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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Structure of Asphaltenes during Precipitation Investigated by Ultra-Small-Angle X-ray Scattering

Time-resolved size and structure measurements of asphaltenes while in the process of precipitating were monitored for the first time using ultra-small-angle X-ray scattering. The results revealed that asphaltenes precipitating from a heptane–toluene mixture demonstrate a hierarchical structure of an asphaltene-rich phase (e.g., droplet) that further agglomerates into fractal flocs. The fractal flocs that form by the agglomeration of the asphaltene-rich phase are what is commonly detected by optical microscopy above the precipitation detection point. The surface of the asphaltene-rich phase is initially rough and transitions to a smooth interface, as would be expected for a highly viscous liquid. Simultaneous small-angle X-ray scattering measurements were also performed to investigate the structure of soluble asphaltenes, providing comprehensive structural characterization from the nanometer- to micrometer-length scales as a function of time. Further, the results demonstrate that the size and concentration of asphaltenes remaining in solution (e.g., soluble asphaltenes) do not change during precipitation, whereas the structure of insoluble asphaltenes varies. The ability to measure the properties of asphaltenes as they undergo precipitation opens new opportunities for understanding the fundamental mechanisms of asphaltene deposition and aggregation and the impact of chemical inhibitors to alter these processes. Here, the universality of these conclusions and how specific properties vary as a function of asphaltene source and solution properties can provide valuable insight into asphaltene behavior.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

DNV GL Joint Industry Project on Validation of Turbulence Models

This shared resource CRADA defines research collaborations between the National Renewable Energy Laboratory (NREL) and Det Norske Veritas (Norway) and Germanischer Lloyd (Germany), known as DNV GL, an international certification body. Under the terms and conditions described in this CRADA agreement, NREL will participate in a wind turbine Joint Industry Project (JIP) led by DNV GL, and including nine other Joint Industry Project sponsors and partners to examine the wind inflow models needed to define the design conditions for wind turbines, with specific focus on atmospheric turbulence. The international design standards are implemented by certification companies, such as DNV GL, the organizing agent of the JIPs. Through this collaboration, the JIP participants have the ability to improve wind turbine design, internationally, as well as in the United States, and can make this improvement by leveraging the significant aggregation of industry funds that has been organized by DNV GL.

17 WIND ENERGY↗
DOE OSTI2020

Effects of soil particles and convective transport on dispersion and aggregation of nanoplastics via small-angle neutron scattering (SANS) and ultra SANS (USANS)

Terrestrial nanoplastics (NPs) pose a serious threat to agricultural food production systems due to the potential harm of soil-born micro- and macroorganisms that promote soil fertility and ability of NPs to adsorb onto and penetrate into vegetables and other crops. Very little is known about the dispersion, fate and transport of NPs in soils. This is because of the challenges of analyzing terrestrial NPs by conventional microscopic techniques due to the low concentrations of NPs and absence of optical transparency in these systems. Herein, we investigate the potential utility of small-angle neutron scattering (SANS) and Ultra SANS (USANS) to probe the agglomeration behavior of NPs prepared from polybutyrate adipate terephthalate, a prominent biodegradable plastic used in agricultural mulching, in the presence of vermiculite, an artificial soil. SANS with the contrast matching technique was used to study the aggregation of NPs co-dispersed with vermiculite in aqueous media. We determined the contrast match point for vermiculite was 66% D 2 O / 33% H 2 O. At this condition, the signal for vermiculite was ~50–100%-fold lower that obtained using neat H 2 O or D 2 O as solvent. According to SANS and USANS, smaller-sized NPs (50 nm) remained dispersed in water and did not undergo size reduction or self-agglomeration, nor formed agglomerates with vermiculite. Larger-sized NPs (300–1000 nm) formed self-agglomerates and agglomerates with vermiculite, demonstrating their significant adhesion with soil. However, employment of convective transport (simulated by ex situ stirring of the slurries prior to SANS and USANS analyses) reduced the self-agglomeration, demonstrating weak NP-NP interactions. Convective transport also led to size reduction of the larger-sized NPs. Therefore, this study demonstrates the potential utility of SANS and USANS with contrast matching technique for investigating behavior of terrestrial NPs in complex soil systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

DNV GL Joint Industry Project on Coupled Analysis of Floating Wind Turbines

This shared resource CRADA defines research collaborations between the National Renewable Energy Laboratory (NREL) and Det Norske Veritas (Norway) and Germanischer Lloyd (Germany), known as DNV GL, an international certification body. Under the terms and conditions described in this CRADA agreement, NREL will participate in an offshore wind turbine Joint Industry Project (JIP) led by DNV GL, and including twelve other Joint Industry Project participants, to examine the coupled analysis methodologies needed for the design and verification of floating wind turbines. The international design standards are implemented by certification companies, such as DNV GL, the organizing agent of the JIP. Through this collaboration, the JIP participants have the ability to improve offshore wind turbine design, internationally, as well as in the United States, and can make this improvement by leveraging the significant aggregation of industry funds that has been organized by DNV GL.

17 WIND ENERGY↗
DOE OSTI2017

Role of Surface Chemistry in Grain Adhesion and Dissipation during Collisions of Silica Nanograins

The accretion of dust grains to form larger objects, including planetesimals, is a central problem in planetary science. It is generally thought that weak van der Waals interactions play a role in accretion at small scales where gravitational attraction is negligible. However, it is likely that in many instances, chemical reactions also play an important role, and the particular chemical environment on the surface could determine the outcomes of dust grain collisions. Using atomic-scale simulations of collisional aggregation of nanometer-sized silica (SiO{sub 2}) grains, we demonstrate that surface hydroxylation can act to weaken adhesive forces and reduce the ability of mineral grains to dissipate kinetic energy during collisions. The results suggest that surface passivation of dangling bonds, which generally is quite complete in an Earth environment, should tend to render mineral grains less likely to adhere during collisions. It is shown that during collisions, interactions scale with interparticle distance in a manner consistent with the formation of strong chemical bonds. Finally, it is demonstrated that in the case of collisions of nanometer-scale grains with no angular momentum, adhesion can occur even for relative velocities of several kilometers per second. These results have significant implications for early planet formation processes, potentially expanding the range of collision velocities over which larger dust grains can form.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Controlled and Selective Photo-oxidation of Amyloid-β Fibrils by Oligomeric p-Phenylene Ethynylenes

Photodynamic therapy (PDT) has been explored as a therapeutic strategy to clear toxic amyloid aggregates involved in neurodegenerative disorders such as Alzheimer’s disease. A major limitation of PDT is off-target oxidation, which can be lethal for the surrounding cells. In this work, we have shown that a novel class of oligo-p-phenylene ethynylenes (OPEs) exhibit selective binding and fluorescence turn-on in the presence of prefibrillar and fibrillar aggregates of disease-relevant proteins such as amyloid-β (Aβ) and α-synuclein. Concomitant with fluorescence turn-on, OPE also photosensitizes singlet oxygen under illumination through the generation of a triplet state, pointing to the potential application of OPEs as photosensitizers in PDT. Herein, we investigated the photosensitizing activity of an anionic OPE for the photo-oxidation of Aβ fibrils and compared its efficacy to the well-known but nonselective photosensitizer methylene blue (MB). Our results show that, while MB photo-oxidized both monomeric and fibrillar conformers of Aβ40, OPE oxidized only Aβ40 fibrils, targeting two histidine residues on the fibril surface and a methionine residue located in the fibril core. Oxidized fibrils were shorter and more dispersed but retained the characteristic β-sheet rich fibrillar structure and the ability to seed further fibril growth. Importantly, the oxidized fibrils displayed low toxicity. We have thus discovered a class of novel theranostics for the simultaneous detection and oxidization of amyloid aggregates. Importantly, the selectivity of OPE’s photosensitizing activity overcomes the limitation of off-target oxidation of traditional photosensitizers and represents an advancement of PDT as a viable strategy to treat neurodegenerative disorders.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Accurate spatiotemporal predictions of daily stream temperature from statistical models accounting for interactions between climate and landscape

Spatial and temporal patterns in stream temperature are primary factors determining species composition, diversity and productivity in stream ecosystems. The availability of spatially and temporally continuous estimates of stream temperature would improve the ability of biologists to fully explore the effects of stream temperature on biota. Most statistical stream temperature modeling techniques are limited in their ability to account for the influence of variables changing across spatial and temporal gradients. We identified and described important interactions between climate and spatial variables that approximate mechanistic controls on spatiotemporal patterns in stream temperature. With identified relationships we formed models to generate reach-scale basin-wide spatially and temporally continuous predictions of daily mean stream temperature in four Columbia River tributaries watersheds of the Pacific Northwest, USA. Models were validated with a testing dataset composed of completely distinct sites and measurements from different years. While some patterns in residuals remained, testing dataset predictions of selected models demonstrated high accuracy and precision (averaged RMSE for each watershed ranged from 0.85–1.54 °C) and was only 17% higher on average than training dataset prediction error. Aggregating daily predictions to monthly predictions of mean stream temperature reduced prediction error by an average of 23%. The accuracy of predictions was largely consistent across diverse climate years, demonstrating the ability of the models to capture the influences of interannual climatic variability and extend predictions to timeframes with limited temperature logger data. Results suggest that the inclusion of a range of interactions between spatial and climatic variables can approximate dynamic mechanistic controls on stream temperatures.

Siegel, Jared E.↗
DOE OSTI2020

Asphaltene-induced spontaneous emulsification: Effects of interfacial co-adsorption and viscoelasticity

Asphaltenes are a class of high molecular weight aromatic compounds found in crude oil. They adsorb onto toluene-water interfaces and induce a spontaneous emulsification phenomenon, whereby stable water-in-oil emulsions form without the need of an external energy input. This work aims to control and understand the factors affecting spontaneous droplet formation in the presence of asphaltene adsorption. This is particularly useful for crude oil refining, where the presence of a stable emulsion hampers the efficiency of downstream processing operations. We explore the effect of the addition of copolymers designed as crude oil flow improvers as a means to control the extent of emulsion formation. We find that the polymers competitively adsorb onto the toluene-water interface and diminish spontaneous emulsification. Additionally, we conduct fluorescence microscopy experiments and measurements of the interfacial energy to determine the mechanism of spontaneous emulsification in asphaltene systems. We conclude that an emulsion forms via the diffusion of molecular water into the oil phase and subsequent binding with asphaltene aggregates, leading to the nucleation of micrometer-sized water droplets. We find that the polymer forms complexes with the dissolved asphaltenes, possibly hampering the ability of diffused water to bind to the asphaltenes and reducing the extent of spontaneous emulsification. Finally, we investigate the role of interfacial shear and dilatational viscoelasticity to better understand which fundamental interfacial properties are important in the emulsification of asphaltene-laden systems. We find that the rate of formation of an interfacial microstructural network is inversely correlated with the extent and rate of spontaneous emulsification.

42 ENGINEERING↗
DOE OSTI2014

Optimization of nanoparticle structure for improved conversion efficiency of dye solar cell

Heavy dye loading and the ability to contain the light within the thin layer (typically ∼12 μm) are the requirement needed for the photoelectrode material in order to enhance the harvesting efficiency of dye solar cell. This can be realized by optimizing the particle size with desirable crystal structure. The paper reports the investigation on the dependency of the dye loading and light scattering on the properties of nanostructured photoelectrode materials by comparing 4 different samples of TiO{sub 2} in the form of nanoparticles and micron-sized TiO{sub 2} aggregates which composed of nanocrystallites. Their properties were evaluated by using scanning electron microscopy, X-ray diffraction and UVVis spectroscopy while the performance of the fabricated test cells were measured using universal photovoltaic test system (UPTS) under 1000 W/cm{sup 2} intensity of radiation. Nano sized particles provide large surface area which allow for greater dye adsorption but have no ability to retain the incident light in the TiO{sub 2} film. In contrast, micron-sized particles in the form of aggregates can generate light scattering allowing the travelling distance of the light to be extended and increasing the interaction between the photons and dye molecules adsorb on TiO{sub 2}nanocrystallites. This resulted in an improvement in the conversion efficiency of the aggregates that demonstrates the close relation between light scattering effect and the structure of the photolectrode film.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Clay, Water, and Salt: Controls on the Permeability of Fine-Grained Sedimentary Rocks

We report that the ability to predict the permeability of fine-grained soils, sediments, and sedimentary rocks is a fundamental challenge in the geosciences with potentially transformative implications in subsurface hydrology. In particular, fine-grained sedimentary rocks (shale, mudstone) constitute about two-thirds of the sedimentary rock mass and play important roles in three energy technologies: petroleum geology, geologic carbon sequestration, and radioactive waste management. The problem is a challenging one that requires understanding the properties of complex natural porous media on several length scales. One inherent length scale, referred to hereafter as the mesoscale, is associated with the assemblages of large grains of quartz, feldspar, and carbonates over distances of tens of micrometers. Its importance is highlighted by the existence of a threshold in the core scale mechanical properties and regional scale energy uses of shale formations at a clay content X clay ≈ 1/3, as predicted by an ideal packing model where a fine-grained clay matrix fills the gaps between the larger grains. A second important length scale, referred to hereafter as the nanoscale, is associated with the aggregation and swelling of clay particles (in particular, smectite clay minerals) over distances of tens of nanometers. Mesoscale phenomena that influence permeability are primarily mechanical and include, for example, the ability of contacts between large grains to prevent the compaction of the clay matrix. Nanoscale phenomena that influence permeability tend to be chemomechanical in nature, because they involve strong impacts of aqueous chemistry on clay swelling. The second length scale remains much less well characterized than the first, because of the inherent challenges associated with the study of strongly coupled nanoscale phenomena. Advanced models of the nanoscale properties of fine-grained media rely predominantly on the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory, a mean field theory of colloidal interactions that accurately predicts clay swelling in a narrow range of conditions (low salinity, low compaction, Na + counterion). An important feature of clay swelling that is not predicted by these models is the coexistence, in most conditions of aqueous chemistry and dry bulk density, of two types of pores between parallel smectite particles: mesopores with a pore width of >3 nm that are controlled by long-range interactions (the osmotic swelling regime) and nanopores with a pore width <1 nm that are controlled by short-range interactions (the crystalline swelling regime). Finally, nanogeochemical characterization and simulation techniques, including coarse-grained and all-atom molecular dynamics simulations, hold significant promise for the development of advanced constitutive relations that predict this coexistence and its dependence on aqueous chemistry.

58 GEOSCIENCES↗
DOE OSTI2013

Context dependent reversion of tumor phenotype by connexin-43 expression in MDA-MB231 cells and MCF-7 cells: Role of β-catenin/connexin43 association

Connexins (Cx), gap junction (GJ) proteins, are regarded as tumor suppressors, and Cx43 expression is often down regulated in breast tumors. We assessed the effect of Cx43 over-expression in 2D and 3D cultures of two breast adenocarcinoma cell lines: MCF-7 and MDA-MB-231. While Cx43 over-expression decreased proliferation of 2D and 3D cultures of MCF-7 by 56% and 80% respectively, MDA-MB-231 growth was not altered in 2D cultures, but exhibited 35% reduction in 3D cultures. C-terminus truncated Cx43 did not alter proliferation. Untransfected MCF-7 cells formed spherical aggregates in 3D cultures, and MDA-MB-231 cells formed stellar aggregates. However, MCF-7 cells over-expressing Cx43 formed smaller sized clusters and Cx43 expressing MDA-MB-231 cells lost their stellar morphology. Extravasation ability of both MCF-7 and MDA-MB-231 cells was reduced by 60% and 30% respectively. On the other hand, silencing Cx43 in MCF10A cells, nonneoplastic human mammary cell line, increased proliferation in both 2D and 3D cultures, and disrupted acinar morphology. Although Cx43 over-expression did not affect total levels of β-catenin, α-catenin and ZO-2, it decreased nuclear levels of β-catenin in 2D and 3D cultures of MCF-7 cells, and in 3D cultures of MDA-MB-231 cells. Cx43 associated at the membrane with α-catenin, β-catenin and ZO-2 in 2D and 3D cultures of MCF-7 cells, and only in 3D conditions in MDA-MB-231 cells. This study suggests that Cx43 exerts tumor suppressive effects in a context-dependent manner where GJ assembly with α-catenin, β-catenin and ZO-2 may be implicated in reducing growth rate, invasiveness, and, malignant phenotype of 2D and 3D cultures of MCF-7 cells, and 3D cultures of MDA-MB-231 cells, by sequestering β-catenin away from nucleus. - Highlights: • Cx43 over-expressing MCF-7 and MDA-MB-231 were grown in 2D and 3D cultures. • Proliferation and growth morphology were affected in a context dependent manner. • Extravasation ability of both MCF-7 and MDA-MB-231 cells was reduced. • Cx43-mediated gap junction complex assembly correlated with observed changes. • We propose that membranous Cx43 sequesters β-catenin away from the nucleus.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Effects of Si solute on the glass formation and atomic structure of Pd liquid

Molecular dynamics simulations were performed to study the effects of Si solute on the glass formation and crystallization of Pd liquid. Pure Pd sample prepared by quenching process with cooling rate of 10 13 K/s can be in an amorphous state but the structural analysis indicates there is nearly no glass-forming motif in the sample. However, doping a small amount Si (Si concentration ~ 4%) the sample can be vitrified at a cooling rate of 10 12 K/s. The glass-forming motifs such as Pd-centered Z13, Si-centered Z9-like and Mixed-ICO-Cube clusters with 5-fold local symmetry are found to be the dominant short-range orders in the glassy samples. With the increasing of the Si-doping concentration, these glass-forming motifs tend to aggregate and connect with each other forming a network structure. Our calculated results revealed that Si solutes in liquid Pd can significantly enhance the glass-forming ability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Demonstrating SolarPILOT’s Python API Through Heliostat Optimal Aimpoint Strategy Use Case

SolarPILOT is a software package that generates solar field layouts and characterizes the optical performance of concentrating solar power (CSP) tower systems. SolarPILOT was developed by the National Renewable Energy Laboratory (NREL) as a stand-alone desktop application but has also been incorporated into NREL’s1 System Advisor Model (SAM) in a simplified format. Prior means for user interaction with SolarPILOT have included the application’s graphical interface, the SAM routines with limited configurability, and through a built-in scripting language called “LK.” This paper presents a new, full-featured, Python-based application programmable interface (API) for SolarPILOT, which we hereafter refer to as CoPylot. CoPylot provides access to all SolarPILOT’s capabilities to generate and characterize power tower CSP systems seamlessly through Python. Supported capabilities include (i) creating and destroying a model instance with message reporting tools; (ii) accessing and setting any SolarPILOT variable including custom land boundaries for field layouts; (iii) programmatically managing receiver and heliostat objects with varied attributes for systems with multiple receiver or heliostat types; (iv) generating, assigning, and modifying solar field layouts including the ability to set individual heliostat locations, aimpoints, soiling rates, and reflectivity levels; (v) simulating solar field performance; (vi) returning detailed results describing performance of individual heliostats, the aggregate field, and receiver flux distribution; and, (vii) exporting Python-based model instances to multiple file formats. CoPylot enables Python users to perform detailed CSP tower analysis utilizing either the Hermite expansion technique (analytical) or the SolTrace ray-tracing engine. In addition to CoPylot’s functionality, Python users have access to the over 100,000 open-source libraries to develop, analyze, optimize, and visualize power tower CSP research. This enables CSP researchers to perform analysis that was previously not possible through SolarPILOT’s existing interfaces. This paper discusses the capabilities of CoPylot and presents a use case wherein we demonstrate optimal solar field aiming strategies.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2021

Demonstrating SolarPILOT's Python API Through Heliostat Optimal Aimpoint Strategy Use Case: Preprint

SolarPILOT is a software package that generates heliostat field layouts and characterizes the optical performance of concentrating solar power (CSP) tower systems. SolarPILOT was developed by the National Renewable Energy Laboratory (NREL) as a stand-alone desktop application but has also been incorporated into NREL's System Advisor Model (SAM) in a simplified format. Prior means for user interaction with SolarPILOT have included the application's graphical interface, the SAM routines with limited configurability, and through a built-in scripting language called "LK." This paper presents a new, full-featured Python-based application programmable interface (API) for SolarPILOT, which we hereafter refer to as CoPylot. CoPylot provides access to all SolarPILOT's capabilities to generate and characterize power tower CSP systems seamlessly through Python. Supported capabilities include (i) creating and destroying a model instances with message reporting tools; (ii) accessing and setting any SolarPILOT variable including custom land boundaries for field layout; (iii) programmatically managing receiver and heliostat objects with varied attributes for systems with multiple receiver or heliostat types; (iv) generating, assigning, and modifying heliostat field layouts including the ability to set individual heliostat locations, aimpoints, soiling rates, and reflectivity levels; (v) simulating heliostat field performance; (vi) returning detailed results describing performance of individual heliostats, the aggregate field, and receiver flux; and, (vii) exporting Python-based model instances to multiple file formats. CoPylot enables Python users to perform detailed tower CSP analysis utilizing either the Hermite expansion technique (analytical) or the SolTrace ray-tracing engine. In addition to CoPylot's functionality, Python users have access to the over 100,000 open-source libraries to develop, analyze, optimize, and visualize CSP tower research.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2026

Multi-physics Preconditioning for Thermally Activated Batteries

Thermal batteries, also known as molten-salt batteries, are single-use reserve power systems activated by pyrotechnic heat generation, which transitions the solid electrolyte into a molten state. The simulation of these batteries relies on multiphysics modeling to evaluate performance and behavior under various conditions. This paper presents advancements in scalable preconditioning strategies for the Thermally Activated Battery Simulator (TABS) tool, enabling efficient solutions to the coupled electrochemical systems that dominate computational costs in thermal battery simulations. We propose a hierarchical block Gauss-Seidel preconditioner implemented through the Teko package in Trilinos, which effectively addresses the challenges posed by tightly coupled physics, including charge transport, porous flow, and species diffusion. The preconditioner leverages scalable subblock solvers, including smoothed aggregation algebraic multigrid (SA-AMG) methods and domain-decomposition techniques, to achieve robust convergence and parallel scalability. Strong and weak scaling studies demonstrate the solver’s ability to handle problem sizes up to 51.3 million degrees of freedom on 2048 processors, achieving near sub-second setup and solve times for the end-to-end electrochemical solve. These advancements significantly improve the computational efficiency and turnaround time of thermal battery simulations, paving the way for higher-resolution models and enabling the transition from 2D axisymmetric to full 3D simulations.

25 ENERGY STORAGE↗
DOE OSTI2018

A study of appliance ownership and electricity consumption determinants in urban Ghanaian households

The residential sector in Ghana accounts for about 40% of aggregate electricity consumption out of which urban centers contribute 70%. The high weighted share of residential electricity use is attributed to high appliance ownership and use, and other household/building factors. The ability to determine how changes in the pattern of these factors influence electricity demand is critical if efforts to reduce consumption are to be effective. Here this study combines a residential electricity consumption survey (RECS) with electricity end-use monitoring of 60 households in Tema city Ghana, to yield the first ever comprehensive investigation of city-scale electricity consumption in urban Ghanaian homes. A multiple linear regression analysis is used to identify the most statistically significant indicators of appliance ownership and household electricity consumption. Results indicate that ownership of air conditioner, freezer, fan, refrigerator and television; and changes in socio-economic and building factors such as energy efficiency awareness and practice; income; household size and floor space show high statistical significance, and collectively explain 57% variance in households’ total electricity consumption. The presence of dependent children increases ownership of television, iron, washing machine and small kitchen appliances. This work provides a solid foundation for developing more tailored energy-saving policy interventions targeted at households.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

A Scalable, Distribution Network-Aware, Customer Privacy-Preserving Framework for Operation of Virtual Power Plants

This poster presents a hierarchical control framework for a virtual power plant that leverages behind-the-meter resources for grid services while maintaining customer privacy during setpoint disaggregation. Unlike many existing approaches, the virtual power plant model uses a hierarchical control strategy and an iterative approach to determine the optimal set point dis-aggregation without direct load control while maintaining system-level power flow and voltage constraints. The proposed approach is numerically validated on a synthetic distribution feeder in San Francisco, demonstrating the ability of the framework to provide privacy-preserving virtual power plant services.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Short-Term Electric Load Forecasting for a Residential Household in Alaska

Accurate short-term load forecasting at a fine scale is essential for demand response programs, peak shaving, and load-shedding strategies [1]. While traditionally, only aggregate short-term consumption data was available, advanced metering infrastructure (AMI) now provides data at the individual consumer level [1]. There is increasing interest in utilizing this data for short-term load forecasting (from an hour to a few days) to optimize grid operations. Electricity consumption in individual households is highly influenced by residents’ personal behaviors [2]. As a result, unlike aggregate loads, electrical power usage in single households often shows significant volatility, making meter-level load forecasting for individual users particularly challenging [3], [4]. Deep learning methods, with their strong ability to model nonlinear data, have become popular for improving the accuracy of household electricity consumption forecasting [4]. Notably, the Long ShortTerm Memory (LSTM) has attracted significant attention [5], [6].

42 ENGINEERING↗