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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 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Distributed Energy Resource Cybersecurity Framework and Cyber Range Integration

Distributed energy resource (DER) systems feature complex, data-driven communications networks that require careful system coordination and constant vigilance to ensure that grid assets are secure. Because DERs are an important component of the decarbonization strategy, agencies need to secure energy data that could implicate issues of national security if compromised. To help federal energy managers assess, monitor, and manage cybersecurity while achieving decarbonization, the National Renewable Energy Laboratory's (NREL's) Distributed Energy Resource Cybersecurity Framework (DER-CF) offers a comprehensive, web-based assessment tool focusing on cyber governance or policies, technical management, and physical security. The DER-CF currently presents users with a series of pertinent cybersecurity questions that are used to generate a site-specific report and recommendations. This paper outlines a plan to integrate the DER-CF with another key asset-NREL's cyber range-to visualize cybersecurity resilience and compliance and to enhance the usability and accessibility of the DER-CF for federal facility energy managers and planners. This integration will result in a visualization environment to interpret and interact with compliance data. Its development will include regular conversations with stakeholders to assess the effectiveness of these efforts, refine the visualization capability, and ensure its value to our partners.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Development of A High-Resolution Dataset for Solar Resource Adequacy Studies

High-resolution, long-term solar dataset is essential for characterizing the variability of solar energy resources and for informing strategies that ensure grid reliability and resilience in grid systems with high levels of solar energy integration. We present the development of a new 4-km, hourly Earth system dataset for the contiguous United States (CONUS), using a statistical downscaling approach that integrates the National Solar Radiation Database (NSRDB) with regional Earth system model projections. The new high-resolution Earth system dataset includes key variables - GHI, DNI, DHI, surface air temperature, and wind speed - under two future scenarios. Preliminary results show a reasonable agreement with NSRDB observations, with nBias less than 1% for GHI across CONUS. The dataset is expected to support in-depth analyses of extreme weather impacts and provide input to resource adequacy for future energy systems with diverse generation sources.

14 SOLAR ENERGY↗
DOE OSTI2014

North and South Dakota High Resolution 50m Wind Resource

Annual average wind resource potential for North and South Dakota at a 50 meter height in a GIS shapefile and links to US national wind resource information tools. This data set was produced and validated by NREL using their WRAM model.

50m↗
NASA NTRSDate not supplied

NASA Envisioned Future Priorities for In Situ Resource Utilization

A major objective of the United States National Aeronautics and Space Administration’s Artemis program is to create a sustainable human lunar exploration program through the establishment of lunar infrastructure and commercial space operations. A key aspect in achieving this objective is characterizing the resources that exist on the Moon and Mars, and learning how to utilize them to create products for crew, power, transportation, and infrastructure growth. Commonly known as In Situ Resource Utilization (ISRU), the ability to make products from local materials instead of bringing everything from Earth has the potential to significantly reduce mission costs, mass, risks, and dependency on Earth. To achieve this vision, NASA’s Space Technology Mission Directorate (STMD) established a strategic framework, called the Strategic Technology Architecture Roundtable (STAR) process, to coordinate development of critical capabilities around four major Thrusts (Go, Land, Live, and Explore). To guide and drive the development of critical mission capabilities, the STAR process involves establishing a ‘grand vision’ known as an Envisioned Future for each of these capabilities. For ISRU, the Envisioned Future is “Scalable ISRU production/utilization capabilities including sustainable commodities on the lunar and Mars Surface”. This paper will discuss the STAR process, and the strategic plan and near-term priorities for achieving the ISRU Envisioned Future.

In Situ Resources Utilization↗
DOE OSTI2016

Distributed Wind Resource Assessment Overview

Wind resource characterization and assessment was identified through a 2014 DOE Request for Information as one of the top four Distributed Wind Portfolio R&D focus areas. This presentation provides an overview of NREL's distributed wind resource assessment project work: the background and motivations for the work; an assessment of the current state of the industry; and challenges, barriers, and high-payoff opportunities.

17 WIND ENERGY↗
DOE OSTI2017

Effects of spatially distributed sectoral water management on the redistribution of water resources in an integrated water model

Realistic representations of sectoral water withdrawals and consumptive demands and their allocation to surface and groundwater sources are important for improving modeling of the integrated water cycle. To inform future model development, in this work we enhance the representation of water management in a regional Earth system (ES) model with a spatially distributed allocation of sectoral water demands simulated by a regional integrated assessment (IA) model to surface and groundwater systems. The integrated modeling framework (IA-ES) is evaluated by analyzing the simulated regulated flow and sectoral supply deficit in major hydrologic regions of the conterminous U.S, which differ from ES studies looking at water storage variations. Decreases in historical supply deficit are used as metrics to evaluate IA-ES model improvement in representating the complex sectoral human activities for assessing future adaptation and mitigation strategies. We also assess the spatial changes in both regulated flow and unmet demands, for irrigation and nonirrigation sectors, resulting from the individual and combined additions of groundwater and return flow modules. Results show that groundwater use has a pronounced regional and sectoral effect by reducing water supply deficit. The effects of sectoral return flow exhibit a clear east-west contrast in the hydrologic patterns, so the return flow component combined with the IA sectoral demands is a major driver for spatial redistribution of water resources and water deficits in the US. Our analysis highlights the need for spatially distributed sectoral representation of water management to capture the regional differences in interbasin redistribution of water resources and deficits.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Laser machined plastic laminates. Towards portable diagnostic devices for use in low resource environments

Despite significant progress in development of bioanalytical devices cost, complexity, access to reagents and lack of infrastructure have prevented use of these technologies in resource-limited regions. To provide a sustainable tool in the global effort to combat infectious diseases the diagnostic device must be low cost, simple to operate and read, robust, and have sensitivity and specificity comparable to laboratory analysis. Thus, in this mini-review we describe recent work using laser machined plastic laminates to produce diagnostic devices that are capable of a wide variety of bioanalytical measurements and show great promise towards future use in low-resource environments.

47 OTHER INSTRUMENTATION↗
DOE OSTI2014

Modeling of thermal storage systems in MILP distributed energy resource models

Thermal energy storage (TES) and distributed generation technologies, such as combined heat and power (CHP) or photovoltaics (PV), can be used to reduce energy costs and decrease CO 2 emissions from buildings by shifting energy consumption to times with less emissions and/or lower energy prices. To determine the feasibility of investing in TES in combination with other distributed energy resources (DER), mixed integer linear programming (MILP) can be used. Such a MILP model is the well-established Distributed Energy Resources Customer Adoption Model (DER-CAM); however, it currently uses only a simplified TES model to guarantee linearity and short run-times. Loss calculations are based only on the energy contained in the storage. This paper presents a new DER-CAM TES model that allows improved tracking of losses based on ambient and storage temperatures, and compares results with the previous version. A multi-layer TES model is introduced that retains linearity and avoids creating an endogenous optimization problem. The improved model increases the accuracy of the estimated storage losses and enables use of heat pumps for low temperature storage charging. Ultimately,results indicate that the previous model overestimates the attractiveness of TES investments for cases without possibility to invest in heat pumps and underestimates it for some locations when heat pumps are allowed. Despite a variation in optimal technology selection between the two models, the objective function value stays quite stable, illustrating the complexity of optimal DER sizing problems in buildings and microgrids.

25 ENERGY STORAGE↗
DOE OSTI2021

Controlling distributed energy resources via deep reinforcement learning for load flexibility and energy efficiency

Behind-the-meter distributed energy resources (DERs), including building solar photovoltaic (PV) technology and electric battery storage, are increasingly being considered as solutions to support carbon reduction goals and increase grid reliability and resiliency. However, dynamic control of these resources in concert with traditional building loads, to effect efficiency and demand flexibility, is not yet commonplace in commercial control products. Traditional rule-based control algorithms do not offer integrated closed-loop control to optimize across systems, and most often, PV and battery systems are operated for energy arbitrage and demand charge management, and not for the provision of grid services. More advanced control approaches, such as MPC control have not been widely adopted in industry because they require significant expertise to develop and deploy. Recent advances in deep reinforcement learning (DRL) offer a promising option to optimize the operation of DER systems and building loads with reduced setup effort. However, there are limited studies that evaluate the efficacy of these methods to control multiple building subsystems simultaneously. Additionally, most of the research has been conducted in simulated environments as opposed to real buildings. This paper proposes a DRL approach that uses a deep deterministic policy gradient algorithm for integrated control of HVAC and electric battery storage systems in the presence of on-site PV generation. The DRL algorithm, trained on synthetic data, was deployed in a physical test building and evaluated against a baseline that uses the current best-in-class rule-based control strategies. Performance in delivering energy efficiency, load shift, and load shed was tested using price-based signals. The results showed that the DRL-based controller can produce cost savings of up to 39.6% as compared to the baseline controller, while maintaining similar thermal comfort in the building. The project team has also integrated the simulation components developed during this work as an OpenAIGym environment and made it publicly available so that prospective DRL researchers can leverage this environment to evaluate alternate DRL algorithms.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Can Wholesale Electricity Markets Achieve Resource Adequacy and High Clean Energy Generation Targets in the Presence of Self-Interested Actors?

Wholesale electricity markets are intended to incentivize system generation investments and operations outcomes that meet evolving system needs. In this work, we evaluate the effectiveness of wholesale market structures, rules and policies in achieving system resource adequacy (RA) and clean energy targets in the presence of self-interested generation investors using the Electricity Markets and Investment Suite Agent-based Simulation (EMIS-AS) model. Results highlight that both capacity markets and operating reserve demand curves (ORDCs) can help achieve a reliable system but with different RA compliance timelines and distribution of generation technologies. Structures with capacity markets tend to favor more capital-intensive peaking technologies while reducing wind and solar build-outs due to suppressed energy and clean energy market prices, particularly in the absence of strong clean energy targets. Conversely, ORDCs improve the commitment of available generation units, but this comes at the expense of higher system costs and renewable generation curtailment. We also find that well-calibrated static capacity demand curves can yield similar reliability and total cost compared to capacity market demand curves informed dynamically by resource adequacy while also yielding stable annual capacity prices. Different approaches to formulating ORDC curves can also yield key trade-offs, namely that a more efficient treatment of storage chronology results in lower ORDC curves and prices, yielding less investment and cost but at the expense of reliability. Finally, the effectiveness of wholesale electricity markets in practically achieving very high clean energy generation targets highly depends on the cost-competitiveness of clean energy technologies that can support critical balancing needs across multiple timescales.

capacity expansion↗
DOE OSTI2017

Identification of blind geothermal resources in Surprise Valley, CA, using publicly available groundwater well water quality data

Geothermal resource exploration is generally limited to areas with surface expressions of thermal activity (fumaroles and hot springs), or relies on expensive geophysical exploration techniques. The hidden subsurface distribution of geothermal fluids has been identified using a free and publicly available water quality dataset from agricultural and domestic water wells in Surprise Valley, northeastern California. Thermally evolved waters in Surprise Valley have element ratios that vary in response to Ca carbonate and Mg silicate mineral precipitation, and have elevated total dissolved solids (TDS). The arid climate in Surprise Valley leads to surface water evaporation in a closed basin, producing high TDS Na-Cl-CO 3 -SO 4 brines in three ephemeral alkali lakes and in shallow groundwater under elevated soil CO 2 conditions. Evaporated fluids in Surprise Valley follow a chemical divide that leads to Ca carbonate and Mg silicate mineral precipitation. Plots of dissolved element ratios can be used to distinguish groundwater affected by evaporation from water affected by thermal water-rock interaction, however it is challenging to select components for plotting that best illustrate different fluid evolution mechanisms. Here, we use a principal component analysis of centered log-ratio transformed data, coupled with geochemical models of fluid evaporation and thermal mixing pathways, to identify components to plot that distinguish between groundwater samples influenced by evaporation from those influenced by thermal processes. We find that groundwater samples with a thermal signature come from wells that define a coherent, linear geographical distribution that closely matches the location of known and inferred faults. Finally, modification of the general approach employed here provides promise for identifying blind geothermal resources in other locations, by applying low-cost geochemical modeling and statistical techniques to areas where large groundwater quality geochemical datasets are available.

15 GEOTHERMAL ENERGY↗
DOE OSTI2014

The updated billion-ton resource assessment

This paper summarizes the results of an update to a resource assessment, published in 2005, commonly referred to as the billion-ton study (BTS). The updated results are consistent with the 2005 BTS in terms of overall magnitude. However, in looking at the major categories of feedstocks the forest residue biomass potential was determined to be less owing to tighter restrictions on forest residue supply including restrictions due to limited projected increase in traditional harvest for pulpwood and sawlogs. The crop residue potential was also determined to be less because of the consideration of soil carbon and not allowing residue removal from conventionally tilled corn acres. The energy crop potential was estimated to be much greater largely because of land availability and modeling of competition among various competing uses of the land. Generally, the scenario assumptions in the updated assessment are much more plausible to show a billion-ton resource, which would be sufficient to displace 30% or more of the country s present petroleum consumption.

09 BIOMASS FUELS↗
DOE OSTI2022

The locational value of distributed energy resources: A parcel-level evaluation of solar and wind potential in New York state

We report distributed energy resources (DERs) are poised to play a significant role in evolving power systems because of their flexibility to be sited in areas of high value to the grid. Traditional DER compensation frameworks, specifically net energy metering (NEM), inadequately communicate differences in the locational and temporal value of DER generation to the grid. As a transition from NEM, New York State's (NYS's) Value of Distributed Energy Resources (VDER) framework provides a methodology for calculating different value components that DERs offer the grid. To study the impacts of VDER frameworks on DER deployment, we developed a model to assess the value of distributed solar and wind systems configured as either a behind-the-meter system or a front-of-the-meter system for each parcel of land in NYS. Using parcel-level granularity, we can closely evaluate DER locational value and siting availability, particularly in urban and suburban settings. Our analysis finds while most DER generators would be modestly compensated for deferred transmission and distribution infrastructure upgrades (~0.01 $\$$/kWh for solar PV), a subset of projects receive significant value from this component (0.035 to 0.089 $\$$/kWh for top 5% of parcels for solar PV). Finally, our analysis finds VDER provides less overall compensation than NEM to the average DER generator, however, it increases access to compensation for front-of-the-meter DERs - a large and emerging market.

14 SOLAR ENERGY↗
DOE OSTI2016

U.S. DOE NETL methodology for estimating the prospective CO 2 storage resource of shales at the national and regional scale

While the majority of shale formations will serve as reservoir seals for stored anthropogenic carbon dioxide (CO2), hydrocarbon-bearing shale formations may be potential geologic sinks after depletion through primary production. Here in this paper we present the United States-Department of Energy-National Energy Technology Laboratory (US-DOE-NETL) methodology for screening-level assessment of prospective CO 2 storage resources in shale using a volumetric equation. Volumetric resource estimates are produced from the bulk volume, porosity, and sorptivity of the shale and storage efficiency factors based on formation-scale properties and petrophysical limitations on fluid transport. Prospective shale formations require: (1) prior hydrocarbon production using horizontal drilling and stimulation via staged, high-volume hydraulic fracturing, (2) depths sufficient to maintain CO 2 in a supercritical state, generally >800 m, and (3) an overlying seal. The US-DOE-NETL methodology accounts for storage of CO 2 in shale as a free fluid phase within fractures and matrix pores and as an sorbed phase on organic matter and clays. Uncertainties include but are not limited to poorly-constrained geologic variability in formation thickness, porosity, existing fluid content, organic richness, and mineralogy. Knowledge of how these parameters may be linked to depositional environments, facies, and diagenetic history of the shale will improve the understanding of pore-to-reservoir scale behavior, and provide improved estimates of prospective CO 2 storage.

25 ENERGY STORAGE↗
DOE OSTI2022

Forecasting distributed energy resources adoption for power systems

Failing to incorporate accurate distributed energy resource penetration forecasts into long-term resource and transmission planning can lead to cost inefficiencies at best and system failures at worst. We have developed an open-source tool that employs an advanced Bass specification to calibrate and forecast technology adoption. The advanced specification includes geographic clustering, exogenously estimated market size, and dynamic time steps. Training on historical adoption of rooftop photovoltaics at the U.S. county-level and using detailed techno-economic estimates, our model achieves a two-year average mean-absolute-percentage-error of 19% in predicting system counts at the county-level, weighted by population. Model error was negatively correlated with market maturity - the error was 12% for counties in states with at least 28 W-per-capita of installed capacity. The advanced specification significantly reduces unweighted forecasting percent error compared to a conventional Bass specification: from 196% to 25% for capacity and from 226% to 22% for system count.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Life-cycle impact and exergy based resource use assessment of torrefied and non-torrefied briquette use for heat and electricity generation

Forest residue biomass can be used as bioenergy feedstock, however, issues associated with its properties including low density and high moisture content constrains its valorization. Using mobile conversion technologies that can operate in remote areas and are capable of converting forest residues into high quality energy products can address the issues associated with its valorization for renewable energy production. This study evaluated environmental sustainability of using an integrated novel system of semi-mobile biomass conversion technologies (BCTs) to utilize low-value forest residue biomass as high value bioenergy products. A cradle-to-grave life cycle assessment (LCA) and resource use assessment on a unit-process level was conducted for two bio-products: nontorrefied briquettes (NTB) and torrefied briquettes (TOB). Their use for production of useful thermal energy in wood stoves for domestic heating and electricity at power plants were investigated along with their alternatives. The analyses were performed with SimaPro 8.5 using the DATASMART database. The impact assessment results showed a notable decrease in global warming (GW) impact when substituting fossil fuels with these two bio-products. Specifically, for domestic heating on an equivalent energy basis, a 50% substitution of propane with NTB and TOB showed GHG emission reductions of 46% and 41%, respectively. For electricity generation, 10% cofiring at coal power plant with NTB and TOB showed GHG emission reductions of 6% and 8%, respectively. For the TOB supply chain, a large portion of the GW impact of the came from the torrefaction process and followed by the drying process. This was due to the propane use in these processes. Comparative analysis showed that near-woods biomass conversion for TOB production instead of processing feedstock at an in-town facility with access to grid electricity found 48%–55% lower GW impact for both electricity and heat generation scenarios, respectively. Resourced footprint analysis showed that most exergy extraction from the natural environment came from the drying process for NTB supply chain. In the TOB product system, torrefaction was the major contributor.

09 BIOMASS FUELS↗
DOE OSTI2016

An ecology-oriented exploitation mode of groundwater resources in the northern foot of Tianshan Mountain, China

In recent years, ecological degradation caused by irrational groundwater exploitation has been of growing concern in arid and semiarid regions. To address the groundwater-ecological issues, this paper proposes a groundwater-resource exploitation mode to evaluate the tradeoff between groundwater development and ecological environment in the northern Tianshan Mountains, northwest China’s Xinjiang Uygur Autonomous Region. Field surveys and remote sensing studies were conducted to analyze the relation between the distribution of hydrological conditions and the occurrence of ecological types. The results show that there is a good correlation between groundwater depth and the supergene ecological type. Numerical simulations and ecological assessment models were applied to develop an ecology-oriented exploitation mode of groundwater resources. The mode allows the groundwater levels in different zones to be regulated by optimizing groundwater exploitation modes. The prediction results show that the supergene ecological quality will be better in 2020 and even more groundwater can be exploited in this mode. This study provides guidance for regional groundwater management, especially in regions with an obvious water scarcity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Sustainable bioplastics derived from renewable natural resources for food packaging

Food packaging is one of the leading sectors for the end use of plastics. Bioplastic is produced from natural renewable resources such as crops, wood pulp, and herbaceous fibers. This article summarizes the rational design of bioplastics from natural resources for food packaging. The bioplastic properties considered include thermal properties, mechanical performance, oxygen/moisture resistance, and biodegradability. Bioplastic degradability and technologies for handling bioplastic waste are discussed. Various aspects of the sustainability of bioplastics (e.g., environmental profile, techno-economic analysis, and societal impact) are investigated. The main challenges of bioplastic application, such as low fracture strain and inferior barrier properties, are discussed. Mitigation approaches to overcome the mechanical properties of bioplastics, such as adding plasticizers, are also discussed. Bioplastic can have properties comparable with fossil-based plastics. In conclusion, bioplastic can be an alternative to conventional plastic in most applications of food packaging, which can reduce the carbon footprint and environmental impact because of its biodegradability.

09 BIOMASS FUELS↗