-to-obtain smart meter data of conventional approaches. It shows effectiveness in both the U.S. and Sub-Saharan Africa. Using this algorithm, we have uncovered the non-uniform vulnerability of distribution grids to wildfires in California in the aspects of undergrounding protection and Distributed Energy Resources (DER) preparedness. This has provided important implications for improving the affordability and equity of grid adaptation approaches. (3) We have made our produced database publicly available and provided user-friendly interface to enable various stakeholders and the general public to interact with the data. We have also integrated the produced data into the Data Commons platform to enable the public to access the data and correlate it with other location-specific characteristics simply using natural language as queries. The impact of our project is three-fold: (1) New algorithms for mapping solar PVs and distribution grids across space and time, which are open source to facilitate researchers and industry; (2) New databases of solar PVs and distribution grids that have been made publicly available for engineering, social, and policy applications; (3) New understandings and actionable insights on the potential approaches to promoting solar adoption and reducing energy infrastructure vulnerabilities. In this report, we start by discussing the project background and motivation (section 5), followed by the overview of project objectives (section 6). Results and discussion for each task are presented in section 7. Significant accomplishments are summarized in section 8. This report will be concluded by discussing the paths forwards (section 9), products (section 10), and team roles (section 11).

14 SOLAR ENERGY↗
DOE OSTI2022

Rooftop solar incentives remain effective for low- and moderate-income adoption

Financial incentives for rooftop solar photovoltaic (PV) adoption have declined in the United States over time by policy design. Incentive phase-down can efficiently promote early adoption and avoid ineffective payments to late adopters. Furthermore, incentive phase-down may exclude low- and moderate-income (LMI) households from realizing the same financial benefits from PV adoption as high-income early adopters. Here, data from two state-level LMI PV incentive programs are analyzed to test whether incentives still drive PV adoption among LMI households. As a first order approximation, the analysis suggests that incentives drove adoption that would not otherwise have happened in about 80% of cases. To the extent that policymakers prioritize PV adoption equity as part of the emerging energy justice policy agenda, the results suggest that ongoing incentive support for LMI adoption may be merited.

14 SOLAR ENERGY↗
DOE OSTI2023

The impact of market design and clean energy incentives on strategic generation investments and resource adequacy in low-carbon electricity markets

Well-designed electricity markets play a crucial role in maintaining reliable electric power systems, which are critical in modern society. Here, this study examines the impact of different electricity market designs and clean energy incentive schemes on supporting renewable energy integration and achieving clean energy goals. To this end, we utilize a game-theoretical generation expansion planning model where generation companies make investment and retirement decisions to maximize their expected profit. The model is structured as an equilibrium problem with equilibrium constraints (EPEC) and solved using a diagonalization approach combined with progressive hedging. We analyze three types of electricity market designs: an energy-only market, a capacity market, and a clean energy market, and consider a wide range of market parameters resulting in 14 total scenarios. Wind and solar capacity comprise the majority of new investments in all considered scenarios, but the resultant system planning reserve margin (PRM) can differ significantly depending on market parameters. We also find that profit-driven investments lead to lower PRMs than a traditional system cost minimization approach. These individual scenario results further demonstrate how different market designs and clean energy incentive schemes may influence investor decision-making and impact resource adequacy throughout the clean energy transition.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Incorporate day-ahead robustness and real-time incentives for electricity market design

In this paper, we propose a two-stage electricity market framework to explore the participation of distributed energy resources (DERs) in a day-ahead (DA) market and a real-time (RT) market. The objective is to determine the optimal bidding strategies of the aggregated DERs in the DA market and generate online incentive signals for DER-owners to optimize the social-welfare taking into account network operational constraints. Distributionally robust optimization is used to explicitly incorporate data-based statistical information of renewable forecasts into the supply/demand decisions in the DA market. We evaluate the conservativeness of bidding strategies distinguished by different risk aversion settings. In the RT market, a bi-level time-varying optimization problem is proposed to design the online incentive signals to tradeoff the RT imbalance penalty for distribution system operators (DSOs) and the costs of individual DER-owners. This enables tracking their optimal dispatch to provide fast balancing services, in the presence of time-varying network states while satisfying the voltage regulation requirement. Simulation results on both DA wholesale market and RT balancing market demonstrate the necessity of this two-stage design, and its robustness to uncertainties, the performance of convergence, the tracking ability and the feasibility of the resulting network operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Economics of land‐based carbon mitigation

Agricultural land holds tremendous potential to contribute to net zero greenhouse gas emission goals by providing low carbon renewable energy to displace fossil fuels and by serving as a sink for sequestering carbon in the soil with climate‐smart practices. This potential is, however, far from being realized. This paper examines the economic incentives and barriers to implementing land‐based carbon mitigation strategies and discusses the specific features of land‐based carbon mitigation practices on carbon emissions that need to be considered in designing policy incentives to induce adoption. Although a carbon price‐based policy is socially efficient, the more commonly observed policies to promote land‐based carbon mitigation include practice‐based conservation programs, technology mandates, and sector‐specific standards. The paper discusses the rationale for these alternative policy approaches and concludes with a discussion of emerging opportunities for designing policy and market‐based approaches for promoting land‐based carbon‐mitigation and future directions for economics research.

additionality↗
DOE OSTI2022

Systems Packages for Washington State Building Performance Standard Incentive Program: Phase 1 Analysis

Starting in 2026 Washington State building performance standards will come into effect that require commercial buildings larger than 50,000 sf to meet site energy use intensity targets. To support a state incentive program designed to encourage building owners to start complying early, we characterized the building stock energy use of 11 building types, analyzed 43 energy upgrade measures, and developed seven packages of energy upgrade measures using the ComStock energy analysis tool. Each energy upgrade package included from 4 to 17 energy measures consisting of lighting, HVAC, and envelope upgrades. Package savings were calculated for four priority building types using a sample of 35,000 buildings characterized by four building area bins, three climate zones, and two county types (urban and rural). Of the 28 package and building type combinations analyzed, 17 (61%) met or exceeded program energy savings targets and two packages met targets for all four building types.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1985

SONTRAC: A solar neutron track chamber detector

The recent detection on the solar maximum mission (SMM) satellite of high energy neutrons emitted during large solar flares has provided renewed incentive to design a neutron detector which has the sensitivity, energy resolution, and time resolution to measure the neutron time and energy spectra with sufficient precision to improve our understanding of the basic flare processes. Over the past two decades a variety of neutron detectors has been flown to measure the atmospheric neutron intensity above 10 MeV and to search for solar neutrons. The SONTRAC (Solar Neutron Track Chamber) detector, a new type of neutron detector which utilizes n-p scattering and has a sensitivity 1-3 orders of magnitude greater than previous instruments in the 20-200 MeV range is described. The energy resolution is 1% for neutron kinetic energy, T sub n 50 MeV. When used with a coded aperture mask at 50 m (as would be possible on the space station) an angular resolution of approx. 4 arc sec could be achieved, thereby locating the sites of high energy nuclear interactions with an angular precision comparable to the existing x-ray experiments on SMM. The scintillation chamber is investigated as a track chamber for high energy physics, either by using arrays of scintillating optical fibers or by optical imaging of particle trajectories in a block of scintillator.

Frye, G. M., Jr.↗
DOE OSTI2022

High Efficiency Heat Pumps Can Pave the Path for Building Decarbonization in Cold Climates: Preprint

Heat pumps play an instrumental role in buildings decarbonization strategies. Recent advances in heat pump systems employ variable-speed compressor technology and electronically commutated fan motors. Inherently, the heating capacity and efficiency of heat pumps decrease with falling outdoor temperatures. Compared to single-speed heat pumps, variable speed systems can maintain higher heating and cooling efficiencies over a wider range of outdoor temperatures. The goal of this multi-phase project was to determine the energy savings of a high efficiency, variable-speed, air-source, split system heat pump designed for cold climate applications. The first project phase was to evaluate the performance of the heat pump in the laboratory under varying outdoor conditions in heating and cooling modes. The second phase was to translate the laboratory-measured performance into lookup tables for EnergyPlus hourly building simulation engine. Then, two sets of annual building simulations were performed using typical meteorological year weather from the Chicago-O'Hare airport for three different building types (a single-family residence, a strip mall, and a low-rise office building). The first set simulated a standard efficiency heat pump while the second set utilized the phase two performance tables to model a high efficiency heat pump. The high efficiency heat pump produced significant annual heating energy savings in all three buildings. The variable speed compressor and fan control also contributed to cooling energy savings. The simulated annual energy savings ranged from 22% to 35% over their respective baseline. The project's findings helped a Midwest electric utility, Commonwealth Edison (ComEd), design new incentives around high efficiency heat pumps.

cold climate heat pump↗
DOE OSTI2022

Price Formation and Grid Operation Impacts from Variable Renewable Energy Resources

Increasing amounts of Variable Renewable Energy Resources (VREs) impact electricity markets and their operation. VREs are intermittent, zero marginal cost resources that tend to displace emissions-intensive generators in electricity dispatch, reducing emissions, but impacting price formation, revenue sufficiency, reliability, and market power mitigation processes of electricity markets. But VREs are not the only factor that affects operational and financial challenges in electricity markets. Declining natural gas prices, changing resource mixes, as well as different electricity market designs and regulatory policies all factor into the challenges both electricity market participants and operators face in today’s electricity markets. With this in-depth examination of electricity markets and related literature review, we aim to inform on key challenges of market design and operation for successful integration of large amounts of zero marginal cost resources. We’ve identified several areas, including VREs impact on price formation, revenue sufficiency, reliability, market power monitoring and mitigation, as well as how state-level incentives and market design impact VREs and these challenges. With each key challenge, we survey the literature to answer the question: To what extent is the problem, and how has it evolved over time? We first conduct a thorough review of ongoing challenges in electricity markets to understand the problem and review the empirical literature to capture important findings on how VREs, specifically, impact the problem. From this review, we highlight metrics that are important to understanding VRE integration and how market designs and outcomes are evolving with increasing levels of VREs. We propose several empirical models for future research to determine the impact of VREs on these identified challenges.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Inducing the adoption of emerging technologies for sustainable intensification of food and renewable energy production: insights from applied economics

Emerging advances in sustainable intensification technologies have the potential to transform land use and crop management approaches in ways that can increase resource productivity and reduce adverse environmental impacts of agricultural production. This paper describes emerging technologies that can sustainably intensify food and renewable energy production. We apply the findings from studies examining the adoption of technologies with similar stylized features to provide insights about the incentives and barriers for the adoption of these emerging technologies. We also present a landscape-based systems approach, based on welfare economics, to go beyond relying on a positive approach to explain observed adoption decisions to examining normative questions about the optimal mix, level, and location of adoption of these technologies to achieve desired societal outcomes. Here, we conclude with a discussion of the insights from applied economics for the design of policy incentives to achieve these outcomes.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2002

Advanced Engine Cycles Analyzed for Turbofans With Variable-Area Fan Nozzles Actuated by a Shape Memory Alloy

Advanced, large commercial turbofan engines using low-fan-pressure-ratio, very high bypass ratio thermodynamic cycles can offer significant fuel savings over engines currently in operation. Several technological challenges must be addressed, however, before these engines can be designed. To name a few, the high-diameter fans associated with these engines pose a significant packaging and aircraft installation challenge, and a large, heavy gearbox is often necessary to address the differences in ideal operating speeds between the fan and the low-pressure turbine. Also, the large nacelles contribute aerodynamic drag penalties and require long, heavy landing gear when mounted on conventional, low wing aircraft. Nevertheless, the reduced fuel consumption rates of these engines are a compelling economic incentive, and fans designed with low pressure ratios and low tip speeds offer attractive noise-reduction benefits. Another complication associated with low-pressure-ratio fans is their need for variable flow-path geometry. As the design fan pressure ratio is reduced below about 1.4, an operational disparity is set up in the fan between high and low flight speeds. In other words, between takeoff and cruise there is too large a swing in several key fan parameters-- such as speed, flow, and pressure--for a fan to accommodate. One solution to this problem is to make use of a variable-area fan nozzle (VAFN). However, conventional, hydraulically actuated variable nozzles have weight, cost, maintenance, and reliability issues that discourage their use with low-fan-pressure-ratio engine cycles. United Technologies Research, in cooperation with NASA, is developing a revolutionary, lightweight, and reliable shape memory alloy actuator system that can change the on-demand nozzle exit area by up to 20 percent. This "smart material" actuation technology, being studied under NASA's Ultra-Efficient Engine Technology (UEET) Program and Revolutionary Concepts in Aeronautics (RevCon) Program, has the potential to enable the next generation of efficient, quiet, very high bypass ratio turbofans. NASA Glenn Research Center's Propulsion Systems Analysis Office, along with NASA Langley Research Center's Systems Analysis Branch, conducted an independent analytical assessment of this new technology to provide strategic guidance to UEET and RevCon. A 2010-technology-level high-spool engine core was designed for this evaluation. Two families of low-spool components, one with and one without VAFN's, were designed to operate with the core. This "constant core" approach was used to hold most design parameters constant so that any performance differences between the VAFN and fixed nozzle cycles could be attributed to the VAFN technology alone. In this manner, the cycle design regimes that offer a performance payoff when VAFN's are used could be identified. The NASA analytical model of a performance-optimized VAFN turbofan with a fan pressure ratio of 1.28 is shown. Mission analyses of the engines were conducted using the notional, long-haul, advanced commercial twinjet shown. A high wing design was used to accommodate the large high-bypassratio engines. The mission fuel reduction benefit of very high bypass shape-memory-alloy VAFN aircraft was calculated to be 8.3 percent lower than a moderate bypass cycle using a conventional fixed nozzle. Shape-memory-alloy VAFN technology is currently under development in NASA's UEET and RevCon Programs.

Berton, Jeffrey J.↗
NASA NTRS1988

Fault tolerant system performance modeling

With the proliferation of complex digital systems on aircraft, the need to accurately predict system performance early in the system design cycle becomes imperative. In the past, system designers have relied on ad hoc methods for evaluating performance issues. This has produced systems that have not always worked as originally intended. To alleviate these design deficiencies, formal methods, with supporting tools, must be adhered to during the system design process. The use of performance modeling tools is becoming widely accepted as a way to address timing considerations of system design. An additional incentive for the use of these tools is that they allow the system architect to analyze system component interactions (i.e., bus contention, contention of functions for a processing site, and system repair activity on application performance). This inherent flexibility can result in an explicit specification of the system architecture. This paper addresses a method that supports performance modeling of fault tolerant systems using a discrete event simulation tool. An additional focus is on lessons learned from analyzing these classes of problems. The methodology and supporting work provide system architects with the capability to specify candidate architectures and accurately predict their performance in the early stages of design, where changes to system design is most cost effective. The work has been supported under NASA contract NAS1-18099. Integrated Airframe Propulsion Control System Architecture (IAPSA II). This contract addresses methodology, analysis, and detailed design of integrated control system architectures suitable for high-performance aircraft of the 1990's.

Discrete event simulation↗
DOE OSTI2025

Rethinking agrivoltaic incentive programs: A science-based approach to encourage practical design solutions

Agrivoltaic systems are promising solutions to address global food and energy challenges by combining agriculture and solar photovoltaics. However, the lack of appropriate regulations to define and guide their implementation constrains the growth of agrivoltaic systems in the U.S. This study uses a shading and radiation tool to evaluate an existing agrivoltaic incentive program that defines agrivoltaic designs based on shading reduction limits and panel height requirements. Our analysis indicates that structuring policy requirements around shading, and not light availability, may lead to an underestimation of crop suitability by neglecting diffuse radiation. Furthermore, we show that agrivoltaic systems can avoid increasing panel height if policy acknowledges use-case scenarios where farming only occurs between rows. In light of these insights, this study proposes two key policy recommendations: (1) benchmark crop suitability based on daily light integral (DLI) requirements for a shade-intolerant crop selected to represent a prevalent crop in the region, and (2) include an incentive scenario where agriculture is only required between rows. Furthermore, these two recommendations can potentially incentivize designs that are practical and closer in cost to conventional solar farms, thereby accelerating the adoption of cost-effective agrivoltaic systems.

14 SOLAR ENERGY↗
DOE OSTI2024

Industrial Assessment Center

Established in 1990, San Diego State University’s (SDSU) Industrial Assessment Center (IAC) is proud of its years of service. During this period, it has served over 620 small and medium-sized manufacturing plants in Southern California. SDSU/IAC’s efforts to transfer state-of-the-art technologies to industry have increased revenues, cultivated creativity, improved energy efficiencies, and benefited the environment. The Center has contributed to the region's economic growth and stability by assisting small and medium size companies to better compete in the global market. It has helped mitigate climate change by reducing greenhouse gas emissions. IAC activities have fostered productive relationships between the University and local industry, assisted industrial sectors to improve their energy efficiency and enhance their manufacturing productivity, in turn impacting the material and working conditions of their employees. In addition to financial savings and environmental benefits, we have trained tens of students who became energy specialists in various companies. Thus, a substantial benefit of the IAC has been the ongoing training of engineering faculty and students. All IAC graduates were offered jobs before or within weeks of their graduation. The activities of the SDSU/IAC have expanded the institutional expertise of the College and improved the knowledge base of the faculties involved leading to several related publications, master’s theses, and senior student projects. Significant number of peer-reviewed publications of the IAC director at SDSU have greatly benefitted from the experience of the Center. As a result of this extensive exposure to manufacturing processes, the SDSU/IAC has grown to be an integral component of SDSU’s engineering research and training. We have successfully built upon these established achievements and academic excellence. IAC service to industry is particularly vital in Southern California, a region with one of the highest manufacturing concentrations in the country. SDSU/IAC has understood and implemented the overall objectives of DOE’s IAC program and guidelines except for the pandemic years when the country’s manufacturing sector was put in dire stress. In addition to student training and service to industry, IAC’s contribution to state and local governments as well as utility companies to assess energy policies and design rebate and incentive strategies cannot be undermined.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗