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At least 433 records · Page 24

Peak Reduction in a Residential Community Through Bayesian Optimization of Transactive Control Signals

Daily residential power consumption in aggregate tends to have a large peak that places stress on the distribution system and induces high operational costs. This work shows that coordinated transactive control of noncritical loads within a residential community or microgrid can help to alleviate peak-time stress on the distribution system by flattening the aggregate load curve. Treating the load forecaster as a high-fidelity, expensive black-box function, a new algorithm utilizing Bayesian optimization (BO) is proposed to achieve the best solution under uncertainty with minimal computing effort. The proposed BO algorithm manipulates the shape of the load based on transactive signals sent to each home. The thermostatically controlled loads (TCLs) act out of self-interest in response to the given price while maintaining comfort, and the optimizer exploits the thermal energy retention of the homes for the benefit of the community. Simulations confirm consistent neighborhood-level peak power reduction and energy cost savings.

Schomer, Ian↗

Multiple microbial guilds mediate soil methane cycling along a wetland salinity gradient

ABSTRACT Estuarine wetlands harbor considerable carbon stocks, but rising sea levels could affect their ability to sequester soil carbon as well as their potential to emit methane (CH 4 ). While sulfate loading from seawater intrusion may reduce CH 4 production due to the higher energy yield of microbial sulfate reduction, existing studies suggest other factors are likely at play. Our study of 11 wetland complexes spanning a natural salinity and productivity gradient across the San Francisco Bay and Delta found that while CH 4 fluxes generally declined with salinity, they were highest in oligohaline wetlands (ca. 3-ppt salinity). Methanogens and methanogenesis genes were weakly correlated with CH 4 fluxes but alone did not explain the highest rates observed. Taxonomic and functional gene data suggested that other microbial guilds that influence carbon and nitrogen cycling need to be accounted for to better predict CH 4 fluxes at landscape scales. Higher methane production occurring near the freshwater boundary with slight salinization (and sulfate incursion) might result from increased sulfate-reducing fermenter and syntrophic populations, which can produce substrates used by methanogens. Moreover, higher salinities can solubilize ionically bound ammonium abundant in the lower salinity wetland soils examined here, which could inhibit methanotrophs and potentially contribute to greater CH 4 fluxes observed in oligohaline sediments. IMPORTANCE Low-level salinity intrusion could increase CH4 flux in tidal freshwater wetlands, while higher levels of salinization might instead decrease CH4 fluxes. High CH4 emissions in oligohaline sites are concerning because seawater intrusion will cause tidal freshwater wetlands to become oligohaline. Methanogenesis genes alone did not account for landscape patterns of CH4 fluxes, suggesting mechanisms altering methanogenesis, methanotrophy, nitrogen cycling, and ammonium release, and increasing decomposition and syntrophic bacterial populations could contribute to increases in net CH4 flux at oligohaline salinities. Improved understanding of these influences on net CH4 emissions could improve restoration efforts and accounting of carbon sequestration in estuarine wetlands. More pristine reference sites may have older and more abundant organic matter with higher carbon:nitrogen compared to wetlands impacted by agricultural activity and may present different interactions between salinity and CH4. This distinction might be critical for modeling efforts to scale up biogeochemical process interactions in estuarine wetlands.

59 BASIC BIOLOGICAL SCIENCES↗

Damage Modeling of Solid Oxide Fuel Cells Accounting for Redox Effects

This work applies a multiscale mechanistic damage model developed for brittle ceramics and implemented in commercial finite element (FE) packages via user subroutines to study progressive damage in solid oxide fuel cells (SOFC) subjected to thermomechanical loading under normal operating and shutdown conditions including redox effects. The damage model captures the micromechanics of stiffness reduction due to material porosity change and microcracking and integrates the as-obtained stiffness reduction law into a continuum damage mechanics (CDM) formulation for the evolution of microcracks up to fracture. The volumetric “swelling” that occurs during redox is treated in constitutive modeling similarly to thermal expansion, but swelling strains are irreversible. Furthermore, this damage model was first validated through predictions of strength and stress-strain response for the SOFC electrode materials. Next, it has been applied to predict the potential for degradation in a generic planar SOFC stack with large active area cells. Multicell stack models were simulated in both co-flow and counter-flow configurations. In addition, a constant temperature redox cycle was also simulated to capture overall cell electrode damage due to volumetric swelling of the nickel (Ni)-based anode in the anode-supported cells.

25 ENERGY STORAGE↗

Filament Extension Atomization for High Solids Loading in Energy Efficient Spray Drying Systems

We demonstrate that we could scale FEA to reach outputs needed by industrial production, while increasing solids loading of the sprayed product by at least 30% and maintaining equal or better spray powder. After testing a wide range of products, in collaboration with industry partners we decided on our primary spray products of dry whey and WPC-80, two common materials processed and sold by US manufacturers with different parameters. We sprayed these with FEA at solids loadings of 70% for dry whey and 45% for WPC-80 with a spray output with particle sizes similar to industrial particles sizes and reduced variation in particle size. We simultaneously scaled up FEA first with a multi-nip with 6 nips surrounding a central roller with parallel axis of rotation and eventually with a tapered design that solved problems we encountered with our initial design. We were able to achieve output from a single array from our first design of up to 4.7 liters per minute (L/min) and from an array of our second multi-nip of 8 L/min exceeding expectations. This demonstrates that FEA technology can indeed be scaled up to meet the needs of industrial production. More arrays can be added as necessary to meet a wide range of spray dryer designs. We also tested FEA to create dried powders from a small scale (10 L/hour of water removal) spray dryer. Though we were not able to produce large quantities of powder from FEA due to challenges in integration, the powder we produced was higher quality and produced from higher solids loading materials. From our technoeconomic analysis we for a typically sized spray dryer, we estimate a 27% cost reduction and 41% energy and carbon reduction for WPC-80 and a 39-57% cost reduction and 52-76% energy reduction for sweet dry whey (depending on the exact product).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Predicting peak day and peak hour of electricity demand with ensemble machine learning

Battery energy storage systems can be used for peak demand reduction in power systems, leading to significant economic benefits. Two practical challenges are 1) accurately determining the peak load days and hours and 2) quantifying and reducing uncertainties associated with the forecast in probabilistic risk measures for dispatch decision-making. In this study, we develop a supervised machine learning approach to generate 1) the probability of the next operation day containing the peak hour of the month and 2) the probability of an hour to be the peak hour of the day. Guidance is provided on preparation and augmentation of data as well as selection of machine learning models and decision-making thresholds. The proposed approach is applied to the Duke Energy Progress system and successfully captures 69 peak days out of 72 testing months with a 3% exceedance probability threshold. On 90% of the peak days, the actual peak hour is among the 2 h with the highest probabilities.

25 ENERGY STORAGE↗

Probabilistic Modeling of Climate Change Impacts on Renewable Energy and Storage Requirements for NM's Energy Transition Act (SAND Report)

This report provides a study of the potential impacts of climate change on intermittent renewable energy resources, battery storage, and resource adequacy in Public Service Company of New Mexico’s Integrated Resource Plan for 2020 – 2040. Climate change models and available data were first evaluated to determine uncertainty and potential changes in solar irradiance, temperature, and wind speed in NM in the coming decades. These changes were then implemented in solar and wind energy models to determine impacts on renewable energy resources in NM. Results for the extreme climate-change scenario show that the projected wind power may decrease by ~13% due to projected decreases in wind speed. Projected solar power may decrease by ~4% due to decreases in irradiance and increases in temperature in NM. Uncertainty in these climate-induced changes in wind and solar resources was accommodated in probabilistic models assuming uniform distributions in the annual reductions in solar and wind resources. Uncertainty in battery storage performance was also evaluated based on increased temperature, capacity fade, and degradation in round-trip efficiency. The hourly energy balance was determined throughout the year given uncertainties in the renewable energy resources and energy storage. The loss of load expectation (LOLE) was evaluated for the 2040 No New Combustion portfolio and found to increase from 0 days/year to a median value of ~2 days/year due to potential reductions in renewable energy resources and battery storage performance and capacity. A rank-regression analyses revealed that battery round-trip efficiency was the most significant parameter that impacted LOLE, followed by solar resource, wind resource, and battery fade. An increase in battery storage capacity to ~25,000 – 30,000 MWh from a baseline value of ~14,000 MWh was required to reduce the median value of LOLE to ~0.2 days/year with consideration of potential climate impacts and battery degradation.

54 ENVIRONMENTAL SCIENCES↗

Smart Ventilation Controls for Occupancy and Auxiliary Fan Use Across U.S. Climates

Smart Ventilation has been developed as a way to reduce the energy associated with ventilation by changing when ventilation happens and how much ventilation occurs at any given time. In high performance buildings with low envelope and appliance related loads, ventilation is becoming a bigger part of the total building energy use and needs to be addressed if performance targets are to be met. This work explores the development and performance of smart ventilation controls based on occupancy and auxiliary fan operation that provide annual dwelling unit ventilation equivalence to ASHRAE Standard 62.2-2016. A prototype high performance home compliant with U.S. DOE Building America Zero Energy Ready program requirements was simulated using the REGCAP tool with and without smart controls across 15 U.S. DOE climate zones. Balanced and unbalanced IAQ fans were independently simulated, and all smart controlled fans had airflows double the reference 62.2-2016 airflow. Three idealized occupancy patterns were examined: 1st shift (a typical daily work/school absence), an extended 1st shift with more time spent out of the home evenings and weekends and 3rd shift (night work). The Occupancy controller turns the IAQ fan off during unoccupied periods, and it resumes ventilation upon their return. While unoccupied, contaminants are allowed to accumulate in the space, because occupants are not exposed to these contaminants. When occupants return home, they are exposed to these higher contaminant concentrations, and the controller increases the ventilation rate sufficiently to ensure equivalence with a continuous IAQ fan. Accounting for pollutant emissions that occur during unoccupied periods (as required by ASHRAE 62.2-2016), sharply distinguishes our occupancy controls from past Demand Controlled Ventilation systems. This new accounting method results in equivalent contaminant exposure, as well as lower reductions in average ventilation rates and lower energy savings. Smart controls were demonstrated that saved HVAC energy (i.e., avoided heating/cooling load, as well as fan energy)—averaging between 6 and 46% of ventilation-related energy use depending on the control strategy and occupancy pattern assumptions. The greatest savings were in the combined Auxiliary Fan + Occupancy control. Energy savings increased with climate heating demand and longer unoccupied time periods. The 3rd shift occupancy pattern had better performance, due to the thermal benefit of reducing the ventilation rate during the cold nighttime hours. This same effect provided a cooling energy benefit in hotter locations for the 1st shift. Overall, savings from occupancy-based smart controls were low, because of the recovery period required after occupants return home, during which the airflow is double the 62.2 reference. This recovery is required to maintain equivalence with the ASHRAE standard. Occupancy-based control performance was improved when combined with sensing auxiliary fans and when providing a pre-occupancy flush out of one- or two-hours. Performance was similarly improved if the ASHRAE Standard were to recognize that pollutant emissions are lower during unoccupied periods, iii allowing a lower target ventilation rate during unoccupied periods (not currently in the standard) (see Full vs. Half AEQ in this report). Finally, over-sized unbalanced fans that are cycled on-and-off by a smart controller (or timer) were found to substantially increase annual average air exchange and energy use relative to a continuous unbalanced fan due to the effects of superposition with natural infiltration.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Performance, Combustion and Emissions Evaluation of Liquid Phase Port-Injected LPG on a Single Cylinder Heavy-Duty Spark Ignited Engine

Liquefied petroleum gas (LPG), like many other alternative fuels, has witnessed increased adoption in the last decade, and its use is projected to rise as stricter emissions regulations continue to be applied. However, much of its use is limited to dual fuel applications, gaseous phase injection, light-duty passenger vehicle applications, or scenarios that require conversion from gasoline engines. Therefore, to address these limitations and discover the most efficient means of harnessing its full potential, more research is required in the development of optimized fuel injection equipment for liquid port and direct injection, along with the implementation of advanced combustion strategies that will improve its thermal efficiency to the levels of conventional fuels. This paper focuses on the development of a liquid phase port-injection system for LPG, the design of a reference piston, and the baseline evaluation of the performance, combustion, and emissions characteristics of a single cylinder research engine to establish a benchmark comparable to existing LPG engines. A sweep of start of injection (SOI) timing is performed by injecting liquid LPG at several closed and open intake valve timings, which demonstrates no significant variation in engine performance, but accounts for a 10% reduction in bsCO with the optimal SOI timing. Spark timing sweep demonstrates the 50% burn crank angle location related to maximum brake torque (MBT) point with a brake thermal efficiency (BTE) of ~34% for the tested load case. The effect of equivalence ratio is also presented with optimal SOI timing at MBT condition. The engine starts exhibiting knocking combustion at 140kPa intake manifold air pressure (IMAP) with a peak torque of 253Nm and a 5% reduction in brake specific fuel consumption compared to the naturally aspirated scenario.

Fosudo, Toluwalase↗

Red-Light-Driven Biophotochemical Diode Based on a Microorganism–Silicon Nanowire Interface for Stable and Efficient Bias-Free CO 2 Reduction

Artificial photosynthesis offers a promising route for sustainable liquid fuel and feedstock production, yet integrating efficient CO 2 reduction catalysts with light-harvesting systems remains challenging. Here, in this study, we present a biophotochemical diode that couples microorganism-driven CO 2 reduction with glycerol oxidation, enabled by silicon nanowire photoelectrodes under varying red-light intensities. Tuning the biotic-abiotic interface─by increasing biocatalyst loading and adjusting the catholyte pH to mitigate local alkalization─significantly improves performance and stability. The enhanced-loading biocathode maintains a high faradaic efficiency across a wide potential range, even under elevated light intensities. At 60 mW/cm 2 , the system achieves a bias-free current density of 3.5 mA/cm 2 . Long-term stability testing at 40 mW/cm 2 demonstrates stable operation for over 100 h. The photoanode generates valuable C 3 products, primarily glycerate and lactate, enhancing the economic viability. This work showcases the importance of microenvironmental control at the biotic-abiotic interface and establishes a scalable platform for light-driven CO 2 reduction using earth-abundant silicon.

Artificial Photosynthesis↗

Multi-injection investigation of a high-volatility diesel in advanced compression ignition combustion for NO x control

Traditional selective catalytic reduction aftertreatment technologies used to reduce [Formula: see text] are very limited at exhaust temperatures below [Formula: see text]. Therefore, under these low engine load conditions, having effective in-cylinder control of [Formula: see text] emissions is important. Previous work by the authors explored the effect of fuel physical properties on the ability to control [Formula: see text] in-cylinder. That work was limited to one direct injection near top dead center. Modern diesel high-pressure fuel systems have the capability of five or more injections in one engine cycle. A higher-volatility diesel fuel and high amounts of exhaust gas recirculation to delay ignition could provide an opportunity for reduction in engine-out [Formula: see text] through an increased level of fuel premixing. By appropriately timing multiple short injections, a more optimal distribution of fuel in-cylinder may be achieved, which could reduce [Formula: see text] while maintaining an efficient combustion phasing. A computational fluid dynamics model previously validated against experimental data was used to explore several injection strategies with increased levels of fuel premixing to assess the potential trade-offs between [Formula: see text] and CO/unburned hydrocarbon (UHC) emissions and thus reduce reliance on the aftertreatment system for [Formula: see text] control. The results show that the devised injection strategies resulted in an increased level of fuel premixing. However, none of the attempted injection strategies resulted in significant [Formula: see text] reductions, and all strategies showed a significant increase in CO and UHC emissions.

33 ADVANCED PROPULSION SYSTEMS↗

Excessive charge, beam loading, and impedance collapse thresholds for a velvet emitter

Excess emission has been observed from velvet cathodes with total emission times >150 ns. In this diode experiment, we produce a sub-relativistic electron beam with the ability to consistently change γ from 1.2 to 1.5 and β = 0.5–0.75. Electron emission in this particular diode geometry requires electric fields >40 kV/cm. The current increases at steady rates >0.05 A/ns after the head of the pulse, indicating an expansion of the emission surface and reduction in the effective AK gap. Small transients of excess emission (or arcs) are consistently observed for current pulses exceeding 150 ns. The excess emission results in beam loaded levels ≥10 kV on the diode voltage. The effects described here are compounded as diode voltage is increased. The principal objective of these experiments is to quantify electric field emission thresholds, current ramps, excess emission delays, effective beam loading, and impedance collapse.

43 PARTICLE ACCELERATORS↗

Performance Improvements on SNS and HFIR Instrument Data Reduction Workflows Using Mantid

Performance of data reduction workflows at the High Flux Isotope Reactor (HFIR) and the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory (ORNL) is mainly determined by the time spent loading raw measurement events stored in large and sparse datasets. This paper describes: (1) our long-term view to leverage SNS and HFIR data management needs with our experience at ORNL’s world-class high performance computing (HPC) facilities, and (2) our short-term efforts to speed up current workflows using Mantid, a data analysis and reduction community framework used across several neutron scattering facilities. We show that minimally invasive short-term improvements in metadata management have a moderate impact in speeding up current production workflows. We propose a more disruptive domain-specific solution: the No Cost Input Output (NCIO) framework, we provide an overview, the risks and challenges in NCIO’s adoption by HFIR and SNS stakeholders.

Godoy, William↗

Effect of hydrogen isotope on plasma impedance and thermal pinching induced by single aerosol droplets injected into an inductively coupled plasma

The mass of the hydrogen isotope in micrometer-sized aqueous droplets introduced into an ICP has been found to affect the degree of resulting plasma perturbation. Studied plasma perturbations include local plasma cooling, plasma shrinkage due to thermal pinching, and changes in plasma impedance. The local cooling effect caused by a vaporizing aerosol droplet was found to be similar between H 2 O and D 2 O. This finding is likely a result of the similar heat capacities and vaporization rates of H 2 O and D 2 O droplets and of the comparable thermal conductivities and dissociation kinetics of H 2 O and D 2 O vapor. In contrast, a clear isotope effect was observed for plasma shrinkage and impedance change, with H 2 O causing a considerably stronger effect. Plasma shrinkage, gauged by the reduction in Ar emission at the edge of the plasma, was detected at all observation heights within the load-coil region, with D 2 O droplets causing as much as 30% less of an effect than H 2 O. Likewise, D 2 O droplets induce significantly less change in plasma impedance than H 2 O droplets. Depending on experimental conditions and the probing method, changes in plasma impedance caused by monodisperse D 2 O droplets were only 52%–80% that of H 2 O. The lower influence on plasma shrinkage and impedance change for D 2 O droplets is believed to be related to the much lower thermal conductivity of atomic deuterium, around 70% that of atomic hydrogen (protium). The time required for the plasma impedance to return to its original steady-state value was comparatively long (~10 ms) and similar for H 2 O and D 2 O droplets.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Optimal Design and Operation of Intensified Absorbers with 3D-Printed Packing for Solvent-Based CO 2 Capture

Many potential solvent-based carbon capture processes suffer from a high heat of absorption of CO 2 that adversely affects the thermodynamic driving force. While interstage coolers are often used for removing a portion of the generated heat by removing the solvent or a portion of the solvent from a stage and cooling and returning it back to the absorber, they can be placed only at discrete locations in the tower. This work investigates intensified absorbers with 3D-printed packing that includes an internal cooler and therefore can be potentially used for maximizing the operational efficiency of the absorbers for CO 2 capture. The intensified absorber is modeled by using a generic, first-principles, equation-oriented absorber column model. Since the placement of these intensified packings would cause a loss of area/volume used for mass transfer, optimization of the proposed intensified absorber is performed by optimally selecting the locations at which to place these devices and designing them such that the trade-off due to the addition of the heat removal area and the resulting loss in the mass transfer area is accounted for. Results show that optimally placed and designed intensified packings can lead to a significant increase in the capture efficiency of the process in comparison to a similar column with no internal cooling. It is also observed that by optimally placing and designing intensified packings, the lean solvent flow rate to the absorber can be decreased, and the CO 2 lean loading can be increased while still maintaining the same capture efficiency. These process changes can lead to a substantial reduction in the cost of capture.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Secondary-Source Core Reload Modeling with VERA

The CASL reactor simulation package VERA has been adapted to provide high-fidelity simulation capabilities for modeling source range detector response during subcritical reactor configurations. New features include the activation and shuffling of secondary-source assemblies, use of burned fuel neutron emission data from the ORIGEN depletion solver to the MPACT deterministic neutron transport solver, allowance of user-defined sources in MPACT based on material composition, ability to solve the subcritical source-driven system with neutron multiplication using the MPACT diffusion solver, and transfer of the calculated fission source from MPACT to the continuous-energy Monte Carlo solver Shift for final detector response evaluation using the CADIS methodology for variance reduction. These new capabilities were benchmarked against Watts Bar Unit 1 plant operating data for the first few fuel loading steps and were found to demonstrate excellent agreement with the measured data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Characterization and Optimization of the Fitting of Quantum Correlation Functions

This case study presents a characterization and optimization of an application code for extracting parton distribution functions from high energy electron-proton scattering data. Profiling this application code reveals that the phase-space density computation accounts for 93% of the overall execution time for a single iteration on a single core. When executing multiple iterations in parallel on a multicore system, the application spends 78% of its overall execution time idling due to load imbalance. We address these issues by first transforming the application code from Python to C++ and then tackling the application load imbalance via a hybrid scheduling strategy that combines dynamic and static scheduling. These techniques result in a 62% reduction in CPU idle time and a 2.46x speedup in overall execution time per node. In addition, the typically enabled power-management mechanisms in supercomputers (e.g., AMD Turbo Core, Intel Turbo Boost, and RAPL) can significantly impact intra-node scalability when more than 50% of the CPU cores are used. This finding underscores the importance of understanding system interactions with power management, as they can adversely impact application performance, and highlights the necessity of intra-node scaling tests to identify performance degradation that inter-node scaling tests might otherwise overlook.

Chuang, Pi-Yueh [Virginia Tech,Dept. of Computer S↗

Transactive HVAC Agent - Design and Performance Evaluation

Transactive energy systems are playing an increasingly important role in the efficient and reliable marketbased operation of the power grid. Since a significant portion of the residential building energy consumption is from heating ventilation and air conditioning (HVAC) systems, HVAC is one of the most promising resources to provide load flexibility. However, utilizing HVAC flexibility to provide various grid services while simultaneously maintaining consumer comfort and cost-reductions is challenging. This paper presents a design of a transactive HVAC agent (T-HVAC) to be used as a supervisory control for the HVAC system that can simultaneously ensure comfort and cost-reduction. In particular, the T-HVAC a) estimates HVAC thermal dynamics, b) ensures optimal operations of the HVAC system, and c) participates into markets, and d) implements a market-based control via controlling the thermostat temperature set-point. The T-HVAC performance is demonstrated through multiple scenarios and illustrations.

Demand flexibility, distribution system, HVAC, Tra↗