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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Enhancing Power Resilience for Remote Communities: A Comprehensive Renewable Energy Solution for Itbayat Island

The island of Itbayat, Philippines, faces significant challenges in maintaining a reliable and resilient power supply due to its current reliance on a vulnerable power distribution system managed by a local electric cooperative. The existing infrastructure, which includes diesel generators and a radial network configuration with some above-ground lines, is highly susceptible to frequent typhoons and adverse weather conditions. These factors, combined with inadequate staffing and high operational costs, result in frequent power outages that disrupt daily life and hinder economic development. This white paper proposes a comprehensive solution to enhance the resilience and reliability of Itbayat's power system by integrating renewable energy sources, specifically solar photovoltaic (PV) systems, battery storage, and a microgrid controller. The proposed solution aims to reduce dependency on diesel fuel, optimize energy use, and provide a sustainable and robust power supply for the island. Key components of the solution include: 1. Solar PV Installation: Deploying solar PV panels to harness abundant solar energy, reducing reliance on diesel fuel. 2. Battery Storage Systems: Installing battery storage to store excess solar energy and ensure a continuous power supply during low solar generation periods. 3. Microgrid Controller: Implementing a microgrid controller to manage and optimize the integration of solar PV, battery storage, and existing diesel generators. The proposed solution addresses several critical issues, including system vulnerability, generator dependency, and operational inefficiencies. By adopting this innovative approach, Itbayat Island can achieve a more resilient, efficient, and sustainable energy infrastructure, ensuring a stable power supply for its residents and enhancing overall energy security.

14 SOLAR ENERGY↗
DOE OSTI2026

A Community Guide to Regulatory Barriers Affecting Microgrids (Reports 1-3)

In response to growing risks of power outages from extreme weather and aging infrastructure, communities are increasingly exploring the potential of microgrids to provide reliable energy access. Microgrids offer promising solutions to meet this challenge but face a complex landscape of non-technical barriers, particularly regulations concerning the provision and distribution of energy. Most existing legal and regulatory frameworks were designed for a centralized, one-way power system, and are often poorly suited to handle systems that independently balance distributed energy resources with local load. This three-part report series provides a strategic analysis of existing regulatory and legal factors affecting microgrid deployments to help non-technical community leaders and decision-makers better understand the feasibility of a microgrid in their community. -Report No. 1: Foundational Issues Facing Microgrids details the universal policy barriers all microgrids face, including utility interconnection processes, rate structures, and local permitting. -Report No. 2: Single Property Microgrids outlines how direct asset ownership and operating behind-the-meter can bypass some regulatory oversight, using the Blue Lake Rancheria microgrid as a case study. -Report No. 3: Multi-Property Microgrids tackles the complex challenges of crossing public rights-of-way and navigating utility franchise rights, highlighting the Coventry microgrid project. The series equips decision-makers with phased frameworks to navigate financial and regulatory complexities, engage effectively with local utilities and Authorities Having Jurisdiction (AHJs), and structure successful microgrid projects.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Supply Chain for Energy Technologies

Understanding manufacturing cost implications of technologies is critical to aid adoption of next-generation energy solutions. It is important to understand not only of the manufacturing costs and value-add along the supply chain, but also gain understanding of manufacturing location decisions. By identifying a technology's competitive strengths and weaknesses, analyses give researchers and program decision makers the data and insights needed to create strategies and plans that better promote U.S. economic growth and pursue R&D activities that have the greatest long-term potential to yield significant energy savings for U.S. consumers. In this talk, we present examples of analysis from a variety of energy technologies to demonstrate how manufacturing cost analysis can be used to answer specific policy or research questions. In addition, we present case studies showing the importance of understanding trade flow, manufacturing locations, and capacity and utilization to inform economic growth and potential for technology adoption.

benchmarking↗
DOE OSTI2023

Decision making for implementing non-traditional water sources: a review of challenges and potential solutions

Abstract The effects of climate change, population growth, and future hydrologic uncertainties necessitate increased water conservation, new water resources, and a shift towards sustainable urban water supply portfolios. Diversifying water portfolios with non-traditional water sources can play a key role. Rooftop harvested rainwater (RHRW), atmospheric and condensate harvesting, stormwater, recycled wastewater and greywater, and desalinated seawater and brackish water are all currently utilized and rapidly emerging non-traditional water sources. This review explores the status and trends around these non-traditional water sources, and reviews approaches and models for prioritizing, predicting, and quantifying metrics of concern. The analysis presented here suggests that understanding the challenges of location specific scenarios, socioeconomic knowledge gaps, water supply technologies, and/or water management structure is the crucial first step in establishing a model or framework approach to provide a strategy for improvement going forward. The findings of this study also suggest that clear policy guidance and onsite maintenance is necessary for variable water quality concerns of non-traditional sources like harvested rainwater and greywater. In addition, use of stormwater or reuse of wastewater raises public health concerns due to unknown risks and pathogen levels, thus rapid monitoring technologies and transparent reporting systems can facilitate their adoption. Finally, cost structure of desalination varies significantly around the world, largely due to regulatory requirements and local policies. Further reduction of its capital cost and energy consumption is identified as a hurdle for implementation. Overall, models and process analyses highlight the strength of comparative assessments across scenarios and water supply options.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

A Two-Stage Quantum Reinforcement Learning Method for Multi-Objective Transmission Switching

Multi-objective transmission switching (MO-TS) problems involve the strategic reconfiguration of network topology to simultaneously optimize multiple objectives. As the system scale increases, finding feasible solutions becomes increasingly challenging due to the problem's nonlinearity and high computational complexity. To address these challenges, this paper proposes a two-stage quantum reinforcement learning method that leverages potential quantum advantages for MO-TS. In the first stage, candidate switching lines are identified using a graph-theoretical approach to reduce the problem's dimensionality. The second stage introduces a quantum-classical reinforcement learning framework, where a learnable measurement-based CNN-ResVQC architecture is developed to effectively reduce the input dimension for quantum processing, mitigate vanishing gradients, and enhance trainability while improving the quantum circuit's flexibility in modeling complex decision policies for MO-TS. Numerical studies on IEEE 14-bus, 57-bus, and 118-bus systems demonstrate that the proposed algorithm achieves superior training stability and faster convergence with approximately 1% of the network parameters required by classical algorithms, highlighting its effectiveness, efficiency, and scalability. Furthermore, the practicality is validated through its stable convergence under three common quantum noise channels.

99 GENERAL AND MISCELLANEOUS↗
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 OSTI2024

EVI-LOCATE: One Stop Solution for Estimating Cost of Installing EV Charging Stations

EVI-LOCATE (Electric Vehicle Infrastructure-Locally Optimized Cost Assessment Tool and Estimator) is a site assessment tool to estimate costs to install EV charging stations. EVI-LOCATE enables users to generate site-specific, user-specific, and location-specific EV charging station installation designs and cost estimates. The tool integrates National Electrical Code, deep-learning pixel classification algorithm, and component-level costs to estimate the costs.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2023

ES4SE Technical Assistance Program Evaluation

Technical assistance (TA) programs can provide organizations and communities with the information, tools, and resources needed to support their development and resilience goals. The Energy Storage for Social Equity (ES4SE) TA program sought to empower undeserved communities through co-development of energy storage pathways and solutions to address community-defined challenges and needs. Evaluating the design, implementation, and outcomes of TA programs like ES4SE is critical to understanding whether program and participant goals were accomplished and how to adjust the TA approach to better meet participant needs. This evaluation explores the experiences and perceptions of community participants in the ES4SE TA program.

25 ENERGY STORAGE↗
DOE OSTI2024

Technoeconomic Analysis of Kraft Pulp Mill Integration with an Advanced Nuclear Reactor

This study focuses on post-combustion capture and oxy-fuel combustion for the boilers at the mill, as well as steam integration with the nuclear power plant. The primary goal of the research outlined in this report is to design, analyze, and document the integration of industrial-scale HTGR with a reference Kraft Pulp Mill. The purpose is to deliver reliable, cost-effective, and sustainable clean energy alternatives while reducing CO2 emissions. Specifically, this study focuses on 6 different scenarios that include carbon capture equipment and some of them use nuclear power to meet the heat and electricity needs of the reference plant. Also, 2 of these scenarios are created while also producing clean hydrogen through integrated High-Temperature Steam Electrolysis (HTSE). This report offers a detailed techno-economic assessment of different scenarios for a Kraft Pulp Mill, including an analysis of tax credits (section 45V, 45Q, and 48E) provided by the Inflation Reduction Act (IRA) of 2022. The evaluation explores the potential economic benefits and challenges of incorporating different configurations, including nuclear energy, into Kraft Pulp Mill operations, with particular attention to energy efficiency, economic implications, and environmental impact. By assessing both the technical feasibility and economic viability, this analysis aims to identify existing gaps and propose solutions for the successful implementation of nuclear integration. The findings are intended to provide valuable insights for stakeholders considering the adoption of advanced nuclear reactors in the pulp and paper industries.

08 HYDROGEN↗
DOE OSTI2020

Improving the Cyber Resiliency and Security Posture of Public Power (Final Report)

The key objective of Improving the Cyber Resiliency and Security Posture of Public Power (Project) was to develop a culture of cyber resiliency and security within the public power community. The relative smaller size and unique structure of community-owned electric utilities can sometimes present challenges in immediate recognition of threats and the escalation of potential incidents. The Project offered targeted education, coordination, capability building, and resources to help the public power community better understand, install, and implement cyber and physical resiliency and security systems. The American Public Power Association (APPA) accelerated efforts to develop resources for and with the public power community to understand and implement resiliency, cybersecurity and cyber-physical solutions, including refining and improving the adoption of advanced control concepts. The Project consisted of four major multi-pronged tasks which included: 1) Advance cyber resiliency and security assessments; 2) Conduct, evaluate, and use the results of onsite vulnerability assessments; 3) Research, evaluate, deploy, and integrate both commercial and pre-commercial security technologies; and 4) Research, evaluate, and implement information sharing mechanisms.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Integrating Multi-Source Data for Bi-Level Traffic Simulator Calibration: A Literature Review and Highway Case Study

Traffic simulation serves as a powerful tool for pre-evaluating policies and technologies. In this context, simulation-based Dynamic traffic assignment (DTA) models are capable of capturing traffic dynamics. They are well-known as critical tools in controlling and predicting traffic situations. The reliability of simulation results heavily depends on the calibration process. Most studies in the literature formulate and calibrate simulators based on a single source of collected data or multiple data sets with the same spatiotemporal characteristics. However, in practice, traffic data is collected by various tools with usually different spatial and temporal resolutions. This study introduces a novel approach to taking into account diverse input data from a variety of sources. An iterative bi-level solution is proposed. to equally treat traffic flow and speed data. The upper level solves flow calibration with the exact solution method, and the lower level calibrates the speed with the simultaneous perturbation stochastic approximation (SPSA) algorithm. Subsequently, the effectiveness of the proposed model is investigated using data from a six-mile section of Nashville's I-24 highway in Tennessee. The results demonstrate that our proposed model creates an effective feedback loop between the optimizer and the simulator for calibrating flow and speed to reduce the error between simulated and real data.

42 ENGINEERING↗
DOE OSTI2023

A hybrid data-driven and model-based approach for computationally efficient stochastic unit commitment and economic dispatch under wind and solar uncertainty

Stochastic unit commitment (UC) and economic dispatch (ED) are imperative in dealing with uncertainty in renewable forecast for power system operation and planning such that the overall expected production cost is minimized over the planning horizon. However, accurate calculation of the expected production cost requires assessment of a very large number of different scenarios of uncertain renewable resources, such as solar and wind, which is practically infeasible to simulate in real time. This article proposes a hybrid datadriven and physics-based model-predictive paradigm to efficiently solve for stochastic unit commitment and economic dispatch considering uncertainty in wind and solar power forecasts. Here, the novelty of the approach lies in decoupling the production cost estimation from the unit commitment and economic dispatch optimization problems under uncertainty without compromising on the fidelity of the solutions. A data-driven machine learning model is first developed to predict the mean optimal production cost. A physics-based inverse problem is then solved to get the stochastic UC and ED profiles from the expected cost. The presented approach considers, for the first time, solar uncertainty in UC/ED determination and enables efficient and accurate propagation of wind and solar uncertainty to estimate the statistics of the production cost. The effectiveness of the developed approach is demonstrated systematically on a stylized RTS-GMLC single-node system. The overall framework predicts the expected cost 62.5% more accurately than the existing state-of-the-art, on unforeseen days during the entire year, and yields, for the first time, the associated physically consistent UC and ED profiles. The solutions are also shown to be flexible in providing adequate daily reserves to address any statistical deviations from probabilistic power forecasts. The computational time associated with the presented method is only about 10 s compared to over 24 h needed for a conventional stochastic UC/ED determination under uncertainty on an Intel Core i9 processor with 32 GB of RAM.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

U.S. Building Stock Characterization Study: A National Typology for Decarbonizing U.S. Buildings

To support the U.S. Department of Energy’s (DOE) Advanced Building Construction (ABC) Collaborative, the National Renewable Energy Laboratory (NREL) has been tasked with characterizing the U.S. building stock and developing a national typology of buildings. The potential use cases of such a typology are flexible and evolving, but in this initial phase, the primary intention is to help identify technology requirements and engineering solutions for moving the U.S. building stock toward a zero-carbon future by midcentury. This study was developed by NREL, with input from the ABC Analysis Working Group, which is a subset of the ABC Collaborative led by the Rocky Mountain Institute (RMI).

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Pathways for Agricultural Decarbonization in the United States

In the United States, agricultural production is both a significant source of greenhouse gases (GHGs) (Environmental Protection Agency (EPA), 2022) and uniquely susceptible to climate change impacts (Vermeulen et al., 2012). Decarbonization solutions have been proposed for addressing agricultural GHGs; however, research has been limited in synthesizing qualitative and quantitative analysis of potential GHG mitigation solutions in the United States. In this report, we review U.S. agricultural GHG sources by activity and quantify potential mitigation solutions based on a comprehensive data and literature analysis. We also discuss agricultural carbon sequestration options to offset GHG emissions. In our analysis, we identified two significant and hard-to-abate GHG sources (N 2 O from soil management, and CH 4 from enteric fermentation from livestock) as well as high-impact GHG mitigation solutions (e.g. agroforestry, reforestation, and biochar application) and cross-cutting GHG mitigation solutions (renewable energy production, precision agriculture, no-till, integrated nutrient management, and biochar). This report is meant to provide initial analysis and establish a foundation for future agricultural decarbonization research - it is not an exhaustive analysis of all available studies. However, to our knowledge this report is the most comprehensive assessment of agricultural GHG emissions and associated mitigation opportunities in the United States to date. Future empirical research is recommended to close research gaps in different climates, soils, and agricultural systems. Meta-analyses for all mitigation solutions would increase confidence in the estimated GHG mitigation potentials. To conclude this report, we discuss short-term and long-term pathways for agricultural decarbonization in the United States, the importance of accounting for total GHG fluxes, potential co-benefits of agricultural decarbonization, analysis of study data confidence, and research gaps.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2024

Tierra del Fuego Case Study Capacity Expansion Analysis

This case study, developed by Net Zero World Initiative and the Government of Argentina, examines least-cost decarbonization pathways for Tierra del Fuego, Argentina, utilizing renewable energy, energy storage, hydrogen, and other decarbonization technologies. Being the second largest natural gas producing province in Argentina, Tierra del Fuego has historically relied on natural gas for their energy sector needs. As they look at possible decarbonization pathways, they face challenges due to extreme weather conditions, isolation from the mainland, and low population density. The study utilizes the Engage web application for capacity expansion modeling, addressing both business-as-usual (BAU) and accelerated decarbonization scenarios, with varying degrees of electrification and carbon emission constraints. Key findings reveal that an interconnection with the mainland, high contribution of wind energy development on Tierra del Fuego, energy storage, and hydrogen, coupled with energy-efficient electrification technologies (such as heat pumps and electric vehicles), emerge as the most cost-effective solutions to decarbonize, significantly reducing carbon emissions and total system energy costs. The study explores self-generation and interconnection alternatives, demonstrating the economic advantage of an interconnection of Tierra del Fuego with the mainland, as an alternative to 100% local generation. Sensitivity analyses on wind data sources and temporal resolutions, as well as projected natural gas prices, highlight the influence of external factors on the feasibility of decarbonization pathways. Challenges identified include the practicality of phasing out natural gas, economic uncertainty, cost implications of long-term storage technologies as wind energy increases, and geographical limitations for wind generation. The case study concludes that while substantial emissions reductions can be achieved by 2050, and be competitive with conventional pathways, achieving a full 100% decarbonization by 2050 would entail higher costs, particularly due to the significant reliance on storage solutions with higher contribution of wind energy. The analysis offers valuable insights for policymakers and stakeholders in Argentina's energy sector, emphasizing the importance of strategic planning, investment in renewable energy and storage technologies, and careful consideration of local conditions in the transition towards Net Zero targets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Virtual Power Plant Profiles and Inventory

Increased adoption of distributed energy resources (DERs), growing quantities of renewable energy on the grid, and load growth from buildings, industry, and data centers are driving the need for increased demand flexibility and solutions to reliably and cost-effectively balance electricity supply and demand. In order to deploy DERs on a similar scale as conventional supply-side resources, utilities and state decision-makers are exploring a range of programmatic approaches and market designs, including Virtual Power Plants (VPP). Based on interviews with more than twenty subject matter experts on VPPs, the Insights into Scaling Virtual Power Plants report and appendix outlines actions that utilities and regulators can take to expand VPPs, organized around successful VPP designs, deployment, and operation. The companion report, Virtual Power Plant Profiles and Inventory describes three conceptual profiles that can be used as a starting point to facilitate clear discussions among regulators, utilities, solution providers, and stakeholders about various VPP strategies. It also includes details on more than 790 demand response programs and net energy metering solar plus battery programs, and 180 VPP programs. The Inventory is provided below as a separate file.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Envisioning Tomorrow's Sustainable Mobility Systems

In the race to achieve efficient, accessible, affordable, and decarbonized transportation, which mobility solutions and strategies will get us to the finish line? Thought leaders from government, industry, and academia convened in mid-2023 at the National Renewable Energy Laboratory (NREL) to propose answers to this question. They worked to determine the research, development, and deployment challenges and opportunities that should be prioritized to create tomorrow's sustainable mobility systems. This fact sheet outlines cross-cutting themes and key findings from the workshop.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2025

Flexible and Effective Object Tiering for Heterogeneous Memory Systems

Computing platforms that package multiple types of memory, each with their own performance characteristics, are quickly becoming mainstream. To operate efficiently, heterogeneous memory architectures require new data management solutions that are able to match the needs of each application with an appropriate type of memory. As the primary generators of memory usage, applications create a great deal of information that can be useful for guiding memory management, but the community still lacks tools to collect, organize, and leverage this information effectively. To address this gap, this work introduces a novel software framework that collects and analyzes object-level information to guide memory tiering. The framework includes tools to monitor the capacity and usage of individual data objects, routines that aggregate and convert this information into tier recommendations for the host platform, and mechanisms to enforce these recommendations according to user-selected policies. Moreover, the developed tools and techniques are fully automatic, work on standard Linux systems, and do not require modification or recompilation of existing software. Using this framework, this study evaluates and compares the impact of a variety of design choices for memory tiering, including different policies for prioritizing objects for the fast memory tier as well as the frequency and timing of migration events. In conclusion, the results, collected on a modern Intel platform with conventional DDR4 SDRAM as well as Intel Optane NVRAM, show that guiding data tiering with object-level information can enable significant performance and efficiency benefits compared with standard hardware- and software-directed data-tiering strategies for a diverse set of memory-intensive workloads.

97 MATHEMATICS AND COMPUTING↗