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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Adaptive Cognitive Mechanisms to Maintain Calibrated Trust and Reliance in Automation

Trust calibration for a human–machine team is the process by which a human adjusts their expectations of the automation’s reliability and trustworthiness; adaptive support for trust calibration is needed to engender appropriate reliance on automation. Herein, we leverage an instance-based learning ACT-R cognitive model of decisions to obtain and rely on an automated assistant for visual search in a UAV interface. This cognitive model matches well with the human predictive power statistics measuring reliance decisions; we obtain from the model an internal estimate of automation reliability that mirrors human subjective ratings. The model is able to predict the effect of various potential disruptions, such as environmental changes or particular classes of adversarial intrusions on human trust in automation. Finally, we consider the use of model predictions to improve automation transparency that account for human cognitive biases in order to optimize the bidirectional interaction between human and machine through supporting trust calibration. The implications of our findings for the design of reliable and trustworthy automation are discussed.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Probabilistic Deliverability Assessment of Distributed Energy Resources via Scenario-Based AC Optimal Power Flow

As electric grids decarbonize and distributed energy resources (DERs) become increasingly prevalent, interconnection assessments must evolve to reflect operational variability and control flexibility. This paper highlights key modeling limitations observed in practice and reviews approaches for modeling uncertainty. It then introduces a Probabilistic Deliverability Assessment (PDA) framework designed to complement and extend existing procedures. The framework integrates scenario-based AC optimal power flow (AC OPF), corrective dispatch, and optional multi-temporal constraints. Together, these form a structured methodology for quantifying DER utilization, deliverability, and reliability under uncertainty in load, generation, and topology. Outputs include interpretable metrics with confidence intervals that inform siting decisions and evaluate compliance with reliability thresholds across sampled operating conditions. A case study on Puerto Rico’s publicly available bulk power system model demonstrates the framework’s application using minimal input data, consistent with current interconnection practice. Across staged fossil generation retirements, the PDA identifies high-value DER sites and regions requiring additional reactive power support. Results are presented through mean dispatch signals, reliability metrics, and geospatial visualizations, demonstrating how the framework provides transparent, data-driven siting recommendations. The framework’s modular design supports incremental adoption within existing workflows, encouraging broader use of AC OPF in interconnection and planning contexts.

14 SOLAR ENERGY↗
DOE OSTI2021

Designing the Insulation System for Motors in Electrified Aircraft: Optimization, Partial Discharge Issues and Use of Advanced Materials

Designing the insulation system for motors to be used in electrical aircraft requires efforts for maximizing specific power, but, in parallel, particular attention to achieve high reliability. As a major harm for organic insulation systems is partial discharges, design must be able to infer their likelihood during any operation stage and handle their potential inception. This paper proposes a new approach to carry out optimized or conservative insulation system designs which can provide the specified life at the chosen failure probability as well as look at the option of possibly reducing the risk of partial discharges to zero, at any altitude. Examples of designing turn, phase to ground and phase-to-phase insulation systems are reported, with cases where the design can be optimized and other cases where the optimized design does not pass IEC testing standard. Therefore, the limits for design feasibility as a function of the required level of safety and reliability are discussed, showing that the presence of partial discharges cannot be always avoided even through conservative design criteria. Therefore, the use of advanced, corona-resistant materials must be considered, in order to reach a higher, sometimes redundant, level of reliability.

Ramin, Robin (ORCID:0000000211455006)↗
DOE OSTI2020

Multi-Temporal Predictive Modelling of Sorghum Biomass Using UAV-Based Hyperspectral and LiDAR Data

High-throughput phenotyping using high spatial, spectral, and temporal resolution remote sensing (RS) data has become a critical part of the plant breeding chain focused on reducing the time and cost of the selection process for the “best” genotypes with respect to the trait(s) of interest. In this paper, the potential of accurate and reliable sorghum biomass prediction using visible and near infrared (VNIR) and short-wave infrared (SWIR) hyperspectral data as well as light detection and ranging (LiDAR) data acquired by sensors mounted on UAV platforms is investigated. Predictive models are developed using classical regression-based machine learning methods for nine experiments conducted during the 2017 and 2018 growing seasons at the Agronomy Center for Research and Education (ACRE) at Purdue University, Indiana, USA. The impact of the regression method, data source, timing of RS and field-based biomass reference data acquisition, and the number of samples on the prediction results are investigated. R2 values for end-of-season biomass ranged from 0.64 to 0.89 for different experiments when features from all the data sources were included. Geometry-based features derived from the LiDAR point cloud to characterize plant structure and chemistry-based features extracted from hyperspectral data provided the most accurate predictions. Evaluation of the impact of the time of data acquisition during the growing season on the prediction results indicated that although the most accurate and reliable predictions of final biomass were achieved using remotely sensed data from mid-season to end-of-season, predictions in mid-season provided adequate results to differentiate between promising varieties for selection. The analysis of variance (ANOVA) of the accuracies of the predictive models showed that both the data source and regression method are important factors for a reliable prediction; however, the data source was more important with 69% significance, versus 28% significance for the regression method.

09 BIOMASS FUELS↗
DOE OSTI2020

Empirical Study of Effect of Dynamic Travel Time Information on Driver Route Choice Behavior

The objective of this paper is to study the effect of travel time information on day-to-day driver route choice behavior. A real-world experimental study is designed to have participants repeatedly choose between two alternative routes for five origin-destination pairs over multiple days after providing them with dynamically updated travel time information (average travel time and travel time variability). The results demonstrate that historical travel time information enhances behavioral rationality by 10% on average and reduces inertial tendencies to increase risk seeking in the gain domain. Furthermore, expected travel time information is demonstrated to be more effective than travel time variability information in enhancing rational behavior when drivers have limited experiences. After drivers gain sufficient knowledge of routes, however, the difference in behavior associated with the two information types becomes insignificant. The results also demonstrate that, when drivers lack experience, the faster less reliable route is more attractive than the slower more reliable route. However, with cumulative experiences, drivers become more willing to take the more reliable route given that they are reluctant to become risk seekers once experience is gained. Furthermore, the effect of information on driver behavior differs significantly by participant and trip, which is, to a large extent, dependent on personal traits and trip characteristics.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Near-infrared Spectral Characterization of Solar-type Stars in the Northern Hemisphere

Although solar-analog stars have been studied extensively over the past few decades, most of these studies have focused on visible wavelengths, especially those identifying solar-analog stars to be used as calibration tools for observations. As a result, there is a dearth of well-characterized solar analogs for observations in the near-infrared, a wavelength range important for studying solar system objects. We present 184 stars selected based on solar-like spectral type and V−J and V−K colors whose spectra we have observed in the 0.8–4.2 μm range for calibrating our asteroid observations. Each star has been classified into one of three ranks based on spectral resemblance to vetted solar analogs. Of our set of 184 stars, we report 145 as reliable solar-analog stars, 21 as solar analogs usable after spectral corrections with low-order polynomial fitting, and 18 as unsuitable for use as calibration standards owing to spectral shape, variability, or features at low to medium resolution. We conclude that all but five of our candidates are reliable solar analogs in the longer wavelength range from 2.5 to 4.2 μm. The average colors of the stars classified as reliable or usable solar analogs are V−J = 1.148, V−H = 1.418, and V−K = 1.491, with the entire set being distributed fairly uniformly in R.A. across the sky between −27° and +67° in decl.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

A Computer Design Tool for Ceramic Receivers

Gen3 solar receivers and other components will experience a combination of high temperatures and high stress caused by thermal stress and internal pressure. Under these conditions metallic components, even those manufactured from nickel-based superalloys, have poor reliability. Engineering ceramics could be a solution, as these materials have excellent high temperature strength. However, accurately assessing the reliability of a ceramic component operating in these conditions requires an entirely different approach compared to metallic materials. This paper describes the implementation of statistical models for evaluating the reliability of high temperature ceramic components in srlife – an open-source software package for estimating the life of high temperature concentrating solar power equipment. This new capability allows users to make fair comparisons between competing metallic and ceramic component designs and to accurately assess the plant efficiency and economics of ceramic solar receivers and other components.

Messner, Mark (ORCID:0000000200404385)↗
DOE OSTI2025

ARM SGP PBLH and MLH datasets from Raman lidar and Doppler lidar

The planetary boundary layer (PBL) plays a critical role in the atmosphere by transferring heat, moisture, and momentum. The warm PBL has a distinct diurnal cycle including the daytime convective mixing layer (ML) and nighttime residual layer developments. Thus, simultaneous determinations of PBL height (PBLH) and ML height (MLH) are necessary for studying PBL characterization and processes. Here, new approaches are developed to provide reliable PBLH and MLH estimates to characterize warm PBL evolution. The approaches use Raman lidar (RL) water vapor mixing ratio (WVMR) and Doppler lidar (DL) vertical velocity measurements at the Southern Great Plains (SGP) atmospheric observatory, which was established by the Atmospheric Radiation Measurement (ARM) User Facility. Compared to widely used lidar aerosol measurements for PBLH, WVMR is a better tracer for PBL vertical mixing. For PBLH, the approach classifies PBL water vapor structures into a few general patterns, then uses a slope method and dynamic threshold method to determine PBLH. For MLH, wavelet analysis is used to reconstruct 2D variance from DL vertical wind velocity measurements according to the turbulence eddy size to minimize the impacts of gravity wave and eddy size on variance calculations; then, a dynamic threshold method is used to determine MLH. Remotely-sensed PBLHs and MLHs are compared with radiosonde measurements based on the Richardson number method. Good agreements between them confirm that the proposed new algorithms are reliable for PBLH and MLH characterization. The algorithms are applied to warm-season RL and ML measurements at the SGP site for five years to study warm-season PBL structure and processes. The weekly composited diurnal evolutions of PBLHs and MLHs in a warm climate were provided to illustrate diurnal and seasonal PBL evolutions. This reliable data set of PBLH and MLH values will be valuable for studying PBL processes, model evolution, and PBL parameterization improvements. The MLH dataset includes the MLH in values of km above ground level. The PBLH dataset includes the PBLH in values of km above ground level, along with a flag ("situation_PBLH") to determine the state of the PBL (1 = Cloudy Condition, 2 = Stable Layer, 3 = Multi-layer WVMR structure, 4 = Well-Mixed PBL, 5 = A de-coupled layer, 6 = Other).

mixing layer height↗
DOE OSTI2024

Datasets for Widespread Residential Space Heating Electrification in Texas

In this experiment, we explore long term patterns in electricity demand driven by the dual effects of full electrification of space heating in Texas (by adoption of electric heat pumps), and climate change. We use a predictive model of electricity demand, climate projections, and an open source nodal power system (DC Optimal Power Flow) model of the Electric Reliability Council of Texas (ERCOT) system. Heat pumps are a more energy efficient way of providing space heating and cooling in homes. We attempt to exhaustively investigate the impacts of full residential space heating electrification by adoption of heat pumps for the segment of Texas households that currently rely on fossil fuels (about 40%), while simultaneously incorporating climate change meteorological variables. We explore a range of scenarios of heat pump efficiency and climate uncertainty over a long period of future years (2020-2099). In total, the simulation experiment generates 1,280 simulation years of hourly data. We report and analyze results in form of impacts on residential load, total load, peak load, seasonality of peaking, and reliability measured by occurrence and frequency of loss of load events. While the experiment is for ERCOT, the insights and approach can be applied to other regions. The results from the analysis can inform system planners on a range of potential capacity requirements/ reliability implications and/or risks of full space heating electrification via the adoption of electric heat pumps, given the uncertainty in the scenarios/ climate futures. The dataset includes model output for residential, non residential and total load, and the results from the GO ERCOT model runs for 4 RCP Scenarios (RCP 4.5 Cooler, RCP 4.5 Hotter, RCP 8.5 Cooler, RCP 8.5 Hotter), 4 Heating electrification Scenarios (Base , Standard Efficiency HP, High Efficiency HP, Ultra-High Efficiency HP) over 80 years (2020-2099). The metrological variables at BA scale were weighted weighted using population projections consistent with the SSP3 scenario.

Climate Change↗
DOE OSTI2020

Considerations when Implementing Shift Work in Nuclear Operations

Many domestic and international nuclear facilities have processes that require personnel to work on some type of shift. Shift work has many different schedules such as night, morning, swing, and rotating shift. Some common shifts are DuPont, Pitman, and Panama. There are many psychological and physiological impacts to a person working shifts. These impacts can affect work performance, safety, and security within an organization. A well-established nuclear organization relies on a strong security culture that implements a trustworthiness or reliability program. The IAEA defines this type of program as individuals meeting the highest standards of reliability, trustworthiness, and physical and mental suitability. Psychological and physiological impacts that apply to a Trustworthiness Program are reliability (an individual’s ability to adhere to security and safety rules and regulations) and physical and mental suitability. If shift work isn’t properly implemented in Facility Operations, then several issues or human factors can arise. An employee that suffers from a poorly designed shift, gets overworked, or doesn’t have the proper rest period implemented, may suffer from shift work disorder, acute fatigue, or cumulative fatigue. Introducing fatigue into Facility Operations can have severe consequences to security, safety, production, and cost. Another challenge of shiftwork within a facility is laziness and complacency. Creating an atmosphere where the employee is willing to admit fatigue to his or her supervisor is a challenge. It is up to the organization to do the needed research on shift work and to implement the best shift for their facility and personnel.

Stockwell, Brandon↗
DOE OSTI2020

Impact of High PV Penetration on Voltage Stability

Photovoltaics (PV) are becoming increasingly relevant in modern power systems. With this increase also comes reliability concerns as photovoltaics behave differently than conventional generators. One reliability concern is voltage stability. In this paper, voltage stability of the Austin area in the Electric Reliability Council of Texas (ERCOT) system is studied using dynamic models with varying levels of photovoltaic penetration. The base case is set at 0% renewable penetration. Additional cases include 15% wind penetration and up to 65% photovoltaic penetration. The study results show that voltage/var control capacity is critical to voltage stability, which PV lacks. Voltage regulation of photovoltaics may cause over-voltage and voltage collapse may be more abrupt under high regional photovoltaic penetration.

Till, Jeremy↗
DOE OSTI2020

STRUCTURE AND PROPERTIES STUDY ON ENERGY MATERIALS: THERMOELECTRIC MATERIAL TETRAHEDRITE AND LITHIUM ION CONDUCTOR

Development of efficient energy materials is critical in order to ease the energy demand and reduce our dependence of fossil fuel. Thermoelectric materials are promising due to their capability of generating electrical power by recovering waste heat. The performance of thermoelectric materials is quantified by a dimensionless figure of merit zT, which depends on their properties such as electrical conductivity, Seebeck coefficient and thermal conductivity. Tetrahedrites, a copper antimony sulfosalt mineral, typified by Cu 12-x MxSb 4 S 13 , where M is a transition metal element such as Ni, Zn, Fe or Mn, have great potential for thermoelectric application due to their relatively high zT (close to 1 at 700 K), earth-abundance, environmental friendliness, favorable electrical properties, and most importantly intrinsic low lattice thermal conductivity (less than 1 W m -1 K -1 ) in wide temperature. In addition to energy recovery, reliable energy storage devices are also emerging to relieve the energy demand and improve the efficiency of consuming energy resources. Lithium-ion batteries are known to be reliable and successful electrochemical energy storage devices and appliable in various aspects, including laptops, smartphones and electrical vehicles. Lithium phosphorous oxynitride (LiPON) are widely used as thin-film solid-state electrolytes in Li-ion battery, which is the only demonstrated solid-state electrolyte that is quite stable in direct contact with Li metal at potentials from 0-5 V. However, the structure of LiPON, the effects of N doping, and the origin of its good electrochemical stability remains inconclusive. In this thesis, reliable modeling techniques accompanied with experimental tools, are applied to study the thermoelectric material tetrahedrite and the ionic conductor LiPON, in order to study their structural and dynamical properties. Accurate and efficient density-functional theory (DFT) and density-functional tight-binding (DFTB) methods, combined with molecular dynamics (MD) simulations are utilized in order to investigate the structures and properties of these energy materials. The incoherent and coherent atomic dynamics study of tetrahedrite Cu 10.5 NiZn 0.5 Sb 4 S 13 provides the origin of softening upon cooling by investigate the motion of Cu12e at different temperatures. The dynamic structure factors in the longitudinal and transverse direction will also be discussed. The Cu movement of Cu-rich tetrahedrite Cu 14 Sb 4 S 13 is revealed by Cu self-diffusivity, nuclear density map and “nudged elastic band” (NEB). Moreover, we investigate the effect of simulation cell size and basis sets on the DFT-based MD simulation results using tetrahedrite Cu1 0 Zn 2 Sb 4 S 13 thermoelectric as a model material, showing the advantage of larger cell by accessing smaller Q range. In addition, the low-temperature structural properties of Cu 12 Sb 4 S 13 is measured by neutron diffraction, which indicates that no cubic to tetragonal transition occurs at metal-semiconductor transition (MST) temperature. Thermoelectric properties such as Seebeck coefficient, electrical resistivity and electrical thermal conductivity will also be investigated. DFTB method is implemented to study the structure and transport properties of Li 3 PO 4 and LiPON, while the exploration of N doping effect is included. Lastly, the LiPON/Li interphase will be revealed in order to study the origin of electrochemical stability.

Li, Junchao↗
DOE OSTI2020

STRUCTURE AND PROPERTIES STUDY ON ENERGY MATERIALS: THERMOELECTRIC MATERIAL TETRAHEDRITE AND LITHIUM ION CONDUCTOR LiPON

Development of efficient energy materials is critical in order to ease the energy demand and reduce our dependence of fossil fuel. Thermoelectric materials are promising due to their capability of generating electrical power by recovering waste heat. The performance of thermoelectric materials is quantified by a dimensionless figure of merit zT, which depends on their properties such as electrical conductivity, Seebeck coefficient and thermal conductivity. Tetrahedrites, a copper antimony sulfosalt mineral, typified by Cu12-xMxSb4S13, where M is a transition metal element such as Ni, Zn, Fe or Mn, have great potential for thermoelectric application due to their relatively high zT (close to 1 at 700 K), earth-abundance, environmental friendliness, favorable electrical properties, and most importantly intrinsic low lattice thermal conductivity (less than 1 W m-1 K-1) in wide temperature. In addition to energy recovery, reliable energy storage devices are also emerging to relieve the energy demand and improve the efficiency of consuming energy resources. Lithium-ion batteries are known to be reliable and successful electrochemical energy storage devices and appliable in various aspects, including laptops, smartphones and electrical vehicles. Lithium phosphorous oxynitride (LiPON) are widely used as thin-film solid-state electrolytes in Li-ion battery, which is the only demonstrated solid-state electrolyte that is quite stable in direct contact with Li metal at potentials from 0-5 V. However, the structure of LiPON, the effects of N doping, and the origin of its good electrochemical stability remains inconclusive.In this thesis, reliable modeling techniques accompanied with experimental tools, are applied to study the thermoelectric material tetrahedrite and the ionic conductor LiPON, in order to study their structural and dynamical properties. Accurate and efficient density-functional theory (DFT) and density-functional tight-binding (DFTB) methods, combined with molecular dynamics (MD) simulations are utilized in order to investigate the structures and properties of these energy materials. The incoherent and coherent atomic dynamics study of tetrahedrite Cu10.5NiZn0.5Sb4S13 provides the origin of softening upon cooling by investigate the motion of Cu12e at different temperatures. The dynamic structure factors in the longitudinal and transverse direction will also be discussed. The Cu movement of Cu-rich tetrahedrite Cu14Sb4S13 is revealed by Cu self-diffusivity, nuclear density map and "nudged elastic band" (NEB). Moreover, we investigate the effect of simulation cell size and basis sets on the DFT-based MD simulation results using tetrahedrite Cu10Zn2Sb4S13 thermoelectric as a model material, showing the advantage of larger cell by accessing smaller Q range. In addition, the low-temperature structural properties of Cu12Sb4S13 is measured by neutron diffraction, which indicates that no cubic to tetragonal transition occurs at metal-semiconductor transition (MST) temperature. Thermoelectric properties such as Seebeck coefficient, electrical resistivity and electrical thermal conductivity will also be investigated. DFTB method is implemented to study the structure and transport properties of Li3PO4 and LiPON, while the exploration of N doping effect is included. Lastly, the LiPON/Li interphase will be revealed in order to study the origin of electrochemical stability

25 ENERGY STORAGE↗
DOE OSTI2021

Accomplishments and Year-End Performance Report; Wind Energy Program: Fiscal Year 2021

The National Wind Technology Center (NWTC), located at the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL) Flatirons Campus, has been a driving force in advancing wind energy technology research worldwide since its designation as a DOE national research center in 1992. Enabled by the Flatirons Campus's world-class facilities, scientists, engineers, analysts, and researchers are pushing the frontiers of science to pursue wind energy innovation. In Fiscal Year (FY) 2021, NREL continued to provide the technical expertise, research capabilities, and industry understanding to support DOE's ambitious climate action and research goals by advancing technology, addressing market and deployment barriers, and driving down costs with more efficient, reliable, and predictable wind energy systems. One of several highlights, NREL received an R&D 100 Special Recognition Award for its Thermoplastic Resin System for Wind Turbine Blades. This breakthrough in the wind turbine manufacturing process will enable the production of recyclable blades that are stronger, longer, and less expensive, while increasing energy capture, decreasing energy and transportation costs, and increasing blade reliability. In a year when the entire U.S. economy struggled to address workforce gaps, an NREL study compared wind industry needs, training programs, and hiring practices with perspectives from students and recent college graduates. Researchers hope that, by pinpointing areas of disconnect, the expectations of employers who have difficulty filling entry-level jobs can better align with the preparation of the potential applicants who find it hard to break into the field. The lab also made numerous new data and modeling resources available in FY 2021. Recent NREL releases include a modeling tool for predicting the power performance and structural loads of wind turbines within a wind farm (FAST.Farm), a computational framework for modeling golden eagle behavior near wind farms, and 20 years of offshore wind data. Updates were also made to the widely used Wind Plant Integrated Systems Design and Engineering Model (WISDEM), which couples engineering and cost models to examine system-level trade-offs. Now, bolstered by a renewed national commitment to tackle climate change and revitalize the U.S. economy through increased investment in clean energy - particularly in offshore wind energy - NREL stands poised to lead the way to a sustainable future that powers the United States with significant levels of reliable, low-cost, accessible wind energy. This report provides an overview of the achievements NREL made on behalf of DOE's Wind Energy Technologies Office (WETO) and other partners during FY 2021 (between Oct. 1, 2020, and Sept. 30, 2021).

Flatirons Campus↗
DOE OSTI2022

Standard Analytical Methods for Pyrolysis Bio-Oils

There has been significant recent interest in the production of renewable fuels and chemicals from biomass and waste feedstocks. Pyrolysis pathways produce a liquid bio-oil product, which must be processed further, or upgraded, to yield fuel or chemical products. Bio-oils are very complex and often unstable samples, and research and development on upgrading processes needs reliable analytical information. In particular, chemical characterization techniques are needed to quantify both functional groups and individual compounds present in bio-oils. Reliable analytics are also needed to enable the bioenergy industry, as industrial facilities often have different analytical needs and capabilities than research facilities. In this presentation, we will discuss the development of a suite of standard analytical methods for pyrolysis bio-oils. Analytical methods to be discussed include: Determination of Carbon, Hydrogen, Nitrogen, and Oxygen in bio-oils; Accelerated Aging of Fast Pyrolysis Bio-oil using Carbonyl Titration; Determination of Water Content in Bio-oils by Volumetric Karl Fischer Titration; Determination of Carbon Functional Groups; Elemental Analysis of Bio-oils by Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES) - Na, K, Mg, Ca, S, P, and Fe; Determination of Phenolic Groups in Bio-oils using Revised Folin-Ciocalteu Methods: Single Cuvette and Plate Reader; Corrosivity of Bio-oils: Screening Test using Metal Leaching; Determination of Biogenic Content by 14C Measurement using Liquid Scintillation Counter. These new analytical methods are publicly available as Laboratory Analytical Procedures (https://www.nrel.gov/bioenergy/bio-oil-analysis.html), along with previously developed standard methods: GC-MS, Acid Titration, Carbonyl Titration, and 31P NMR. Additionally, the development of diffusion ordered NMR for characterization of bio-oil molecular weight will be discussed. Collectively, this suite of analytical methods represents the most comprehensive set of standard methods available for pyrolysis bio-oils. These standard methods are commonly used by the bioenergy community, and provide reliable information that enables research, scaleup, and industrial processing of biomass to produce renewable fuels and chemicals.

analytical↗
DOE OSTI2022

Use of Systems Engineering in Repurposing Coal-Fired Power Plants with Malta Pumped Thermal Energy Storage System

he electric sector across North America is facing a transition. Both economics and policy decisions have pointed towards a broad retirement of fossil assets across markets. Owners are facing the problem of how to evolve the base of the electric sector from fossil asset to greener alternative. Coal-fired power plants built the modern electricity grid. Their rotating machinery are the beating heart of the grid, providing essential resiliency and reliability services. Power plant retirements are disruptive to plant workforces and cause outsized impacts on surrounding communities. The transition from thermal power plants that use rotating machinery to generate electricity (e.g., coal- and gas-fired plants) to variable, inverter-based generation (e.g., solar and wind) is affecting the reliability of the electric grid. Grid operators and national regulators have issued warnings about known and anticipated risk. In 2021, Malta Inc. was awarded a Department of Energy (DOE) grant to study how to integrate a Malta 100MW Pumped Heat Energy Storage (PHES) system with a retiring coal-fired power plant to meet emissions requirements, retain plant workforces, preserve communities, and maintain grid reliability. This presentation provides a summary of this study, focusing on how systems engineering approach was used to arrive at a proposed design concept that met multiple objectives and requirements. There will be three main parts for this presentation. The first part of the presentation will focus on how different systems engineering was applied for this work. In particular, the following areas: stakeholder engagement, site selection process, developing requirements and use cases for the integrated system, defining the system and its boundary, coming up with different system architecture/option, performing a techno-economic analysis to compare the different options and down selection of the preferred option, will be discusses. For these areas, discussion on the decisions on how much breadth and depth to go into each area will be provided. These discussions provide good insights into how to apply systems engineering. The second part of the presentation will provide a deeper dive into the two recommended integration options that repurpose coal-fired power plants with Malta PHES system. The comparison of the two options and general guidance of how to choose an option will be provided. This is particularly useful for utilities who are facing coal-plant retirements. The two options will be compared based on its performance (such as power output, efficiency), complexity, and cost. The social impact on local communities of the two options will also be discussed. The final part of the presentation will discuss the impact that this work has had, including Malta Inc. being invited to the White House to discuss progress and outcomes of this work with the Interagency Working Group on Coal and Power Plant Communities and Economic Revitalization. In summary, this presentation aims to provide a showcase of how sy

25 ENERGY STORAGE↗
DOE OSTI2022

Transient Stability Study of a Real-World Microgrid with 100% Renewables

This paper performs a transient stability study of a real-world microgrid that can operate with 100% renewables to better understand the stability and reliability of the microgrid under various dynamic scenarios. In particular, the operation of multiple grid-forming (GFM) and grid-following (GFL) inverters in such a power system is not well understood under dynamic operation conditions, such as islanding and black start; therefore, in this paper, an electromagnetic transient model of the microgrid is developed to investigate the stability of the system under various dynamic operating conditions and to identify potential reliability risks. The PSCAD/EMTDC simulation with the high-fidelity model provides helpful insights into the optimal operation modes of GFM and GFL inverters as well as the stability and reliability of the microgrid. It can also inform field deployment in terms of inverter control parameters and coordination as well as the expected performance of black start and unplanned islanding.

black start↗
DOE OSTI2022

Transient Stability Study of a Real-World Microgrid with 100% Renewables: Preprint

This paper performs a transient stability study of a real-world microgrid with 100% renewables to fully understand the stability and reliability of the microgrid under various dynamic scenarios. In particular, the operation of multiple grid-forming (GFM) and grid-following (GFL) inverters in such a power system is not well understood under dynamic operation conditions, such as islanding and black start; therefore, in this paper, the full-scale electromagnetic transient modeling of the microgrid is developed to investigate the stability of the system under various dynamic operating conditions and to identify potential reliability risks. The PSCAD/EMTDC simulation with the high-fidelity model provides helpful insights into the optimal operation modes of GFM and GFL inverters as well as the stability and reliability of the microgrid, which gives good references for the field deployment in terms of inverter configuration and coordination as well as the capabilities of black start and unplanned islanding.

100% renewable microgrid↗