SEARCH · Search NASA

Results for “resource estimates”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 397 records · Page 22

All sources NASA NTRS DOE OSTI

DOE OSTI2023

Hydropower Energy Storage Capacity (HESC) Dataset

The Hydropower Energy Storage Capacity (HESC) Dataset catalogs characteristics that are relevant to evaluating reservoir storage and estimates of energy storage capacity based on varying levels of detail. Hydropower dams and reservoirs were included based on information from the National Inventory of Dams (NID; USACE, 2021) and Global Reservoir and Dam (GRanD v1.3) and Existing Hydropower Assets datasets. These data provide a foundation for understanding available resources at existing hydropower facilities and their potential to provide storage of energy and more flexible generation. Estimates of energy storage capacity include: • Level 1 – nominal energy storage capacity based on maximum storage capacities and hydraulic head • Level 2 – nominal energy storage capacity based on historical models or observations of reservoir volume and hydraulic head. These estimates are provided based on capacity from the entire historical period as well as monthly values. • Level 3 – modeled energy generation based on volume-elevation relationships, historical storage, observed/modeled inflows, and hydraulic capacity of turbines and calculated both as overall and on a monthly basis. • Level 4 – modeled energy generation incorporating information from Level 3 and operational constraints. For facilities where installed capacity is known, there are also estimates for discharge duration (the length of time when a facility could provide generation at a given capacity).

13 HYDRO ENERGY↗

DOE OSTI2024

Impact of Geothermal District Heating System on Flexibility of Microgrid in Tuttle, Oklahoma: Preprint

Flexibility is the capability of the power grid to maintain a balance between electricity generation and variable demand. This study presents preliminary results evaluating the impact of geothermal district heating systems on the flexibility of a conceptual microgrid in Tuttle, Oklahoma. Heating demand profiles were modeled using EnergyPlus for the district that includes two schools and 250 single-family houses. Then, geothermal energy production was modeled using GEOPHIRES to estimate how much heating demand in the district can be supplied by five different geothermal system scenarios. The results indicated that geothermal energy production varied depending on the resource temperature at different depths, system configurations, and flow rates. For the grid flexibility analysis, electricity consumptions in the five geothermal systems were estimated for pump operations to circulate water from the wells to radiators, while electricity consumption by air-source heat pump in the base case was estimated to supply the same heating load. Electricity consumption in the geothermal systems was significantly lower than those in base cases. The electricity saved by the geothermal system was then incorporated into the microgrid electrical load profiles where variable renewable electricity generation is significantly high. The results visually showed that geothermal district heating system can improve grid flexibility as a baseload during the winter season. The results also highlighted potential opportunities to save energy costs that will be further analyzed in future study.

Cambium↗

DOE OSTI2025

Impact of Geothermal District Heating System on Flexibility of Microgrid in Tuttle, Oklahoma

Flexibility is the capability of the power grid to maintain a balance between electricity generation and variable demand. This study presents preliminary results evaluating the impact of geothermal district heating systems on the flexibility of microgrid in Tuttle, Oklahoma. Heating demand profiles were modeled using EnergyPlus for the district that includes two schools and 250 single-family houses. Then, geothermal energy production was modeled using GEOPHIRES to estimate how much heating demand in the district can be supplied by five different geothermal system scenarios. The results indicated that geothermal energy production varied depending on the resource temperature at different depths, system configurations, and flow rates. For the grid flexibility analysis, electricity consumptions in the five geothermal systems were estimated for pump operations to circulate water from the wells to radiators, while electricity consumption by air-source heat pump in the base case was estimated to supply the same heating load. Electricity consumption in the geothermal systems was significantly lower than those in base cases. The electricity saved by the geothermal system was then incorporated into the microgrid electrical load profiles where variable renewable electricity generation is significantly high. The results visually showed that geothermal district heating system can improve grid flexibility as a baseload during the winter season. The results also highlighted potential opportunities to save energy costs that will be further analyzed in future study.

Cambium↗

DOE OSTI2022

Deployment of Energy Efficiency and Clean Energy on Indians Lands – A Community Solar Project

The Eastern Band of Cherokee Indians (EBCI or Tribe) is a federally recognized Indian Tribe located on ancestral homelands in western North Carolina. The Tribe is comprised of just over 16,000 enrolled members, with an estimated 8,000 – 10,000 residing on tribal lands. The Qualla Boundary is comprised of over 56,000 acres of contiguous trust land adjacent to the Great Smoky Mountain National Park. The EBCI also possess an assortment of scattered parcels of varying sizes across western North Carolina, some in trust status and others in deeded or fee simple. This project was implemented on a trust parcel in Cherokee County, NC. The Tribe was awarded the maximum amount of $\$ $1,000,000 for the installation of a 705.6 kilowatt (kW) solar PV array to supplement the power consumed and reduce annual utility costs at the Harrah’s Cherokee Valley River (HCVR) casino and hotel in Murphy, NC. The casino is a tribal entity of the Tribe. The total cost of the project was $\$ $2.364 million. The system was officially commissioned on April 12, 2019. For the purpose of calculating the amount of power produced and reduction in utility costs, the time frame assessed is May 2019 through April 2020. All power generated was consumed onsite.Based on the first full year of data, the project achieved the estimated 8.3% reduction in utility costs. A total of six casino and tribal staff were trained and received a North American Board of Certified Energy Practitioners (NABCEP) certification, giving our staff the resources and skills to manage and operate the solar PV array. Based on the Tribal match of $\$ $1,377,797 and estimated net annual benefit of $89,000, the estimated return on investment (ROI) is 15.48 years.

14 SOLAR ENERGY↗

DOE OSTI2023

A Two-Step Time-Series Data Clustering Method for Building-Level Load Profile

Residential and commercial buildings have huge potential to contribute value to improve grid resilience by participating grid services. To reveal the significant value, it is critical to estimate the grid service capability from these buildings. Unlike the large-scale distributed energy resources such as wind and solar farms, those buildings need to participate grid services in aggregation, not by individual. Therefore, it is important to appropriately group buildings for aggregation. The load profiles in the same group will have similar characteristics at the same time step, so grid operators can send the grid service signal to the customer group with a higher chance to respond at that time step. In this paper, we develop a load profile clustering method to classify the building-level load profiles for grid service capability estimation. In our two-step clustering approach, we first calculate the total load consumption for each building, clustering the load profiles based on energy consumption level. Then, we further cluster the load profiles in each energy cluster based on the load shape. The parameter selection for each clustering step is discussed. The proposed method is applied on actual building-level load profiles, and the results have proved the effectiveness of this method.

advanced metering infrastructure (AMI)↗

DOE OSTI2024

Commercialization of Distribution System Load Modeling Tool for Improved DER Interconnection Studies

14 SOLAR ENERGY↗

DOE OSTI2023

A Two-Step Time-Series Data Clustering Method for Building-Level Load Profile

AMI↗

DOE OSTI2024

Potential Availability of Alternative Fuel to Supply Maritime Activities in Pacific Northwest Ports

The international shipping sector represented 3% of global greenhouse gas emissions in 2023 (Office of Energy Efficiency & Renewable Energy 2024). International shipping has been classified as a difficult-to-decarbonize industry (IRENA 2024). In an effort to drive decarbonization, the U.S. Department of Energy has partnered with Mission Innovation to co-lead the Zero-Emission Shipping Mission, which launched in 2021(Office of Energy Efficiency & Renewable Energy 2021). In addition, the U.S. Department of State partnered with Norway to launch the Green Shipping Challenge in 2022 (Office of the Spokesperson 2022b). As part of the ZESM and Green Shipping Challenge, the United States is collaborating with the Republic of Korea (ROK) to develop a green shipping corridor (U.S. Mission Korea 2023). The United States and ROK have conducted a pre-feasibility study as the first step in developing a green shipping corridor between the countries. The ports included in the study are Seattle, Tacoma, and Everette in the U.S. Pacific Northwest (PNW) and Busan, Ulsan, and Masan in ROK. The National Renewable Energy Laboratory's role in the study was to analyze the availability and technical potential of alternative marine fuels in proximity to U.S. PNW ports. The findings show most of the existing alternative fuel capacity within the region is from renewable diesel, biodiesel, and sustainable aviation fuel facilities. The largest growth in fuel capacity in the region by 2030 is projected to be in renewable diesel and hydrogen. The overall technical readiness of non-drop-in alternative fuel production and conversion technologies is more developed than alternative-fueled ships and associated fueling infrastructure. However, much of the fuel capacity in the region is comprised of drop-in fuels, making it technically possible to use existing infrastructure for transporting and bunkering to the existing fleet. Data to inform regional alternative fuel quantity estimations were collected from an extensive review of databases, reports, announcements, and other publicly available resources. A maturity index and sector competition factor were applied to announced fuel projects to determine the quantity of alternative fuel available to the marine sector in the region by 2030. Demand data were collected from fuel bunkering logs covering the PNW seaports (State of Washington 2021). Both supply and demand data were converted to very-low sulfur fuel oil gallon equivalents (VLSFO-GE) for better comparison. Qualitative data were gathered through interviews with stakeholders, project developers, and industry experts. Total alternative fuel capacity available to the marine sector in the region is estimated to be 824 million VLSFO-GE per year by 2030. This is sufficient to cover the requirements of a green shipping corridor between the United States and ROK. The findings from this report are being used to inform detailed feasibility studies for several U.S. PNW -ROK green shipping corridors. Updates from the U.S. PNW - ROK feasibility studies will continue to be published on Mission Innovation's green corridor tracking website (Zero Emission Shipping Mission, n.d.). In addition, this report has helped to inform further work on shipping decarbonization in the U.S. PNW, including the Pacific Northwest to Alaska Green Corridor focused on cruise vessels.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

FASTSim™ (Future Automotive Systems Technology Simulator) [SWR-20-101 and SWR-12-07]

The Future Automotive Systems Technology Simulator (FASTSim™) provides a simple way to compare powertrains and estimate the impact of technology improvements on light-, medium-, and heavy-duty vehicle efficiency, performance, cost, and battery life. This extremely fast simulation tool features a streamlined user interface and can rapidly perform a variety of tasks using basic computing resources: • less than 0.1 second to simulate second-by-second standard duty cycles • less than 10 seconds to estimate vehicle efficiency, fuel economy, acceleration, battery life, and cost • less than 5 minutes to perform powertrain comparisons of efficiency and cost. FASTSim models a variety of vehicle powertrains and fuel converter types: • Conventional vehicles - spark ignition, Atkinson, diesel, and hybrid diesel • Electric-drive vehicles - hybrid, plug-in hybrid, and all-electric • Hydrogen fuel cell vehicles. The default model includes a variety of vehicles and duty cycles and an option for adding additional vehicles and custom cycles: • Packaged with more than 20 vehicles • User interface enables addition of more vehicles • Includes standard U.S. drive cycles as well as European and Japanese cycles. FASTSim is available for download in Microsoft Excel and Python formats here: https://www.nrel.gov/transportation/fastsim.html

Baker, Chad↗

DOE OSTI2021

Defender Policy Evaluation and Resource Allocation against MITRE ATT&CK Data and Evaluations

Protecting against multi-step attacks of uncertain duration and timing forces defenders into an indefinite, always ongoing, resource-intensive response. To effectively allocate resources, a defender must be able to analyze multi-step attacks under assumption of constantly allocating resources against an uncertain stream of potentially undetected attacks. To achieve this goal, we present a novel methodology that applies a game-theoretic approach to the attack, attacker, and defender data derived from MITRE´s ATT&CK ® Framework. Time to complete attack steps is drawn from a probability distribution determined by attacker and defender strategies and capabilities. This constraints attack success parameters and enables comparing different defender resource allocation strategies. By approximating attacker-defender games as Markov processes, we represent the attacker-defender interaction, estimate the attack success parameters, determine the effects of attacker and defender strategies, and maximize opportunities for defender strategy improvements against an uncertain stream of attacks. This novel representation and analysis of multi-step attacks enables defender policy optimization and resource allocation, which we illustrate using the data from MITRE´ s APT3 ATT&CK ® Framework.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Quantum Computing for Neutrino-Nucleus Scattering

Neutrino-nucleus cross section uncertainties are expected to be a dominant systematic in future accelerator neutrino experiments. The cross sections are determined by the linear response of the nucleus to the weak interactions of the neutrino, and are dominated by energy and distance scales of the order of the separation between nucleons in the nucleus. These response functions are potentially an important early physics application of quantum computers. Here we present an analysis of the resources required and their expected scaling for scattering cross section calculations. The current estimates of Trotter steps needed to achieve an energy resolution of 10 MeV and the number of CNOT gates for analyzing Ar40 highlights the need for significant improvements in algorithms. We also examine simple small-scale neutrino-nucleus models on modern quantum hardware. In this paper, we use variational methods to obtain the ground state of a three nucleon system (the triton) and then implement the relevant time evolution. To tame the errors in present-day NISQ devices, we explore the use of different error-mitigation techniques to increase the fidelity of the calculations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Production of Uranium from Seawater Using a Novel Polymer Adsorbent – Process Development and Cost Analysis (Final Scientific/Technical Report SBIR Phase II)

Research in developing techniques for extracting uranium from seawater is of considerable current interest. One reason which drives scientists to develop techniques of sequestering uranium from ocean is the prediction that the land-based uranium reserves would be depleted by the end of this century based on the current production rate. Uranium exists in seawater at a very low concentration (about 3 ppb) and as highly stable uranyl tris-carbonato complexes, primarily in the form Ca 2 [UO 2 (CO 3 ) 3 ]. Because of the enormous volume of seawater, the total amount of uranium in ocean is estimated to be a thousand times greater than the land-based uranium resources. As early as 1964, the idea of extracting uranium from seawater was discussed by Davies et al. in a Nature paper. In the past decades, many different materials were tested to evaluate their ability for sequestering uranium from seawater. Among them, amidoxime and carboxylate containing polymer fiber adsorbents appear most promising because of their high uranium adsorption capacity and stability in seawater. The carboxylate groups are necessary to make the polymer adsorbent hydrophilic whereas the amidoxime groups provide strong coordination sites for uranyl ions. Moreover, according to theoretical analysis, the adsorbability of uranium may involve synergistic effects of both amidoxime and carboxyl groups in the fiber adsorbent.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Advances in Energy Hybridization for Resilient Supply: A Sustainable Approach to the Growing World Demand

Energy poverty, defined as a lack of access to reliable electricity and reliance on traditional biomass resources for cooking, affects over a billion people daily. The World Health Organization estimates that household air pollution from inefficient stoves causes more premature deaths than malaria, tuberculosis, and HIV/AIDS. Increasing demand for energy has led to dramatic increases in emissions. The need for reliable electricity and limiting emissions drives research on Resilient Hybrid Energy Systems (RHESs), which provide cleaner energy through combining wind, solar, and biomass energy with traditional fossil energy, increasing production efficiency and reliability and reducing generating costs and emissions. Microgrids have been shown as an efficient means of implementing RHESs, with some focused mainly on reducing the environmental impact of electric power generation. The technical challenges of designing, implementing, and applying microgrids involve conducting a cradle-to-grave Life Cycle Analysis (LCA) to evaluate these systems’ environmental and economic performance under diverse operating conditions to evaluate resiliency. A sample RHES was developed and used to demonstrate the implementation in rural applications, where the system can provide reliable electricity for heating, cooling, lighting, and pumping clean water. The model and findings can be utilized by other regions around the globe facing similar challenges.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2021

Hydropower Energy Storage Capacity Dataset

The Hydropower Energy Storage Capacity (HESC) Dataset catalogues estimates of nominal energy storage capacity based on varying levels of detail. Dams and reservoirs selected were selected based on those reported in the National Inventory of Dams (NID 2019) and/or the Global Reservoir and Dam (GRanD v1.3) datasets. These data provide a foundation for understanding available resources at existing hydropower facilities and their potential to provide storage of energy and more flexible generation. Current estimates include Level 1 (based on maximum storage capacities and hydraulic head) and Level 2 (based on historical models or observations of reservoir volume and hydraulic head). For facilities where installed capacity is known, there are also estimates for discharge duration or the length of time when a facility could provide generation at a given capacity. Essential information used to calculate the energy storage capacity and discharge duration (volume, hydraulic head, and details about the sources or records used to obtain those parameters) and summaries of historical generation (for context) are also included.

13 HYDRO ENERGY↗

DOE OSTI2023

Robust Real-Time Modeling of Distribution Systems with Data-Driven Grid-Wise Observability (Final Technical Report)

The overall objective of this project is to leverage existing and emerging sensor measurements to develop data-driven observability enhancement algorithms as well as robust state estimation and parameter identification techniques to enable real-time grid-wise monitoring and modeling of loads and distributed energy resources (DERs). The project resulted in a holistic framework with the following key components: 1) data-driven and machine learning-based grid-edge visibility enhancement, 2) robust branch-current-based state estimation (BCSE), and 3) robust real-time steady-state and dynamic-state modeling of loads and DERs. The research outcomes have provided utility companies better network visibility, higher-fidelity load/DER models, and more accurate assessment of DERs’ impacts, thus, facilitating the integration of renewable energy sources. The synergistic collaborative project among Iowa State University (ISU), Argonne National Laboratory (ANL), Electric Power Research Center (EPRC), SIEMENS Industry, Alliant Energy, Cedar Falls Utilities (CFU), and Maquoketa Valley Electric Cooperative (MVEC) to leverage the team’s extensive expertise and experience in power distribution systems, state estimation, online modeling and identification, and DER integrations. The proposed frameworks have been verified with industry adopted software and attempted integrated with existing tool wherever possible

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Nanosecond machine learning regression with deep boosted decision trees in FPGA for high energy physics

We present a novel application of the machine learning / artificial intelligence method called boosted decision trees to estimate physical quantities on field programmable gate arrays (FPGA). The software package fwXmachina features a new architecture called parallel decision paths that allows for deep decision trees with arbitrary number of input variables. It also features a new optimization scheme to use different numbers of bits for each input variable, which produces optimal physics results and ultraefficient FPGA resource utilization. Problems in high energy physics of proton collisions at the Large Hadron Collider (LHC) are considered. Estimation of missing transverse momentum (E T miss ) at the first level trigger system at the High Luminosity LHC (HL-LHC) experiments, with a simplified detector modeled by Delphes, is used to benchmark and characterize the firmware performance. The firmware implementation with a maximum depth of up to 10 using eight input variables of 16-bit precision gives a latency value of $\mathcal{O}$(10) ns, independent of the clock speed, and $\mathcal{O}$(0.1)% of the available FPGA resources without using digital signal processors.

Instruments & Instrumentation↗

DOE OSTI2024

When energy doesn’t add up: use of an energyshed framework in assessing progress towards renewable energy transitions

Global progress in energy transitions to support climate mitigation goals has been slower than anticipated; this has prompted shifts away from traditional paradigms of regulated energy ownership towards a model of energy democratization by local communities and individuals. For example, in the United States, local communities in over 250 cities, counties, and states have made pledges to reach 100% renewable electrification by target dates ranging from 2020 to 2050. However, the availability of infrastructure and the competition for renewable energy resources, as well as lack of awareness of these limitations, present significant barriers to overcome. In this study, we explored a subset of 31 of these cities to assess their current electricity generation and how much further they have to go to meet their goals. Through an energyshed framework, we estimated powerplant electricity allocation to each city assuming competition for power from various renewable and non-renewable resource types, as well as look at the ‘best case scenario’ assuming 100% allocation of renewable-sourced electricity for a handful of cities in order to understand the existing and planned energy mixes for 2021 and the following 20 years. It is likely most cities will meet 10% of their energy demand with renewable energy, with best cases scenarios reaching between 35% and 65% renewable penetration, within the next 20–30 years. This highlights the need for infrastructural development in the energy sector, as well as intentional planning efforts in order to make these energy goals a reality.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Reliability-informed end-of-use decision making for product sustainability using two-stage stochastic optimization

The concept of circular economy has been diffused in recent decades to promote economic growth that does not add to the burden on natural resource extraction. Re-X options (e.g., reuse, repair, refurbish, remanufacture, recycle) have been gradually adopted in the product development process and optimized to reduce or eliminate waste and pollution. Although manufacturing incorporating Re-X options can be more environmentally friendly, it involves more sources of uncertainty than traditional manufacturing since the end-of-use products can be collected from multiple origins with various quantities and qualities, and the market demand for both new and remanufactured products cannot be forecasted perfectly. Thus, there is a need to optimize the Re-X policy to alleviate the negative impacts of the higher uncertainty. One option is using the reliability information of new products to estimate the end-of-use conditions and applying multi-stage stochastic optimization to capture multiple demand scenarios. This paper develops a two-stage stochastic optimization model to optimize the quality thresholds for reuse, recycling, and remanufacturing options. Our objective is to minimize the total cost, energy consumption, and environmental impact of producing and providing warranty service for a product family. The model employs reliability information of product components to estimate the warranty service cost and the end-of-use conditions of the returned resources. A case study on a general product family is implemented to illustrate the efficacy of the optimization model. Finally, results show that the two-stage optimization can achieve cost and environmental impact reduction for a hybrid manufacturing and remanufacturing process.

97 MATHEMATICS AND COMPUTING↗