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DOE OSTI2020

Impact of Miller Cycle Strategies on Combustion Characteristics, Emissions and Efficiency in Heavy-Duty Diesel Engines

This study experimentally investigated the potential of Miller cycle strategies as a means to improve fuel consumption and reduce NO x emissions in heavy-duty diesel engines. The experiments were conducted at constant engine speed, load, and engine-out NO x (1160 rev/min, 1.76 MPa net IMEP, 4.5 g/kWh) on a single cylinder research engine equipped with a fully-flexible hydraulic valve train system. Early Intake Valve Closing (EIVC) and Late Intake Valve Closing (LIVC) timing strategies were compared to a conventional intake valve profile. While the decrease in effective compression ratio associated with the use of Miller valve profiles was symmetric around bottom dead center, the decrease in volumetric efficiency (VE) was not. EIVC profiles were more effective at reducing VE than LIVC profiles. Despite this difference, EIVC and LIVC profiles with comparable VE decrease resulted in similar changes in combustion and emissions characteristics. Miller cycle operation at constant intake pressure resulted in lower peak cylinder pressure, higher exhaust temperatures and lower EGR requirements compared to the baseline case, albeit with a significant fuel consumption penalty. Increasing intake manifold pressure to match the baseline air-fuel ratio overcame the fuel consumption penalty, without compromising NO x emissions. Selected EIVC/LIVC profiles were compared to the baseline condition at three different overall turbocharger efficiencies (n TC ). At the baseline n TC , Miller cycle profiles can lower peak cylinder pressures and increase exhaust temperatures with a minimal penalty in BSFC and FSN. At higher n TC than baseline, Miller cycle can maintain the benefits of lower peak cylinder pressure and higher exhaust temperature without a BSFC or FSN penalty.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

METHODOLOGY AND APPLICATION OF PHYSICAL SECURITY EFFECTIVENESS BASED ON DYNAMIC FORCE-ON-FORCE MODELING

This paper describes ongoing work within the Light Water Reactor Sustainability (LWRS) Program at Idaho National Laboratory (INL) to optimize security and cost of nuclear power plants (NPPs). It reviews the conservatisms in conventional physical security posture and regulations. It introduces the dynamic risk assessment tool developed at INL, Event Modeling Risk Assessment using Linked Diagrams (EMRALD). The dynamic assessment methodology leverages EMRALD to process results of force-on-force (FOF) simulations and crediting safety mitigation actions from probabilistic risk assessment (PRA) models as well as diverse and flexible coping strategies (FLEX) mitigation strategies. Timing information from these simulations are compared against the available time to perform mitigations obtained from Reactor Excursion and Leak Analysis Program (RELAP5) simulations. To illustrate the methodology, a station blackout (SBO) attack scenario was modeled in commercially available FOF simulation tools. The simulation results provide valuable insights into possible attack outcomes and as the probabilistic risk of a core damage event given these outcomes. Safety mitigation procedures were modeled in EMRALD, and were dependent on the attack outcomes by considering human operator uncertainties. RELAP5 simulations incorporating human and hardware uncertainties were performed to estimate the distribution of time-to-core damage. The results demonstrate that, even in the extreme case of a successful adversarial attack, plant mitigation strategies provide significantly high-likelihood of preventing radiological release. The proposed modeling and simulation framework of integrating FLEX equipment with FOF models enables the NPPs to credit FLEX portable equipment in the plant security posture, resulting in an efficient and optimized physical security.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

A new efficient grain growth model using a random Gaussian-sampled mode filter

This paper presents the use of a Gaussian neighborhood mode filter for predicting grain growth in a manner similar to the solutions obtained by a Monte Carlo Potts model. This flexible grain growth model can quickly utilize modern, computationally optimized data science strategies on graphics processing units to simulate grain growth up to 100 times faster than the state-of-the-art, publicly available Monte Carlo Potts model. We show that, given the correct neighborhood, the mode filter can replicate normal grain growth in two or three dimensions. In addition, the paper briefly demonstrates the ability to model limited anisotropic in grain boundary energy and mobility. Anisotropic grain boundary energy is modeled by defining a weighted mode filter operation. Anisotropic grain boundary mobility is modeled by scaling and orienting the Gaussian neighborhood in a particular direction.

Anisotropy↗

DOE OSTI2020

Structure of the Electrical Double Layer at the Interface between an Ionic Liquid and Tungsten Oxide in Ion-Gated Transistors

The structure of electrical double layers at electrified interfaces is of utmost importance for electrochemical energy storage as well as printable, flexible, and bioelectronic devices, such as ion-gated transistors (IGTs). Here we report a study based on atomic force microscopy force–distance profiling on electrical double layers forming at the interface between the ionic liquid 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide and sol–gel films of mesoporous tungsten oxide. Here, we successfully followed, under in operando conditions, the evolution of the arrangement of the ions at the interface with the tungsten oxide films used as channel materials in IGTs. Our work sheds light on the mechanism of operation of IGTs, thus offering the possibility of optimizing their performance.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Least-Cost Pathways for India's Electric Power Sector

The Government of India has a target of deploying 175 GW from renewable energy by 2022 and 40% of electricity capacity from renewable energy by 2030 and has indicated that ambitions for 2030 could be higher. Rapid changes in technology costs and performance could drive further deployment of wind and solar capacity beyond these policy targets. Increased deployment of variable renewable energy (VRE) raises new questions for power system planning regarding the optimal siting of generation capacity, trade-offs between generation and transmission infrastructure, and system flexibility needs. This study aims to evaluate least-cost pathways for India's electric power system over the period 2017-2047. Uniquely, this work considers an expanded planning horizon and range of scenarios not previously analyzed in national planning studies in India. The data collection and model design processes undertaken for this study provides a framework for recurring planning studies. This study finds anticipated changes in electricity demand and component costs can drive a significant shift in India's future electricity supply and how this system will be operated. In the Base scenario, the share of generation from VRE reaches 54% by 2047. Reducing the capital cost of wind has a larger impact on VRE penetration than reducing the capital cost of solar PV or battery storage. In the lowest wind cost scenario (40% capital cost decline by 2047 relative to the Base scenario), the penetration of VRE in the generation mix reaches 722%, exceeding the penetration levels achieved when the cost of battery storage or solar PV are reduced by an even greater 50%. In a future system with high penetrations of RE, capacity additions are driven by the coincidence of demand and RE generation rather than peak demand alone. This study finds the system could have surplus capacity during the peak demand months of July–September because this period corresponds to periods with high wind speeds and more wind generation available to meet peak demand. By contrast, new capacity is needed to meet demand during moderate demand months of October–November when output from wind plants falls more than 75% nationally compared to the previous two months. Finally, the success for gas for electricity production may depend on cost competitiveness rather than fuel availability. Increasing the amount of gas available for electricity production had no significant impact on the capacity or generation mix by 2047, as determined from a scenario that significantly increases fuel availability throughout the planning horizon. In fact, over 80% of new gas fuel available for the power sector remains unused. This suggests the high cost of gas plant operations relative to other technologies may constrain the expansion of gas generation in India more than fuel availability.

14 SOLAR ENERGY↗

DOE OSTI2020

Emergent Degradation Phenomena Demonstrated on Resilient, Flexible, and Scalable Integrated Photoelectrochemical Cells

Photoelectrochemical (PEC) water splitting provides a pathway to generate sustainable clean fuels using the two most abundant resources on Earth: sunlight and water. Currently, most of the successful models of PEC cells are still fabricated on small scales near 1 cm 2 , which largely limits the mass deployment of solar-fuel production. Here, the scale-up to 8 cm 2 of an integrated PEC (IPEC) device is demonstrated and its performance compared to a 1 cm 2 IPEC cell, using state-of-the-art iridium and platinum catalysts with III–V photoabsorbers. The initial photocurrents at 1 sun are 8 and 7 mA cm -2 with degradation rates of 0.60 and 0.47 mA cm -2 day -1 , during unbiased operation for the 1 and 8 cm 2 devices, respectively. Additionally, evaluating under outdoor and indoor conditions at two U.S. National Laboratories reveals similar results, evidencing the reproducibility of this design's performance. Furthermore, the emerging degradation mechanisms during scale-up are investigated and the knowledge gained from this work will provide feedback to the broader community, since PEC device durability is a limiting factor in its potential future deployment.

25 ENERGY STORAGE↗

DOE OSTI2023

Cost Estimates of Roll-to-Roll Production of Organic Light Emitting Devices for Lighting

White organic light emitting devices (WOLEDs) offerdistinct advantages as solid state lighting sources, including high energy efficiency, superior color quality,and a flexible, thin profile that can accommodate a vast array of possible fixture designs. Recent advances in device lifetime and high speed deposition suggest that mass production of WOLED panels is approaching an inflection point. To understand the tradeoffs in the volume manufacturing of WOLED lighting panels, in this work, we estimate the cost of white WOLED panel production based on vacuum and vapor phase deposition in a roll-to-roll production line envisioned to yield an annual capacity of at least 6 × 10 6 m 2 . Assuming a WOLED operating luminance at 10 klm/m 2 , we anticipate a $\$12.5$ /klm cost of a WOLED light engine that includes the cost of the current driverand packaging. With incremental reduction in material and driver costs and improved luminance, the costof WOLED lighting can be reduced to $\$6.3$ /klm in thenear term, potentially positioning WOLEDs for use innumerous premium lighting applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Development of a Power Electronics-based Testbed for a Flexible Combined Heat and Power System

A flexible combined heat and power (F-CHP) concept, enabled by a power electronics-based power conditioning system (PCS), has been recently proposed as a cost-effective way for supporting the grid with high penetration of renewable energy sources. To verify the design, control, and performance of the overall system, a laboratory-scale testbed is essential. This paper focuses on the development of a power electronics-based testbed for such a F-CHP system. The developed testbed can test the control, grid-connected mode operation, islanded mode operation, and mode transitions, including planned/unplanned islanding and reconnection, of the F-CHP system. In the grid-connected mode, both the steady state and transients of the ac grid can be emulated, and various grid support functions can be tested with the help of the developed PCS converter. In the islanded mode, the external ac loads can also be supported by the F-CHP system. Also, the central controller, which is implemented in a NI CompactRIO, can be tested. Experimental test results for the grid-connected mode, islanded mode, and mode transitions are provided to validate the testbed design.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

RuralAI in Tomato Farming: Integrated Sensor System, Distributed Computing, and Hierarchical Federated Learning for Crop Health Monitoring

Precision horticulture is evolving due to scalable sensor deployment and machine learning (ML) integration. These advancements boost the operational efficiency of individual farms, balancing the benefits of analytics with autonomy requirements. However, given concerns that affect wide geographic regions (e.g., climate change), there is a need to apply models that span farms. Federated learning (FL) has emerged as a potential solution. FL enables decentralized ML across different farms without sharing private data. Traditional FL assumes simple two-tier network topologies and, thus, falls short of operating on more complex networks found in real-world agricultural scenarios. Networks vary across crops and farms and encompass various sensor data modes, extending across jurisdictions. New hierarchical FL (HFL) approaches are needed for more efficient and context-sensitive model sharing, accommodating regulations across multiple jurisdictions. Here, we present the RuralAI architecture deployment for tomato crop monitoring, featuring sensor field units for soil, crop, and weather data collection. HFL with personalization is used to offer localized and adaptive insights. Model management, aggregation, and transfers are facilitated via a flexible approach, enabling seamless communication between local devices, edge nodes, and the cloud.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Virtual Power Plant Profiles and Inventory

Increased adoption of distributed energy resources (DERs), growing quantities of renewable energy on the grid, and load growth from buildings, industry, and data centers are driving the need for increased demand flexibility and solutions to reliably and cost-effectively balance electricity supply and demand. In order to deploy DERs on a similar scale as conventional supply-side resources, utilities and state decision-makers are exploring a range of programmatic approaches and market designs, including Virtual Power Plants (VPP). Based on interviews with more than twenty subject matter experts on VPPs, the Insights into Scaling Virtual Power Plants report and appendix outlines actions that utilities and regulators can take to expand VPPs, organized around successful VPP designs, deployment, and operation. The companion report, Virtual Power Plant Profiles and Inventory describes three conceptual profiles that can be used as a starting point to facilitate clear discussions among regulators, utilities, solution providers, and stakeholders about various VPP strategies. It also includes details on more than 790 demand response programs and net energy metering solar plus battery programs, and 180 VPP programs. The Inventory is provided below as a separate file.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Deployable sensor system using mesh networking and satellite communication

A sensor system may be configured for continuous operation in a low resource environment and/or in extreme environmental conditions. The sensor system may have sufficient processing capabilities to provide scientific computing for pre-processing, quality control, statistical analysis, event classification, data compression and corrections (e.g., spikes in the data), autonomous decisions and actions, triggering other nodes, and information assurance functions that provide data confidentiality, data integrity, authentication, and non-repudiation. The hardware may have both mesh networking and satellite and cellular communication capability, and may be available for relatively low cost. Such a network provides the flexibility to have potentially any number of nodes be completely independent from one another. Thus, the network may scale across a diverse terrain.

Frigo, Janette↗

DOE OSTI2024

DRiFT current mode, trigger settings and flexible detector specifications applied to scintillator arrays

MCNP radiation transport output is post-processed by DRiFT, a Detector Response Function Toolkit to simulate detailed nuclear instrumentation response. DRiFT can be used to assess the performance and potential limitations of scintillator, gas, and semiconductor detectors under a variety of simulated conditions not easily achievable in a laboratory setting. This work describes new updates in DRiFT for scintillator simulations which focus on the capability to simulate scintillators in current mode, an expansion of trigger options, and the ability to customize individual detector properties in a simulation. These improvements are designed to facilitate the ability to model large arrays of scintillator detectors with higher fidelity than was previously possible and are demonstrated in three examples. The first shows the difference between operating DRiFT in current and pulse mode. In the second example, which is intended to demonstrate deviations in individual detector performance, each detector has properties (PMT gain, optical transport, scintillation yield, etc.) that vary between detectors and are specified in DRiFT. A final example examines how DRiFT could be used to optimize digitizer settings in high rate measurements with split signals using the new common trigger option.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2020

Developing Flexible, Networked Lighting Control Systems That Reliably Save Energy in California Buildings

An important strategy to meet California's ambitious energy efficiency goals is to use innovative wireless communications, embedded sensors, data analytics and controls to significantly reduce lighting energy use in commercial buildings. This project developed a suite of networked lighting solutions to further this goal. The technologies include a platform for low-cost sensing, distributed intelligence and communications, the “PermaMote,” which is a self-powered sensor and controller for lighting applications. The project team also developed a task ambient daylighting system that integrates sensors with data-driven daylighting control using an open communication interface, called the “Readings-At-Desk” (RAD) system. To address the problem of building occupants being confused about how to operate traditional lighting control systems, the research team created content that could be the basis for a user interface standard for lighting controls. Finally, to address the difficulty of ensuring that advanced lighting control systems actually deliver their promised energy savings, the project team developed a new method for evaluating and specifying lighting systems’ performance. The research team validated these technologies in the laboratory, showing significant lighting energy savings, up to 73% for the PermaMote sensor system from occupancy control and daylight dimming features, compared to the same light source (LED replacement lamps) operated via simple on/off scheduling. The project team also developed a proposed standard lighting data model and user interface elements, which were contributed to the ANSI Lighting Systems Committee (C137) for standardization. Existing data models are incomplete and inconsistent, whereas the lighting-specific data model developed here is clear and comprehensive, to serve as a starting point for creating common, universally agreed upon semantic definitions of key lighting parameters, to promote interoperability. For the task on verifiable performance of lighting systems, the project team developed a more effective metric for capturing the actual energy impact of a lighting system over time — the energy usage intensity (kWh/ft2/year). Three commercial lighting systems were tested in FLEXLAB® using this new metric, and the tests show a wide range in the accuracy of the self-reported energy-use metric, from 0.5% to 28% error compared to direct measurement of lighting energy using dedicated submeters. Overall, the project team estimates that these advanced technologies can reduce California office lighting energy use by 20% (above and beyond normal advanced lighting controls mandated by Title 24), resulting in about 1,600 GWh/year in savings.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

DRiFT Current Mode, Trigger Settings and Flexible Detector Specifications Applied to Scintillator Arrays

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Impacts of climate change on subannual hydropower generation: a multi-model assessment of the United States federal hydropower plant

Abstract Hydropower is a low-carbon emission renewable energy source that provides competitive and flexible electricity generation and is essential to the evolving power grid in the context of decarbonization. Assessing hydropower availability in a changing climate is technically challenging because there is a lack of consensus in the modeling representation of key dynamics across scales and processes. Focusing on 132 US federal hydropower plants, in this study we evaluate the compounded impact of climate and reservoir-hydropower models’ structural uncertainties on monthly hydropower projections. In particular, instead of relying on one single regression-based hydropower model, we introduce another conceptual reservoir operations-hydropower model in the assessment framework. This multi-model assessment approach allows us to partition uncertainties associated with both climate and hydropower models for better clarity. Results suggest that while at least 70% of the uncertainties at the annual scale and 50% at the seasonal scale can be attributed to the choice of climate models, up to 50% of seasonal variability can be attributed to the choice of hydropower models, particularly in regions over the western US where the reservoir storage is substantial. The analysis identifies regions where multi-model assessments are needed and presents a novel approach to partition uncertainties in hydropower projections. Another outcome includes an updated evaluation of Coupled Model Intercomparison Project Phase 5 (CMIP5)-based federal hydropower projection, at the monthly scale and with a larger ensemble, which can provide a baseline for understanding future assessments based on CMIP6 and beyond.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Model predictive control for robust quantum state preparation

A critical engineering challenge in quantum technology is the accurate control of quantum dynamics. Model-based methods for optimal control have been shown to be highly effective when theory and experiment closely match. Consequently, realizing high-fidelity quantum processes with model-based control requires careful device characterization. In quantum processors based on cold atoms, the Hamiltonian can be well-characterized. For superconducting qubits operating at milli-Kelvin temperatures, the Hamiltonian is not as well-characterized. Unaccounted for physics (i.e., mode discrepancy), coherent disturbances, and increased noise compromise traditional model-based control. This work introduces model predictive control (MPC) for quantum control applications. MPC is a closed-loop optimization framework that (i) inherits a natural degree of disturbance rejection by incorporating measurement feedback, (ii) utilizes finite-horizon model-based optimizations to control complex multi-input, multi-output dynamical systems under state and input constraints, and (iii) is flexible enough to develop synergistically alongside other modern control strategies. We show how MPC can be used to generate practical optimized control sequences in representative examples of quantum state preparation. Specifically, we demonstrate for a qubit, a weakly-anharmonic qubit, and a system undergoing crosstalk, that MPC can realize successful model-based control even when the model is inadequate. These examples showcase why MPC is an important addition to the quantum engineering control suite.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2022

Model-Free Building Temperature Control and Power Allocation Under Measurement Time Delays

Taking a step towards a greener planet has created an increased need for a higher integration of renewable energy resources into the electric grid. Nonetheless, the intermittency and uncertainty associated with renewable generation have slowed down this integration. Demand response (DR) has been recently adopted to address this challenge by utilizing demand side flexibility and enabling the participation of many grid-interactive efficient buildings (GEBs). However, existing DR methods require significant modeling and/or training efforts and are computationally expensive. To address the aforementioned issues, we propose a model-free control (MFC)-based strategy that is robust to the time delays in the temperature measurements of the thermostatically controlled loads (TCLs). It assigns to each GEB a local controller to maintain the TCLs’ temperatures within desired comfort levels, while the load aggregator (LA) allocates the assigned reference power provided by the distribution system operator (DSO) to support a specific grid service, such as demand peak reduction, load shifting, balancing supply and demand, and consuming the solar photovoltaic power locally. We investigate the effects of such loss of information on the local control action as well as on meeting the power allocation constraint. We conclude that, for an appropriate choice of design parameters, the proposed MFC controller is satisfactorily robust to measurement time delays.

Telsang, Bhagyashri↗

DOE OSTI2023

Packetized Energy Management: Coordinating Transmission and Distribution (Final Report)

The project Packetized Energy Management (PEM): Coordinating Transmission and Distribution was part of the ARPA-E NODES program from 2015 to 2023. The high-level goal of the project was to develop and demonstrate novel, scalable, and impactful technologies related to the coordination of networked distributed energy resources (DERs). By demonstrating responsive means by which fleets of DERs could be coordinated to enhance grid operation and reliability, the U.S. could accelerate renewable integration and electrification efforts and meet decarbonization goals.

25 ENERGY STORAGE↗