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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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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

HIPPO – A Software Platform for Electricity Market Research and Development

The goal of this project is to provide Regional transmission organizations (RTOs) and independent system operators (ISOs) a market design and prototyping software, High-Performance Power-Grid Optimization (HIPPO), that they can evaluate electricity market design options, calculate market planning strategies and operational performance. With the high standards and strict reliability requirements for operating power systems, impacts of new technologies need to be fully investigated prior to any consideration for adoption. A market design and prototyping software tool which can be used to prototype electricity market design options, to calculate market planning strategies and operational performance with high precision, and to investigate the impacts for integrating future power grid technologies will be valuable to RTOs/ISOs who operate power systems, to vendors like GE and ABB who provide the market solvers, and to market participants and researchers who are actively doing market research. HIPPO is a such tool that can be used to improve the current market operations and provide capabilities for rigorous forward-looking design and prototyping of next-generation energy markets. HIPPO has a high-resolution model for the day-ahead SCUC, which was validated with MISO and GE-Grid Solutions. HIPPO is built with parallel and distributed computing capabilities and can be executed in both multi-thread and high-performance computing (HPC) settings. This capability provides fast solution speed necessary to handle the larger and more complex SCUC problems of real-world cases and the potentially growing size and complexity of future scenarios. In addition, HIPPO has a concurrent optimizer (CO) which manages multiple algorithm executions simultaneously and leverages the advantages from different algorithms. This structure provides flexibility to better benchmark competing approaches. Highly accurate market model, fast solution technologies and flexible model and algorithm control are the features which will make HIPPO an extensible platform for developing and testing multiple approaches to meet a wide range of future market needs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

SMR Current Status: Development Needs and Global Perspectives

Defined as nuclear reactors with a power output up to 300 megawatts electrical (MWe) by the International Atomic Energy Agency (IAEA) and targeted for multipurpose applications, small modular reactors (SMRs) have been recognized as a very promising, clean, affordable, and sustainable energy source by many countries. At present, more than 80 SMRs are under design, development, demonstration, deployment, and beyond (4D+) phases worldwide. This study focuses on the current world status of SMRs and focuses on the necessary developments to accelerate the process of adopting SMRs as a major energy source globally. SMRs are not a new concept, but they do represent a new vision for older concepts if the challenges inherent within them are mitigated with strategic and realistic solution approaches. The major challenges for SMRs 4D+ like any new reactors are: (a) qualifying the advanced fuel-to-reactor design; (b) supporting rapid scaled/prototypic experimentations; (c) maintaining local and global codes, standards, and licensing; (d) supply chain issues;(e) effective cradle-to-grave nuclear fuel cycle and fuel material transportation, and (f) mitigating financial and environmental risks. These upfront challenges can be mitigated with a synergistic solution approach among the various stakeholders: industry, academia, research, government, and international entities.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Presentation: SMR Current Status: Development Needs and Global Perspectives

Defined as nuclear reactors with a power output up to 300 megawatts electrical (MWe) by the International Atomic Energy Agency (IAEA) and targeted for multipurpose applications, small modular reactors (SMRs) have been recognized as a very promising, clean, affordable, and sustainable energy source by many countries. At present, more than 80 SMRs are under design, development, demonstration, deployment, and beyond (4D+) phases worldwide. This paper focuses on the current world status of SMRs and focuses on the necessary developments to accelerate the process of adopting SMRs as a major energy source globally. SMRs are not a new concept, but they do represent a new vision for older concepts if the challenges inherent within them are mitigated with strategic and realistic solution approaches. The major challenges for SMRs 4D+ like any new reactors are: (a) qualifying the advanced fuel-to-reactor design; (b) supporting rapid scaled/prototypic experimentations; (c) maintaining local and global codes, standards, and licensing; (d) supply chain issues; (e) effective cradle-to-grave nuclear fuel cycle and fuel material transportation, and (f) mitigating financial and environmental risks. These upfront challenges can be mitigated with a synergistic solution approach among the various stakeholders: industry, academia, research, government, and international entities.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

SMR Current Status: Development Needs and Global Perspectives

Defined as nuclear reactors with a power output up to 300 megawatts electrical (MWe) by the International Atomic Energy Agency (IAEA) and targeted for multipurpose applications, small modular reactors (SMRs) have been recognized as a very promising, clean, affordable, and sustainable energy source by many countries. At present, more than 80 SMRs are under design, development, demonstration, deployment, and beyond (4D+) phases worldwide. This study focuses on the current world status of SMRs and focuses on the necessary developments to accelerate the process of adopting SMRs as a major energy source globally. SMRs are not a new concept, but they do represent a new vision for older concepts if the challenges inherent within them are mitigated with strategic and realistic solution approaches. The major challenges for SMRs 4D+ like any new reactors are: (a) qualifying the advanced fuel-to-reactor design; (b) supporting rapid scaled/prototypic experimentations; (c) maintaining local and global codes, standards, and licensing; (d) supply chain issues;(e) effective cradle-to-grave nuclear fuel cycle and fuel material transportation, and (f) mitigating financial and environmental risks. These upfront challenges can be mitigated with a synergistic solution approach among the various stakeholders: industry, academia, research, government, and international entities.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

A safe reinforcement learning algorithm for supervisory control of power plants

Traditional control theory-based methods require tailored engineering for each system and constant fine-tuning. In power plant control, one often needs to obtain a precise representation of the system dynamics and carefully design the control scheme accordingly. Model-free Reinforcement learning (RL) has emerged as a promising solution for control tasks due to its ability to learn from trial-and-error interactions with the environment. It eliminates the need for explicitly modeling the environment’s dynamics, which is potentially inaccurate. However, the direct imposition of state constraints in power plant control raises challenges for standard RL methods. To address this, we propose a chance-constrained RL algorithm based on Proximal Policy Optimization for supervisory control. Our method employs Lagrangian relaxation to convert the constrained optimization problem into an unconstrained objective, where trainable Lagrange multipliers enforce the state constraints. In conclusion, our approach achieves the smallest distance of violation and violation rate in a load-follow maneuver for an advanced Nuclear Power Plant design.

constrained optimization↗
DOE OSTI2023

Virtual Community Trains

When access to transit solutions is restricted to parts of a community, a division occurs what leads to disadvantaged socioeconomic conditions that only grows over time. This restriction causes difficulties in accessing needed resources such as medical facilities, employment, healthy food, education, healthy food, and more. To solve this restricted access, Labyrinth Smart Mobility and partners are developing a virtual community train that encourages scalability, energy efficiency, and equitability to all regardless of individual circumstances and limitation. The implementation of virtual community trains allows access to resources previously out of reach. The virtual community train enables one operator to drive a lead vehicle. This lead vehicle would then provide direction to a follow vehicle through vehicle-to-vehicle communication. Labyrinth Smart Mobility in conjunction with partners used various methods and resources to prove market feasibility, technical feasibility, economic need and viability, and more as well as design system requirements and architecture emphasis efficiency and safety. In doing so, Labyrinth Smart Mobility and partners will continue these advancements to further develop the virtual community train.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2019

Highlighting Recent Uses of the NASA Worldview Mapping Application

NASA’s Worldview (https://worldview.earthdata.nasa.gov/) web mapping application from the Earth Observing System Data and Information System (EOSDIS) provides a low friction solution for users of different scientific backgrounds to access satellite imagery and data products. Worldview uses imagery from the Global Imagery Browse Services (GIBS), which has an increasing catalog of 800+ products serving global, full-resolution satellite imagery from NASA’s Earth observing fleet. NASA promotes the open sharing of all data with researchers, private industry, academia, and the general public. Worldview encourages this open data policy. Numerous general news publications feature Worldview for its unique imagery. Worldview also helps scholarly research in identifying field research locations, mapping thermal hotspots of active burning fires, and visualizing theoretical models of weather storm systems amongst other uses. This presentation shares some recent uses of Worldview which highlight its capabilities.

Plato, Edward A.↗
NASA NTRS2019

Highlighting Recent Uses of the NASA Worldview Mapping Application

NASA’s Worldview (https://worldview.earthdata.nasa.gov/) web mapping application from the Earth Observing System Data and Information System (EOSDIS) provides a low friction solution for users of different scientific backgrounds to access satellite imagery and data products. Worldview uses imagery from the Global Imagery Browse Services (GIBS), which has an increasing catalog of 800+ products serving global, full-resolution satellite imagery from NASA’s Earth observing fleet. NASA promotes the open sharing of all data with researchers, private industry, academia, and the general public. Worldview encourages this open data policy. Numerous general news publications feature Worldview for its unique imagery. Worldview also helps scholarly research in identifying field research locations, mapping thermal hotspots of active burning fires, and visualizing theoretical models of weather storm systems amongst other uses. This presentation shares some recent uses of Worldview which highlight its capabilities.

Plato, Edward A.↗
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

Design and optimization of a modular hydrogen-based integrated energy system to maximize revenue via nuclear-renewable sources

Here, this paper demonstrates a novel modular distributed framework that uses optimal energy-dispatching strategies to enable greater flexibility and profitability in nuclear-renewable integrated energy systems (NR-IES). Hydrogen is used as a commodity in this framework since its production can improve grid stability and system operational flexibility, decarbonize heavy industry, and create an additional revenue stream for electricity generators, particularly nuclear power plants with high operational expenses. The proposed solution addresses the challenges associated with merging multiple software and services from various domains by using functional mock-up units (FMU) to co-simulate diverse subsystems designed in various platforms. The tightly coupled integrated energy system (IES) is optimized to maximize revenue by utilizing the deep reinforcement learning (DRL) technique to make smart dispatching decisions based on variable electricity prices and the availability of renewable energy. Proximal policy optimization (PPO) algorithm is used in training and testing the DRL agent. Over a period of 120 days, the proposed hydrogen-based IES framework showed about 10% revenue boost compared to a non-hydrogen generating baseline IES while also providing an easily-adoptable framework which can help to improve the flexibility of future generation nuclear power plants.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Resilience Valuation and Planning for Solar and Storage on Critical Infrastructure

This case study report documents the City's project evolution and the entrepreneurial ways through which the City approached the questions of how solar and storage could support their resilience efforts and how to value and pay for solar-plus-storage systems. This report documents how and why the City of Reno came to the specific conclusion to integrate solar and storage into their Public Safety Center retrofit project and apply for Federal Emergency Management Agency (FEMA) Building Resilient Infrastructure and Communities (BRIC) funding. (The City of Reno applied for and was awarded FEMA BRIC funding in January 2021; leveraging work that was underway in this project.) This report provides an overview for other local governments to draw inspiration from when considering how to prioritize community values and pursue multi-stakeholder dialogue around resilient energy solutions. The City of Reno's experience can serve as a starting point for other communities interested in valuing the resilience benefits of solar and storage.

14 SOLAR ENERGY↗
NASA NTRS2013

Access Control of Web- and Java-Based Applications

Cybersecurity has become a great concern as threats of service interruption, unauthorized access, stealing and altering of information, and spreading of viruses have become more prevalent and serious. Application layer access control of applications is a critical component in the overall security solution that also includes encryption, firewalls, virtual private networks, antivirus, and intrusion detection. An access control solution, based on an open-source access manager augmented with custom software components, was developed to provide protection to both Web-based and Javabased client and server applications. The DISA Security Service (DISA-SS) provides common access control capabilities for AMMOS software applications through a set of application programming interfaces (APIs) and network- accessible security services for authentication, single sign-on, authorization checking, and authorization policy management. The OpenAM access management technology designed for Web applications can be extended to meet the needs of Java thick clients and stand alone servers that are commonly used in the JPL AMMOS environment. The DISA-SS reusable components have greatly reduced the effort for each AMMOS subsystem to develop its own access control strategy. The novelty of this work is that it leverages an open-source access management product that was designed for Webbased applications to provide access control for Java thick clients and Java standalone servers. Thick clients and standalone servers are still commonly used in businesses and government, especially for applications that require rich graphical user interfaces and high-performance visualization that cannot be met by thin clients running on Web browsers

Tso, Kam S.↗
DOE OSTI2021

Accelerating Clean Energy @Scale: Place-Based Solutions

Customized, holistic energy modeling and analysis is conducted across a wide range of geospatial scales -- from global to local. We will describe the value and importance of local, place-based solutions, particularly, how scientific insights, decision support, and technical assistance based on integrated, customized modeling and analysis, and in-depth stakeholder engagement can assist communities in translating their ambitions into implementable action plans.

clean energy↗
DOE OSTI2024

B-Biz: Building Business Network

The Building Business Network (B-Biz) aims to provide high-performance building technology solutions to underserved customers by collaborating with local small businesses that provide and service high-performance building technologies in communities with the lowest rates of adoption.

BTO↗
DOE OSTI2022

Optimal economic dispatch policy for prosumer with energy storage considering self-consumption demand

This paper analyzed the effects of self-consumption demand on the joint economic dispatch of prosumers (energy consumers who are also producers), particularly for prosumers with both energy storage and distributed energy sources (DERs). Studies in the existing literature on the economic dispatch scheduling policy of energy storage, mostly from the perspective of electricity merchants, do not address the impacts of self-consumption demand. However, due to the intermittent and high levels of uncertainty regarding DERs generation and the dynamic demand of the prosumer, production and consumption are not always simultaneous; there are two possible scenarios in each period depending on whether DERs generation can meet prosumers' self-consumption or not. Incorporating the self-consumption demand will pose modeling challenges since these two scenarios cannot occur simultaneously in each period, and different scenarios require different decisions for prosumers. Further, this paper analyzed the two scenarios separately to find the optimal storage scheduling strategy, and the results were combined to get the optimal global solution. We focused on prosumers' economic decision-making while considering self-consumption demand and the physical constraints of a battery based on dynamic programming. Our study showed that the feasible state of charge (SOC) range of storage can be segmented into several sub-ranges by SOC reference points under the above two scenarios. As a result, a prosumer's optimal scheduling can be uniquely and conveniently selected based on the sub-ranges within which the current SOC falls. The results, therefore, provided multistage decision-making guidance for prosumers with energy storage.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Artificial-intelligence-driven shot reduction in quantum measurement

Variational Quantum Eigensolver (VQE) provides a powerful solution for approximating molecular ground state energies by combining quantum circuits and classical computers. However, estimating probabilistic outcomes on quantum hardware requires repeated measurements (shots), incurring significant costs as accuracy increases. Optimizing shot allocation is thus critical for improving the efficiency of VQE. Current strategies rely heavily on hand-crafted heuristics requiring extensive expert knowledge. This paper proposes a reinforcement learning (RL)-based approach that automatically learns shot assignment policies to minimize total measurement shots while achieving convergence to the minimum of the energy expectation in VQE. The RL agent assigns measurement shots across VQE optimization iterations based on the progress of the optimization. This approach reduces VQE's dependence on static heuristics and human expertise. When the RL-enabled VQE is applied to a small molecule, a shot reduction policy is learned. The policy demonstrates transferability across systems and compatibility with other wavefunction Ansätze. In addition to these specific findings, this work highlights the potential of RL for automatically discovering efficient and scalable quantum optimization strategies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Defining Infrastructure Feasibility for Hub-Scale Offshore Atlantic Carbon Storage in the Northeastern United States

In the Northeast U.S., deep rock formations along the Atlantic outer continental shelf may have the potential to sequester 150–1136 million metric tons of CO2. However, the design and infrastructure necessary to develop offshore carbon storage in this region is not well defined because there has been little oil and gas exploration and no commercial production. Consequently, an infrastructure feasibility design was completed for a hub-scale offshore CO2 storage system along the Northeast U.S. Atlantic. The design included development of a detailed, site-specific geological model for a location near the Great Stone Dome geological structure in the Baltimore Canyon Trough off the coast of Delaware, Maryland, and New Jersey. A field injection system topology design was completed to portray a design with eight wells in two clusters connected by central manifolds. Reservoir simulations were completed for the injection system that showed the hub may be able to inject 17 million metric tons (MMT) of CO2 per year for thirty years, but injection rates varied substantially across the eight wells. A CO2 pipeline design determined feasible routes from the east coast shoreline to the injection field. Finally, the CO2 injection system design included subsea injection trees, manifolds, and power umbilicals. This is the first study to define large-scale carbon storage design and infrastructure options for the offshore Atlantic, which can help to progress this region towards field characterization and early-mover deployment for future decarbonization in the region.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗