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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Grid Service Values of Generic Marginal Building Flexibility in Modeled 2030 U.S. Power Systems

The datasets include the capacity, energy, and ancillary service values of a marginal kilowatt-hour (kWh) of generic, daily, shiftable building flexibility as a presumed market entrant in the 2030 U.S. power systems. The results should be interpreted along with the caveats listed in "Valuation of Building Flexibility: Grid Service Value for Initial Market Entrants in Projected 2030 United States Power Systems", which also documents the methods used for the study. The factors examined in the study include: grid scenario, region, original usage hour in the day (local time), and building flexibility parameters - efficiency, dissipation, and shifting window include max pre-shift and max post-shift. Filenames in the datasets: The filenames contain information on the grid scenario, and the building flexibility efficiency and dissipation. For example: MidCase_2030_efficiency1.25_dissipation0.05_value.csv contains all results under Mid RE 2020, efficiency = 1.25, and dissipation = 0.05. * MidCase = Mid RE Each .csv file contains: region: The location of the building flexibility, aligned with U.S. Energy Information Administration (EIA) National Energy Modeling System (NEMS) Electricity Market Module regions. max_pre_shift: Part of building flexibility shifting window parameter, indicates the max number of hours the building flexibility can shift earlier. max_post_shift: Part of building flexibility shifting window parameter, indicates the max number of hours the building flexibility can shift later. local_datetime: Original datetime of 1kWh of building energy consumption. local_orig_h: Original usage hour (1-24) of building energy consumption, ignores daylight saving. local_shift_to: The datetime to when building energy consumption shifts, if shifting happens. If no shifting occurs, this cell is left blank. energy: Net energy value of energy shifting. capacity: Net capacity value of energy shifting. shifting_value: Net energy plus capacity value of energy shifting. spin: Spin reserve value at the original datetime of consumption. flex: Flexible reserve value at the original datetime of consumption. reg: Regulation reserve value at the original datetime of consumption. total_profit: Assuming the building flexibility is capable of providing energy, capacity, and ancillary services, total profit is the maximum value of energy shifting value, spin reserve value, flexible reserve value, and regulation reserve value - one of the four choices at any given hour - because we do not allow its value to be double-counted.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Analyzing Next-Generation Supply Chains Using the Materials Flows through Industry Tool

The Materials Flows through Industry (MFI) tool is a supply chain modeling tool developed at the National Renewable Energy Laboratory (NREL) with funding from the Department of Energy's Advanced Manufacturing Office. MFI was created to identify and analyze opportunities to reduce the energy and carbon intensities of the U.S. industrial sector (Hanes and Carpenter 2017). In this work, we present an overview of the MFI tool's structure and capabilities, as well as the results of using MFI to analyze a novel NREL-developed process to 'upcycle' PET plastic into higher-value composite materials (Rorrer et al. 2019). This process combines recycled PET (rPET) plastic with inputs that can be derived from biomass, including muconic acid, acrylic acid, and ethylene glycol, to chemically break down the plastic back to its monomers in a process called glycolization. Then, repolymerization and the application of fiberglass yields the valuable glass fiber reinforced plastic (GFRP) composite, a performance material used in the manufacture of wind turbine blades, boat hulls, and other applications. This rPET-derived GFRP was found to have superior strength and fiberglass adhesion compared to conventional GFRP formulations. Our findings indicate that this GFRP production process, were it to be widely commercialized beyond its current lab-scale, could potentially reduce the fossil energy intensity of the GFRP supply chain by between 37% and 58% compared to the conventional method of GFRP manufacture from fossil-derived inputs. We also estimate potential supply chain greenhouse gas (GHG) emissions reductions between 30% and 40% from this process. Scaling these GHG offset estimates up to annual GFRP production in the U.S. would be roughly equivalent to removing between 150,000 and 200,000 vehicles from U.S. roads. These ranges of impact estimates represent the range of differences associated with the various economic allocation methods we have assumed for the intensity contributions from the first life of the PET plastic. Following Shen et al. (2010), we derive economic allocation factors from the current price ratios of clear- and green-colored recycled PET plastic to virgin PET resin ('waste-valuation' approach) or assume them to be zero in a more simplistic allocation ('cutoff' approach). Future work involving the MFI modeling tool will also be discussed, including preliminary results comparing the energy intensity of conventional and bio-based nylons manufacturing. Attendees will also be encouraged to conduct MFI supply chain modeling of their own by requesting a user account on the MFI web application, which is freely available to the public at the following address: https://mfitool.nrel.gov.

36 MATERIALS SCIENCE↗
DOE OSTI2021

BETO 2021 Peer Review - Analytical Development & Support WBS 2.5.1.101

The objective of the Analytical Development and Support (ADS) Project is to produce and maintain the critical analytical methods and tools that enable evaluation of emerging biofuels R&D at NREL and in the broader biofuels research community. Our project is divided into two tasks: one task to develop novel analytical techniques and improve existing methods and one task to maintain existing analytical capabilities at NREL and provide outreach to the wider community. The ADS Project is world-recognized for our Laboratory Analytical Procedures (LAPS) which provide detailed procedures for compositional analysis of biomass and have been adopted as the de facto standards within the biofuels community largely due to the transparency of the methods and the high reputation of NREL's research. Our dialog with stakeholders allows us to provide robust, precise, accurate, and publicly available analytical procedures for better valuation of scientific tools such as our recent accomplishment in developing a cellulose assay to support the EPA and industry in calculation of converted cellulose during starch ethanol production. We continue to develop analytical capabilities to support BETO's directives to research cost advantaged fuels such as animal wastes and novel bioproducts like 2,3-Butane-diol.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Geothermal Representation in Power System Models

Power system models generally fail to capture the range of characteristics geothermal resources provide and the value they potentially contribute to decarbonization and reliability of future electricity grids as firm, dispatchable, non-combustion power resources. This study reviews the results of power system modeling efforts to investigate geothermal deployment potential in the United States, including the U.S. DOE GeoVision analysis and ongoing modeling and analysis efforts to support planning and development of future grids with 100% renewable energy in California. Several themes are identified that could be implemented immediately to improve the accuracy of geothermal representation in power system models: consistency of model inputs, modeling of baseload and dispatchable geothermal resources, accurate valuation of grid services, improved representation of capacity factor, use of contemporary LCOE estimates, improved understanding of the evolution of geothermal value, and use of accurate resource potential constraints. Many of the models reviewed produced significantly different amounts of geothermal resource selection - even when modeling the same region and time period. This highlights the variability of inputs and assumptions among models, so creating a consistent set of geothermal inputs is a first step toward more accurate representation of geothermal in models. Research opportunities are identified that could help improve geothermal data inputs in modeling efforts, including analyses of historical data, sensitivity to model inputs, and comparative value of geothermal generators as baseload or dispatchable resources. Outcomes of such research can inform the geothermal community about how best to guide geothermal development toward wider deployment in support of future electricity grids through improved understanding of the evolution of geothermal value over time and the characteristics that contribute to that value.

capacity expansion models↗
DOE OSTI2020

Quantifying Occupant Health and Productivity for Deep Retrofits: Beyond Traditional IEQ Studies

As energy-efficiency standards for both new construction and existing building renovations become more stringent, further reductions become less tractable and more expensive. With increasing interest and rising investment in healthy built environments, integrating energy efficiency with improved occupant experience (i.e., health, comfort, and work performance) offers a new path to drive deep energy retrofits. However, the difficulty in quantifying and verifying health and productivity gains from building upgrades leads to lower valuation of human benefits in practice. Building codes and standards have progressive energy targets but often give minimum requirements to occupant health for factors such as ventilation and thermal comfort. State and federal laws in the United States that govern the energy service performance contract (ESPC) have no clear and consistent guidance on quantifying non-energy benefits and incorporating them into a formal cost-effectiveness analysis. This paper presents a methodology to measure a building’s potential performance improvement regarding occupant health based on existing evidence correlating IEQ to occupant outcomes. Health improvement measures are integrated with a building energy model to identify and measure the impact of holistic improvement strategies. The net present value of these measures is determined based on the investment costs required to attain those improvements, energy savings, and personnel gains. We will discuss results from one pilot building, which showed nearly $50 per square foot 20-year net present value using the integrated approach.

Keene, Kevin M.↗
DOE OSTI2022

System and method for management of electrochemical energy storage devices

Methods and software for electrochemical energy storage management including operation, planning, and valuation. The decision objective for operation is to maximize the total/remaining life-cycle benefit of electrochemical energy storage, subject to degradation and other operational constraints. The operational decisions are both short term and long term, to address the intertemporal trade-offs brought by degradation issues. Two metrics are proposed for operational and planning decisions respectively: marginal benefit of usage and average benefit of usage. A sample algorithm is provided to solve the multi-timescale optimization problem.

Whitacre, Jay↗
DOE OSTI2022

A multi-level load shape clustering and disaggregation approach to characterize patterns of energy consumption behavior

This study presents representative electrical load shapes, disaggregated to the end-use level, for over 5000 customer clusters across California’s residential, commercial, industrial and agricultural sectors. We developed a novel, multi-level load shape clustering approach for residential and commercial sectors leveraging interval meter data for over 350,000 California utility customers collected as a part of the Phase 4 California Demand Response (DR) Potential Study. The clustering approach allowed us to identify typical consumption patterns and categorize customers based on their daily load shape displayed throughout the year. For example, we were able to identify customers with particular energy technologies such as electric vehicles and rooftop solar, as well as building occupancy types such as restaurants, grocery stores and even unoccupied buildings, based solely on whole-building interval data. We then combined the load shape-based clusters with other customer information including building type, climate, geographical area, total consumption and low-income status, to create a set of customer clusters based on both demographics and usage patterns. Total cluster electricity demand was then disaggregated into a wide variety of end-uses using weather normalization and other publicly available end-use load shape datasets. The resulting disaggregated cluster load shapes will be released in anonymized form as part of the Phase 4 DR Potential Study. They will have wide-ranging applications in energy research and policy analysis, including estimation of energy efficiency (EE) and DR potential on the end-use level, time-dependent valuation of EE savings, building stock modeling, and developing customer targeting strategies for EE and DR programs.

Murthy, Samanvitha↗
DOE OSTI2024

Experimental Considerations for Estimating Degradation in PV Modules

Carefully controlled laboratory experiments and measurements can enable the determination of acceleration factors suitable for extrapolation to durability and performance of a fielded PV module. Ideally, a single mechanism can be identified with appropriate acceleration factors for extrapolation to the field. However, even with a single mechanism, the inherent uncertainty in these factors leads to uncertainty in the extrapolation which is greater the higher the acceleration factor. This course will explain how because of the wide range of acceleration factors for a given degradation mode, utilizing acceleration factors greater than about 10x will typically lead to unacceptable uncertainty in the results. Therefore, if even just a rank ordering of materials is desired, acceleration factors must be minimized which requires a good general understanding of the scale of the different acceleration factors for the degradation mode of interest. In this tutorial we will discuss what the different purposes are for many of the accelerated stress tests used today. E.g., what is a qualification test, a highly accelerated stress test, a rank ordering test, or a service life prediction test. We will discuss how one can understand the relationship between test results and expected field performance. A single accelerated stress test condition cannot duplicate outdoor exposure for all possible degradation pathways; therefore, one must use targeted evaluation of material properties at different stress levels to determine the relevant acceleration factors and fit it to a model. We will also discuss how to interpret the results of experiments understanding what is relevant/not relevant, or not e valuated in a test. There are many common error people make in their test interpretations because they push the stress levels to be too harsh. This creates biases and can mask the relevant failure modes and mechanisms or will erroneously lead one to over design materials against things that aren't relevant. Several case studies will be presented to illustrate appropriate interpretation of accelerated stress testing results.

degradation↗
DOE OSTI2022

Case Study: Resilience Benefits of Distributed Wind Against Fuel and Weather Hazards in Alaska

In this case study of St. Mary’s Village, Alaska, we present a resilience evaluation exercise. A resilience framework is employed to identify system characteristics, relevant metrics, and resilience hazards and to assess the performance against the hazards with and without a distributed wind system installed. The results show the resilience benefits provided by the distributed wind installation against fuel shortage hazards and cold weather hazards. The resilience benefits can be assigned monetary values, which will be highly dependent on actual circumstances of the hazard, but provide insight into value streams of distributed wind that are not usually considered. For example, the single 900 kW turbine was found to prevent an average of 14,643 kWh of load from being dropped during a two-day diesel fuel shortage event, which saved the community $447,592 from the prevented outages. This case study serves as an example for novel power system resilience analysis and builds understanding of resilience hazards that are common across many power systems.

Culler, Megan J.↗
DOE OSTI2020

Increased nitrogen use efficiency in crop production can provide economic and environmental benefits

Potential economic and environmental benefits of increasing nitrogen-use efficiency (NUE) are widely recognized but scarcely quantified. This study quantifies the effects of increased NUE on 1) the national agricultural economy using a simulation model of US agriculture and 2) regional water quality effects using a biogeochemical model for the Arkansas-White-Red river basin. Here, national economic effects are reported for NUE improvement scenarios of 10%, 20%, 50%, and 100%, whereas regional water quality effects are estimated for a 20% NUE improvement scenario in the Arkansas-White-Red river basin. Simulating a 20% increase in NUE in row crops is shown to reduce N requirements by 1.4 million tonnes y-1 and increase farmer net profits by 1.6% ($743 million) per year by 2026 over the baseline simulation for the same period. For each 10% increase in NUE, annual farm revenues for commodity crops increased over the baseline by approximately $350 million per year by 2026. Changes in crop prices and land-use relative to the baseline were less than 2%. This suggests a net benefit even though fertilizer cost savings can result in increased cultivation of land, i.e., ‘Jevon's paradox’. Results from the biogeochemical model of the Arkansas-White-Red river basin suggest that a 20% increase in NUE corresponds to a 5.72% reduction in nitrate loadings to freshwaters, with higher reductions in agricultural watersheds. The value of these reductions was estimated as $43 ha-1, for a total of $15.3 to 136.7 million yr-1 in avoided water treatment costs. After estimating the social value of increased NUE, we conclude with a discussion of potential strategies to increase efficiency and the research needed to achieve this goal. These include perennialization of the agricultural landscape, genetic crop improvement, targeted fertilizer application, and manipulation of the plant-root microbiome.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

New Tool Evaluates the Financial Viability of Pumped Storage Hydropower

The rapidly evolving electricity system with increasing variable renewable energy (VRE) resources provides both opportunities and challenges for the power sector. With the significant ramps and intermittency associated with VRE resources, the requirements and need for additional flexible resources increase. Pumped storage hydropower (PSH) provides flexibility to the electricity grid to replace fossil fuel plants, which are responsible for 25% of U.S. emissions. PSH projects support various aspects of power system operations, including flexibility, ramping capability, energy, ancillary service, black start, and others. The significant potential of hydropower requires understanding the different value drivers to the electricity system specific to the location of a project and then optimizing the plant for the different system values. Thus, determining the value of PSH projects and their many services and contributions to the electricity system can be a challenge for potential developers, system owners, regulators, policy makers, and consultants.

13 HYDRO ENERGY↗
DOE OSTI2023

Cybersecurity Value-at-Risk Framework

As more variable renewable energy sources are added to the grid, the role of hydropower as a reliable baseline and firming resource is growing more critical. However, the U.S hydropower fleet is not fully prepared to face modern issues such as cybersecurity threats. Hydropower accounts for 37% of U.S. utility-scale renewable electricity but is challenged by diverse infrastructure and legacy devices that predate modern security practices. While new cybersecurity solutions cannot simply be added to current hydropower generation and operation technologies, custom cybersecurity assessments can reveal system-specific threats and risk probabilities and identify mitigating enhancements.

cybersecurity valuation methodology↗
DOE OSTI2022

Impact of Storage Dispatch Assumptions on Resource Adequacy and Capacity Credit

Representing energy-limited resources in power system probabilistic resource adequacy assessment introduces new considerations that invalidate classical modeling assumptions. In particular, such resources have multi-period operating objectives and constraints that in real systems are addressed via a sequence of rolling intertemporal optimizations. Ideally, adequacy models would develop dispatch decisions by solving a similar sequence of problems, but this approach has historically been too computationally intensive for practical use in Monte Carlo simulations, with studies making use of simplifying approximations instead. These simplifications have the potential to distort the assessed value of energy-limited resources on the system.This work describes three classes of storage dispatch assumptions in current use and discusses their theoretical differences. It then provides an empirical analysis of their differences on test systems with different levels of storage, assessing the potential for a study's modeling assumptions to influence the perceived contribution of energy-limited resources.

capacity credit↗
DOE OSTI2023

Quantitative approaches for including equity in risk and resilience infrastructure planning analyses

Risk and resilience assessments for critical infrastructure focus on myriad objectives, from natural hazard evaluations to optimizing investments. Although research has started to characterize externalities associated with current or possible future states, incorporation of equity priorities at project inception is increasingly being recognized as critical for planning related activities. However, there is no standard methodology that guides development of equity-informed quantitative approaches for infrastructure planning activities. Here, to address this gap, we introduce a logic model that can be tailored to capture nuances about specific geographies and community priorities, effectively incorporating them into different mathematical approaches for quantitative risk assessments. Specifically, the logic model uses a graded, iterative approach to clarify specific equity objectives as well as inform the development of equations being used to support analysis. We demonstrate the utility of this framework using case studies spanning aviation fuel, produced water, and microgrid electricity infrastructures. For each case study, the use of the logic model helps clarify the ways that local priorities and infrastructure needs are used to drive the types of data and quantitative methodologies used in the respective analyses. The explicit consideration of methodological limitations (e.g., data mismatches) and stakeholder engagements serves to increase the transparency of the associated findings as well as effectively integrate community nuances (e.g., ownership of assets) into infrastructure assessments. Such integration will become increasingly important to ensure that planning activities (which occur throughout the lifecycle of the infrastructure projects) lead to long-lasting solutions to meet both energy and sustainable development goals for communities.

community-based↗
DOE OSTI2021

Influence of Business Models on PV-Battery Dispatch Decisions and Market Value

PV-battery hybrid projects dominate interconnection queues in some regions in the United States, but few projects have been operational long enough to assess how the hybrid capabilities may be used in practice. We interview plant operators and analyze empirical dispatch data for eleven large-scale PV-battery hybrids in three organized wholesale markets in the United States. We use the dispatch data and wholesale market prices to estimate the market value of our sample hybrids in 2020. The empirical increase in market value of a PV-battery hybrid relative to a standalone PV plant varies by project and ranges from $\$$1 to $\$$48/MWhsolar. The premium is driven by market, location, technical characteristics of the PV and battery asset, and battery dispatch strategies. In contrast to the widespread assumptions in the PV-battery hybrid modeling literature, only three of the eleven project operators optimize battery usage for wholesale market revenue as merchant plants. Instead, the majority of operators in the sample have alternate objectives. For example, load-serving entities target peak load reductions, incentive program participants focus on compliance with program requirements, and large energy consumers prioritize resiliency and utility bill minimization. Understanding prevalent dispatch signals and the degree of alignment with system-wide grid needs can increase the market value of PV-battery hybrids.

14 SOLAR ENERGY↗