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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Temporal Resource Continuity Increases Predator Abundance in a Metapopulation Model: Insights for Conservation and Biocontrol

The amount of habitat in a landscape is an important metric for evaluating the effects of land cover on biodiversity, yet it fails to capture complex temporal dimensions of resource availability that could be consequential for species population dynamics. Here, we use a spatially-explicit predator–prey metapopulation model to test the effect of different spatiotemporal resource patterns on insect predators and their prey. We examined population responses in model landscapes that varied in both the amount and temporal variability of basal vegetation. Further, we examined cases where prey comprised either a single generalist species or two specialist species that use different resources available either early or late in the growing season. We found that predators and generalist prey benefitted from lower temporal variance of basal resources, which increased landscape-scale abundances. However, increasing the amount of basal resources also increased the variability of generalist prey populations. Specialist prey, on the other hand, did not benefit from less temporally variable basal resources, as they were restricted by habitat type, while also suffering greater predation. Predators achieved greater prey suppression in landscapes with less temporally variable resources, but the overall effects on prey abundance depended on prey habitat specialization. Our simulations demonstrate the joint importance of both the amount and temporal variability of resources for understanding how landscape heterogeneity influences biodiversity and ecosystem services such as the biological control of agricultural pests.

Spiesman, Brian↗
DOE OSTI2026

Value of Geothermal Energy Storage for Supply-Side and Demand-Side Applications

This report presents the results of a study examining the value potential for geothermal energy storage (GES), a long-duration energy storage resource that stores thermal and/or geomechanical energy in the subsurface. GES could benefit the overall U.S. power system by temporally shifting electricity generation (supply-side) or meeting building heating and cooling load (demand-side). This report analyzes supply-side and demand-side opportunities independently because of differences in applications and models. Currently there is significant uncertainty about the development costs for GES, with only a limited number of demonstration plants for electric energy storage and building heating and cooling storage developments. In this report, we estimate the value of supply-side and demand-side GES to the bulk power system in the contiguous United States. Because of the significant uncertainty about GES development costs, this analysis does not consider GES deployment costs but instead focuses on the value of GES to the U.S. electricity system. The estimated values of GES provide reference points for economically competitive commercial cost targets. Supply-side GES is modeled as part of an enhanced geothermal system (EGS) generation plant in NREL's Regional Energy Deployment System (ReEDS) capacity expansion model (Ho et al. 2021). In contrast to conventional geothermal plants, which generate constant power, EGS plants have unique features that may allow for in-reservoir energy storage for flexible generation. Demand-side GES for heating and cooling, including seasonal hot and cold storage and short-duration heat pump storage, is incorporated into a price-taker model using Cambium electricity marginal cost projections. To establish an upper bound for the value of GES, analysis focused on favorable scenarios for storage with high generation from zero marginal cost, variable renewable energy resources. High penetrations of variable renewable energy generation can increase hourly electricity price variability, which increases the value of temporal energy arbitrage for storage technologies like GES.

15 GEOTHERMAL ENERGY↗
NASA NTRS1993

Resource utilization model for the algorithm to architecture mapping model

The analytical model for resource utilization and the variable node time and conditional node model for the enhanced ATAMM model for a real-time data flow architecture are presented in this research. The Algorithm To Architecture Mapping Model, ATAMM, is a Petri net based graph theoretic model developed at Old Dominion University, and is capable of modeling the execution of large-grained algorithms on a real-time data flow architecture. Using the resource utilization model, the resource envelope may be obtained directly from a given graph and, consequently, the maximum number of required resources may be evaluated. The node timing diagram for one iteration period may be obtained using the analytical resource envelope. The variable node time model, which describes the change in resource requirement for the execution of an algorithm under node time variation, is useful to expand the applicability of the ATAMM model to heterogeneous architectures. The model also describes a method of detecting the presence of resource limited mode and its subsequent prevention. Graphs with conditional nodes are shown to be reduced to equivalent graphs with time varying nodes and, subsequently, may be analyzed using the variable node time model to determine resource requirements. Case studies are performed on three graphs for the illustration of applicability of the analytical theories.

Stoughton, John W.↗
DOE OSTI2011

Flexibility Reserve Reductions from an Energy Imbalance Market with High Levels of Wind Energy in the Western Interconnection

The anticipated increase in variable generation in the Western Interconnection (WI) over the next several years has raised concerns about how to maintain system balance, especially in smaller Balancing Areas (BAs). Given renewable portfolio standards in the West, it is possible that more than 50 gigawatts (GW) of wind capacity will be installed by 2020. Significant quantities of solar generationare likely to be added as well. The consequent increase in variability and uncertainty that must be managed by the conventional generation fleet and responsive load make it attractive to consider ways in which Balancing Area Authorities (BAAs) can pool their variability and response resources, thus taking advantage of geographic and temporal diversity to increase overall operational efficiency.Our analysis considers several alternative forms of an Energy Imbalance Market (EIM) that have been proposed in the non-market areas of the WI. The proposed EIM includes two changes in operating practices that independently reduce variability and increase access to responsive resources: BAA cooperation and sub-hourly dispatch. As proposed, the EIM does not consider any form of coordinated unitcommitment; however, over time it is possible that BAAs would develop formal or informal coordination plans. This report examines the benefits of several possible EIM implementations, both separately and in concert.

17 WIND ENERGY↗
DOE OSTI2018

The impact of planning reserve margins in long-term planning models of the electricity sector

The planning reserve margin is the predominant metric used in long-term planning models to ensure the resource adequacy of projected power systems. Considerable work has been done to estimate the contribution of variable renewable energy resources, such as wind and solar, to the planning reserve margin, but little work has been done to assess what planning reserve margin should be used in planning models. Typically, U.S.-based models use the North American Electric Reliability Corporation (NERC)-recommended reserve margin levels. However, historical reserve margins have often exceeded the NERC-recommended levels, suggesting that the use of NERC-recommended levels in planning models may negatively bias projected future capacity investments relative to real-world trends. Using the Regional Energy Deployment System capacity expansion model, we show that setting the planning reserve margin to observed levels in lieu of the NERC-recommended levels leads to substantial differences in near-term capacity additions. Scenarios using alternative specifications for the reserve margin resulted in increased national solar builds of 20-100 GW. Given that the magnitude on results from altering the reserve margin level is similar to or greater than many policies frequently analyzed with planning models, careful consideration of the reserve margin level is crucial for developing accurate power sector projections.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

Market Evolution: Wholesale Electricity Market Design for 21st Century Power Systems

Demand for affordable, reliable, domestically sourced, and low-carbon electricity is on the rise. This growing demand is driven in part by evolving public policy priorities, especially reducing the health and environmental impacts of electricity service and expanding energy access to under-served customers. Consequently, variable renewable energy resources comprise an increasing share ofelectricity generation globally. At the same time, new opportunities for addressing the variability of renewables are being strengthened through advances in smart grids, communications, and technologies that enable dispatchable demand response and distributed generation to extend to the mass market. A key challenge of merging these opportunities is market design -- determining how to createincentives and compensate providers justly for attributes and performance that ensure a reliable and secure grid -- in a context that fully realizes the potential of a broad array of sources of flexibility in both the wholesale power and retail markets. This report reviews the suite of wholesale power market designs in use and under consideration to ensure adequacy, security, and flexibilityin a landscape of significant variable renewable energy. It also examines considerations needed to ensure that wholesale market designs are inclusive of emerging technologies, such as demand response, distributed generation, and storage.

21st Century Power Partnership↗
DOE OSTI2024

Tools And Methods to Analyze Plant Outage Schedule and Assist Schedulers in Improving Outage Resilience

Refueling outages of nuclear power plants (NPPs) are considered one of the most critical phases throughout the plant lifetime. In such instances, tens of thousands of activities (e.g., maintenance, surveillance) are performed in a short amount of time (typically 2-3 weeks unless major backfitting or modernization projects are carried out) by a large number of crews (e.g., electricians, mechanics) that are hired as contractors. As a consequence, a plant outage can be expensive not only in terms of costs (e.g., contractor labor, material), but also in terms of loss generation since the plant is taken off the grid during the full outage duration (an indicative metric is about 1.2M$/day of loss of revenue). Thus, there is a continuous need to decrease the economic impact of outages on plant finances. This can be done by: decreasing the frequency of plant outages (e.g., from 18 to 24 months), reducing the time to complete the outage, and reducing the risk of outage delays. The Optimization of Outage Activities project under the Risk Informed Systems Analysis Pathway (RISA) sponsored by Department of Energy (DOE) Light Water Reactor Sustainability (LWRS) Program focuses on developing tools and methods to support NPPs with outage schedule optimization. The developed tools and methods are designed to analyze plant outage schedule with the goal of identify critical elements in the schedule that might pose a high risk of delays. These methods and tools can be considered resource-centric in the sense that they address outage challenges as a resource optimization problem. In this context, resources are either time and crews; outage delays occurs when either (or both) resources are insufficient to complete the set of tasks assigned at a specific time instant of the outage. This report provides details on how plant resources (time and crews) can be allocated in such a way that delays are minimized. In this respect, two classes of methods have been developed: the first one focuses on the time resource and how variability of the time to complete outage tasks may impact outage delays. The second one integrates available resources to assess when dailies activities should be performed such that the risk of outage delays are minimized.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Capturing Inter-Annual Variability of PV Energy Production in South Asia

Long-term variability of solar resource is an important factor in planning a utility-scale photovoltaic (PV) generation plant, and annual generation for a given location can vary significantly from year to year. Based on multiple years of solar irradiance data, an exceedance probability is the amount of energy that could potentially be produced by a power plant in any given year. An exceedance probability accounts for long-term variability and climate cycles (e.g., monsoons or changes in aerosols), which ultimately impact PV energy generation. Study results indicate that a significant bias could be associated with relying solely on typical meteorological year (TMY) resource data to capture long-term variability. While the TMY tends to under-predict annual generation overall compared to the P50, there appear to be pockets of over-prediction as well.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2015

Analysis of the Effects of a Flexible Ramping Ancillary Service Product on Power System Operations: Preprint

The recent increased interest in utilizing variable generation (VG) resources such as wind and solar in power systems has motivated investigations into new operating procedures. Although these resources provide desirable value to a system (e.g., no fuel costs or emissions), interconnecting them provides unique challenges. Their variable, non-controllable nature in particular requires significant attention, because it directly results in increased power system variability and uncertainty. One way to handle this is via new operating reserve schemes. Operating reserves provide upward and downward generation and ramping capacity to counteract uncertainty and variability prior to their realization. For instance, uncertainty and variability in real-time dispatch can be accounted for in the hour-ahead unit commitment. New operating reserve methodologies that specifically account for the increased variability and uncertainty caused by VG are currently being investigated and developed by academia and industry. This paper examines one method inspired by the new operating reserve product being proposed by the California Independent System Operator. The method is based on examining the potential ramping requirements at any given time and enforcing those requirements via a reserve demand curve in the market-clearing optimization as an additional ancillary service product.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Demand Response in Bangalore: Implications for Electricity System Operations

Recent Greening the Grid studies for India highlight the benefits of flexible resources for integrating variable renewable energy onto India’s electricity system. India’s ambitious renewable energy targets, which are particularly focused on renewable resource states such as Karnataka, will face fewer challenges when combined with new planning and operational strategies and technologies. This report explores one such strategy - demand response - by which the system operator shifts load throughout a day to minimize system wide production costs. To explore this strategy, we added demand response resources to Karnataka’s electricity system in a production cost model of India, using load shifting potential analyzed by Lawrence Berkeley National Labs. We then investigated the impacts of increasing demand response capacity under several renewable resource scenarios. Our results show the addition of demand response enables fuel shifting from high-marginal-cost and emissions-intensive subcritical coal and diesel generation to zero-marginal-cost and emissions-free renewable generation. Accordingly, the value that demand response provides to the system increases as the renewable penetration increases. In addition to reducing production costs and emissions, demand response reduces the time that thermal generators spend at their minimum output levels, which typically represents a less efficient and costlier operational state. Agricultural load shifting provides greater value to the system than residential, commercial, or industrial loads. Agricultural demand response is more flexible than other sectors because it is not exposed to subdaily operational constraints and it can operate for more hours per day without impacting customer satisfaction. Further, the first increment of demand response that is added to a system provides the greatest value; further additions provide additional benefits but have a decreasing impact. The insights we discuss could be leveraged by system planners and operators in other jurisdictions, particularly those facing significant renewable energy penetrations, to develop their own demand response programs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Dynamic security assessment of systems powered only by grid-forming power plants with uncertain dispatch using polynomial vectors

A modern challenge in power engineering is to perform the dynamic security assessment (DSA) of grids that are 100% powered by inverter-based resources (IBRs). Addressing this challenge is difficult because: (i) the dispatch of IBRs can be uncertain as a result of the variability of renewable resources and (ii) they have hard current control limits that cannot be neglected, contrasting synchronous machines. To address this problem, this paper sets forth a framework to conduct DSA of bulk power systems that are 100% powered by grid-forming IBRs. Furthermore, the framework considers that IBR operational conditions are unknown but bounded by a zonotope which is also expressed as a polynomial vector for uncertainty propagation via Dormand–Prince integration. The framework is applied to modified versions of the WSCC 9-bus and IEEE 39-bus grids.

14 SOLAR ENERGY↗
DOE OSTI2015

Role of Concentrating Solar Power in Integrating Solar and Wind Energy: Preprint

As wind and solar photovoltaics (PV) increase in penetration it is increasingly important to examine enabling technologies that can help integrate these resources at large scale. Concentrating solar power (CSP) when deployed with thermal energy storage (TES) can provide multiple services that can help integrate variable generation (VG) resources such as wind and PV. CSP with TES can provide firm, highly flexible capacity, reducing minimum generation constraints which limit penetration and results in curtailment. By acting as an enabling technology, CSP can complement PV and wind, substantially increasing their penetration in locations with adequate solar resource.

14 SOLAR ENERGY↗
DOE OSTI2026

Data Analytics Methods to Measure Plant Outage Resilience

Every 18 or 24 months nuclear power plants (depending on plant configuration, pressurized or boiling water reactor respectively) undergo a period of outage where the plant is taken offline and a large number of maintenance and surveillance activities (that cannot be performed while plant is running) are performed in typically 2–3 weeks. Planning of a plant outage is very challenging since all the activities are required to be performed in the shortest amount of time given available resources (typically contractor crews hired for the duration of the outage). Consequently, plant outages can be costly due the actual loss of power generation and crew costs and, because of it, there is a need to maximize resource usage in the outage planning phase and reduce the risk of outage delays. This paper is addressing these needs by providing a set of analytical methods designed to analyze plant outage schedule and identify critical elements based on available resources (time and crews). These methods are based on natural language processing and optimization algorithms. In this respect, two classes of methods have been developed: one that focuses on the time resource and how variability in the time to complete outage tasks may impact outage delays, and one that minimizes the risk of outage delays by integrating available resources to assess when daily activities should be performed.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2018

Incentivizing Flexibility in System Operations

Defining flexibility has been a challenge that a number of industry members and researchers have attempted to address in recent years. With increased variability and uncertainty of variable generation (VG), the resources on the system will have to be more flexible to adjust output, so that power output ranges, power ramp rates, and energy duration sustainability are sufficient to meet the needs of balancing supply with demand at various operational timescales. This chapter discusses whether existing market designs provide adequate incentives for resources to offer their flexibility into the market to meet the increased levels of variability and uncertainty introduced by VG in the short-term operational time frame. It presents a definition of flexibility and discusses how increased levels of VG require increased needs for flexibility on power systems. Following this introductory material, the chapter examines how existing market designs ensure that resources have the right incentives to provide increased flexibility, and then discusses a number of emerging market design elements that impact flexibility incentives.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2013

Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison: Preprint

One of the critical challenges of wind power integration is the variable and uncertain nature of the resource. This paper investigates the variability and uncertainty in wind forecasting for multiple power systems in six countries. An extensive comparison of wind forecasting is performed among the six power systems by analyzing the following scenarios: (i) wind forecast errors throughout a year; (ii) forecast errors at a specific time of day throughout a year; (iii) forecast errors at peak and off-peak hours of a day; (iv) forecast errors in different seasons; (v) extreme forecasts with large overforecast or underforecast errors; and (vi) forecast errors when wind power generation is at different percentages of the total wind capacity. The kernel density estimation method is adopted to characterize the distribution of forecast errors. The results show that the level of uncertainty and the forecast error distribution vary among different power systems and scenarios. In addition, for most power systems, (i) there is a tendency to underforecast in winter; and (ii) the forecasts in winter generally have more uncertainty than the forecasts in summer.

17 WIND ENERGY↗
DOE OSTI2025

Toward Mixed Analog-Digital Quantum Signal Processing: Quantum AD/DA Conversion and the Fourier Transform

Signal processing stands as a pillar of classical computation and modern information technology, applicable to both analog and digital signals. Recently, advancements in quantum information science have suggested that quantum signal processing (QSP) can enable more powerful signal processing capabilities. However, the developments in QSP have primarily leveraged digital quantum resources, such as discrete-variable (DV) systems like qubits, rather than analog quantum resources, such as continuous-variable (CV) systems like quantum oscillators. Consequently, there remains a gap in understanding how signal processing can be performed on hybrid CV-DV quantum computers. Here we address this gap by developing a new paradigm of mixed analog-digital QSP. We demonstrate the utility of this paradigm by showcasing how it naturally enables analog-digital conversion of quantum signals—specifically, the transfer of states between DV and CV quantum systems. We then show that such quantum analog-digital conversion enables new implementations of quantum algorithms on CV-DV hardware. This is exemplified by realizing the quantum Fourier transform of a state encoded on qubits via the free-evolution of a quantum oscillator, albeit with a runtime exponential in the number of qubits due to information theoretic arguments. Collectively, this work marks a significant step forward in hybrid CV-DV quantum computation, providing a foundation for scalable analog-digital signal processing on quantum processors.

42 ENGINEERING↗
DOE OSTI2015

Sources of biomass feedstock variability and the potential impact on biofuels production

In this study, terrestrial lignocellulosic biomass has the potential to be a carbon neutral and domestic source of fuels and chemicals. However, the innate variability of biomass resources, such as herbaceous and woody materials, and the inconsistency within a single resource due to disparate growth and harvesting conditions, presents challenges for downstream processes which often require materials that are physically and chemically consistent. Intrinsic biomass characteristics, including moisture content, carbohydrate and ash compositions, bulk density, and particle size/shape distributions are highly variable and can impact the economics of transforming biomass into value-added products. For instance, ash content increases by an order of magnitude between woody and herbaceous feedstocks (from ~0.5 to 5 %, respectively) while lignin content drops by a factor of two (from ~30 to 15 %, respectively). This increase in ash and reduction in lignin leads to biofuel conversion consequences, such as reduced pyrolysis oil yields for herbaceous products as compared to woody material. In this review, the sources of variability for key biomass characteristics are presented for multiple types of biomass. Additionally, this review investigates the major impacts of the variability in biomass composition on four conversion processes: fermentation, hydrothermal liquefaction, pyrolysis, and direct combustion. Finally, future research processes aimed at reducing the detrimental impacts of biomass variability on conversion to fuels and chemicals are proposed.

09 BIOMASS FUELS↗