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At least 1,621 records · Page 90
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DOE OSTI2022

Consensus-Based Approach for Active Power Control and Reserve Estimation in Distributed PV Systems

With the increased adoption of distributed energy resources (DER), they are expected to contribute to power system reliability services and enhance power system stability. This paper presents a distributed consensus control approach for the real-time active power reserve estimation and power management in distributed PV (photovoltaic) systems. The proposed method estimates the cumulative active power reserve from numerous PV generators using only the sparse communication network for a DER aggregator to provide active power regulation services. The real-time active power reserve estimation using the proposed approach can be used by DER aggregators to manage curtailment in distributed PV systems to maintain stipulated reserves and further to provide power system frequency regulation. Using the proposed approach, the DER aggregator only requires measurements at the feeder substation and it does not require information from individual DER units, thereby improving system resiliency. The proposed distributed consensus control method is validated on IEEE 123 testbed using PSCAD simulations.

active power reserve↗
DOE OSTI2024

Robust VAR Capability Curve of DER with Uncertain Renewable Generation

Active distribution system with high penetration of inverter based distributed energy resources(DER), can be utilized for var-related ancillary services at the transmission side interface. In order to utilize the DER flexibility, transmission system operator must be presented the aggregated DER flexibility of distribution system. However, the uncertainty in renewable generation, questions the credibility of aggregated capability curve in practice. In this paper, we incorporate the uncertainty into aggregation process to develop capability curve while preserving the real physics (unbalance and lossy nature) of distribution system. The Resulting capability curve with the associated probability can be harnessed by the TSO for decision making for both planning and operation.

Kar, Aditya Shankar↗
DOE OSTI2021

Simulation of PV Variability as a Function of PV Generation and Plant Size

The deployment of photovoltaic (PV) systems continues to show significant expansion; however, this growth has brought added attention to issues around the variability of the solar resource. Both spatial and temporal variability exist. Temporal scales can range from the sub-second to multiyear, whereas spatial scales can range from a few meters to tens of kilometers. There are multiple methods described in the literature to quantify PV variability at various spatial and temporal scales. This study focuses on short-term temporal variability and uses similar approaches with the addition of PV plant size a parameter to quantify variability. The method employed here incorporates the normalization of clear-and cloudy-sky conditions and PV plant size to quantify nominal variability metrics. The distribution and fluctuations of these metrics provide relevant information that is useful for system operations. The National Solar Radiation Database (NSRDB) is used to simulate PV variability as a function of PV generation and plant size. Hypothetical but realistic system information at 33 locations is used to model PV generation by feeding NSRDB solar irradiance data to the National Renewable Energy Laboratory’s System Advisor Model (SAM). Over the selected region, it is found that the aggregated ramp rates for the 1-minute data are associated with standard deviations ranging from 0.002–0.055 on a daily basis; however, hourly intervals induce higher aggregated ramp rates than the other timescales. Even though minute-to-minute variations are significant for the 1-minute time-scale, the standard deviation aggregated into a daily metric is smaller because of the cancellation of values.

irradiance↗
DOE OSTI2024

HAPPA: A Modular Platform for HPC Application Resilience Analysis with LLMs Embedded

High-performance computing (HPC) systems are increasingly vulnerable to soft errors, which pose significant challenges in maintaining computational accuracy and reliability. Predicting the resilience of HPC applications to these errors is crucial for robust code protection and detailed resilience analysis. In this study, we present HAppA, a modular platform designed for HPC Application Resilience Analysis. Embedding Large Language Models (LLMs), HAppA addresses understanding the context information of long code sequences typical in HPC applications. HAppA implements a novel code representation module that chunks the code into fixed-size segments and aggregates the embeddings of these segments. Three aggregation methods have been explored: MeanPooling, MaxPooling, and LSTM-based techniques. We built a DAtaset for REsilience analysis using Fault Injection (FI), named DARE. Using our DARE dataset, HAppA is trained for regression prediction tasks. Our evaluation results demonstrate the predictive accuracy of HAppA compared to other models, particularly noting that the LSTM-based aggregation method -- HAppA-LSTM -- achieves a mean squared error (MSE) of 0.078 for SDC prediction, surpassing the existing state-of-the-art PARIS model, which recorded an MSE of 0.1172. Additionally, HAppA with the KeyBERT model extracts a list of keywords representing the source code. A comprehensive importance analysis of these keywords further elucidates the code patterns contributing to the error rate. These findings highlight the effectiveness of HAppA in analyzing the resilience of HPC applications and establish a new benchmark for predictive accuracy in resilience.

Jiang, Hailong [Kent State University]↗
DOE OSTI2019

Individual Load Model Parameter Estimation in Distribution Systems Using Load Switching Events

There currently exists a mature literature on modeling the aggregate load of a distribution feeder by making use of measurements at its feeder-head at substation. The primary application of such feeder-aggregated load models is in sub-transmission or transmission system analysis. However, there is a growing need in practice also to model each individual load across the feeder. If available, such individual load models have applications in power distribution system analysis, e.g., to better integrate distributed energy resources or to improve power quality and reliability. Motivated by this observation, in this paper, we propose a new method for individual load modeling in power distribution systems. It works by using the measurements only at the feeder-head. It takes an innovative approach to analyzing the load switching events across the distribution feeder itself, instead of or in addition to relying on upstream voltage events that are commonly used in feeder-aggregated load modeling. By tracking the downstream load switching events, the proposed method can make a robust estimation of the ZIP load model parameters for all individual loads. The proposed method is examined on small illustrative test-feeders as well as the IEEE 33-bus test system under various operating scenarios. The adverse impact of errors in measurements and system parameters are also investigated on the performance of the developed load modeling method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Bayesian Framework for Multi-Timescale State Estimation in Low-Observable Distribution Systems

To support the smart grid paradigm, there has been a significant increase in sensor deployments and metering infrastructure in distribution systems. However, the measurements provided by these sensors and metering devices are typically sampled at different rates and could suffer from losses during the aggregation process. It is crucial to effectively reconcile the time-series measurements for a reliable state estimation. While weighted least squares has been the traditional approach for state estimation, sparsity-based approaches like matrix completion have become popular due to their superior performance in low-observability conditions. This paper proposes a Bayesian framework for both multi-timescale data aggregation and matrix completion based state estimation. Specifically, the multiscale time-series data aggregated from heterogenous sources are reconciled using a multitask Gaussian process that exploits the spatio-temporal correlations. Here, the resulting consistent timeseries alongwith the confidence bound on the imputations are fed into a Bayesian matrix completion method augmented with linearized power-flow constraints to accurately estimate the states in low-observability conditions. Results on three phase unbalanced IEEE 37 and IEEE 123 bus test systems reveal the superior performance of the proposed Bayesian framework. The computational complexity for the proposed Bayesian framework is also quantified.

42 ENGINEERING↗
DOE OSTI2023

Fairness-Aware Distributed Energy Coordination for Voltage Regulation in Power Distribution Systems

The accelerating deployment of solar photovoltaics into low-voltage distribution networks can cause reverse power flow and overvoltage problems. However, if coordinated properly, the real and reactive power flexibility of these resources enables distribution operators to manage their networks more efficiently. Existing literature is rich in droop-based control (Volt-Watt and Volt-VAr) and optimization-based distributed energy coordination for four-quadrant control of photovoltaics to prevent overvoltage issues. While optimal coordination can effectively mitigate overvoltage, it tends to treat resources at sensitive parts of the grid unfairly. Here, to address this concern, we propose a distributed optimal power flow formulation that incorporates fairness in curtailing photovoltaic generation and utilizes the reactive power capability of smart inverters. The proposed distributed formulation allows for scalable resource aggregation that can be leveraged to achieve fairness within a certain segment of the grid and/or fairness across the entire network. Fair curtailment of photovoltaic systems is demonstrated with aggregation at each of two layers in a distribution network: 1) area-level fairness and 2) feeder-level fairness. To explore the trade-off between fairness and optimal utilization, the fairness-aware control actions are compared against the performance of a centralized controller that aims to maximize the aggregate PV generation without incorporating fairness. Simulation results show that introducing area-level fairness increased curtailment by 0.0101 percentage points and feeder-level fairness increased curtailment by 0.0458 percentage points compared to a fairness-agnostic control.

Poudel, Shiva↗
DOE OSTI2014

A Structure-Based Distance Metric for High-Dimensional Space Exploration with Multi-Dimensional Scaling

Although the Euclidean distance does well in measuring data distances within high-dimensional clusters, it does poorly when it comes to gauging inter-cluster distances. This significantly impacts the quality of global, low-dimensional space embedding procedures such as the popular multi-dimensional scaling (MDS) where one can often observe non-intuitive layouts. We were inspired by the perceptual processes evoked in the method of parallel coordinates which enables users to visually aggregate the data by the patterns the polylines exhibit across the dimension axes. We call the path of such a polyline its structure and suggest a metric that captures this structure directly in high-dimensional space. This allows us to better gauge the distances of spatially distant data constellations and so achieve data aggregations in MDS plots that are more cognizant of existing high-dimensional structure similarities. Our MDS plots also exhibit similar visual relationships as the method of parallel coordinates which is often used alongside to visualize the high-dimensional data in raw form. We then cast our metric into a bi-scale framework which distinguishes far-distances from near-distances. The coarser scale uses the structural similarity metric to separate data aggregates obtained by prior classification or clustering, while the finer scale employs the appropriate Euclidean distance.

Clustering↗
DOE OSTI2018

Microbial interactions in the anaerobic oxidation of methane: model simulations constrained by process rates and activity patterns: Process modelling of anaerobic methane oxidation

Proposed syntrophic interactions between the archaeal and bacterial cells mediating anaerobic oxidation of methane coupled with sulfate reduction include electron transfer through (1) the exchange of H2 or small organic molecules between methane-oxidizing archaea and sulfate-reducing bacteria, (2) the delivery of disulfide from methane-oxidizing archaea to bacteria for disproportionation and (3) direct interspecies electron transfer. Each of these mechanisms was implemented in a reactive transport model. The simulated activities across different arrangements of archaeal and bacterial cells and aggregate sizes were compared to empirical data for AOM rates and intra-aggregate spatial patterns of cell-specific anabolic activity determined by FISH-nanoSIMS. Additionally, simulation results showed that rates for chemical diffusion by mechanism (1) were limited by the build-up of metabolites, while mechanisms (2) and (3) yielded cell specific rates and archaeal activity distributions that were consistent with observations from single cell resolved FISH-nanoSIMS analyses. The novel integration of both intra-aggregate and environmental data provided powerful constraints on the model results, but the similarities in model outcomes for mechanisms (2) and (3) highlight the need for additional observational data (e.g. genomic or physiological) on electron transfer and metabolic functioning of these globally important methanotrophic consortia.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Local Communication in Populations of Thermostatically Controlled Loads

Thermostatically controlled loads (TCLs) have shown great potential for demand response (DR) in electric grid operations. However, it has been commonly seen that DR events using TCLs may cause load synchronization and unwanted oscillatory effects, especially in homogeneous populations. In an attempt to mitigate the negative impacts of DR events, a decentralized method is proposed that modifies each thermostat behavior based on the activity of a small number of nearby TCLs. This feedback introduces the possibility of instability in the aggregate behavior. A stability analysis is performed on a linearized model of the aggregate system and the results of that analysis compared to simulation results. The proposed modification of thermostat behavior results in fourfold reduction in the post-DR peak while suppressing ensuing oscillations at the expense of a modest increase in compressor cycling. Further, the linearized model also provides insight into the aggregate behavior of the population.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Characterization of Syntrophic Geobacter Communities Using ToF-SIMS

The aggregation of syntrophic Geobacter metallireducens and Geobacter sulfurreducens is known to be beneficial for enhancing direct interspecies electron transfer (DIET). However, the chemical speciation of such co-cultured communities was unclear. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) has been used to characterize biological samples relevant to aggregates of Geobacter, including G. metallireducens and G. sulfurreducens single cultures in planktonic, biofilms formed from either the single bacteria or both, and co-cultures of these two strains in planktonic and aggregate forms. By using principle component analysis (PCA), the syntrophic Geobacter communities were significantly distinguished from their planktonic cells by a series of characteristic peaks such as amino acids, fatty acids/lipids, and quorum sensing signal molecules, indicating a different chemical composition and structure formed on their surfaces. Additionally, insights of co-culture community dynamics were obtained from a new perspective . These first SIMS results demonstrate that proteins played an important role in microbial communications.

ToF-SIMS, Geobacter, DIET, syntrophic↗
DOE OSTI2015

Characterization of cardiac quiescence from retrospective cardiac computed tomography using a correlation-based phase-to-phase deviation measure

Purpose: Accurate knowledge of cardiac quiescence is crucial to the performance of many cardiac imaging modalities, including computed tomography coronary angiography (CTCA). To accurately quantify quiescence, a method for detecting the quiescent periods of the heart from retrospective cardiac computed tomography (CT) using a correlation-based, phase-to-phase deviation measure was developed. Methods: Retrospective cardiac CT data were obtained from 20 patients (11 male, 9 female, 33–74 yr) and the left main, left anterior descending, left circumflex, right coronary artery (RCA), and interventricular septum (IVS) were segmented for each phase using a semiautomated technique. Cardiac motion of individual coronary vessels as well as the IVS was calculated using phase-to-phase deviation. As an easily identifiable feature, the IVS was analyzed to assess how well it predicts vessel quiescence. Finally, the diagnostic quality of the reconstructed volumes from the quiescent phases determined using the deviation measure from the vessels in aggregate and the IVS was compared to that from quiescent phases calculated by the CT scanner. Three board-certified radiologists, fellowship-trained in cardiothoracic imaging, graded the diagnostic quality of the reconstructions using a Likert response format: 1 = excellent, 2 = good, 3 = adequate, 4 = nondiagnostic. Results: Systolic and diastolic quiescent periods were identified for each subject from the vessel motion calculated using the phase-to-phase deviation measure. The motion of the IVS was found to be similar to the aggregate vessel (AGG) motion. The diagnostic quality of the coronary vessels for the quiescent phases calculated from the aggregate vessel (P{sub AGG}) and IVS (P{sub IV} {sub S}) deviation signal using the proposed methods was comparable to the quiescent phases calculated by the CT scanner (P{sub CT}). The one exception was the RCA, which improved for P{sub AGG} for 18 of the 20 subjects when compared to P{sub CT} (P{sub CT} = 2.48; P{sub AGG} = 2.07, p = 0.001). Conclusions: A method for quantifying the motion of specific coronary vessels using a correlation-based, phase-to-phase deviation measure was developed and tested on 20 patients receiving cardiac CT exams. The IVS was found to be a suitable predictor of vessel quiescence. The diagnostic quality of the quiescent phases detected by the proposed methods was comparable to those calculated by the CT scanner. The ability to quantify coronary vessel quiescence from the motion of the IVS can be used to develop new CTCA gating techniques and quantify the resulting potential improvement in CTCA image quality.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

SU-E-T-186: Cloud-Based Quality Assurance Application for Linear Accelerator Commissioning

Purpose: To identify anomalies and safety issues during data collection and modeling for treatment planning systems Methods: A cloud-based quality assurance system (AQUIRE - Automated QUalIty REassurance) has been developed to allow the uploading and analysis of beam data aquired during the treatment planning system commissioning process. In addition to comparing and aggregating measured data, tools have also been developed to extract dose from the treatment planning system for end-to-end testing. A gamma index is perfomed on the data to give a dose difference and distance-to-agreement for validation that a beam model is generating plans consistent with the beam data collection. Results: Over 20 linear accelerators have been commissioning using this platform, and a variety of errors and potential saftey issues have been caught through the validation process. For example, the gamma index of 2% dose, 2mm DTA is quite sufficient to see curves not corrected for effective point of measurement. Also, data imported into the database is analyzed against an aggregate of similar linear accelerators to show data points that are outliers. The resulting curves in the database exhibit a very small standard deviation and imply that a preconfigured beam model based on aggregated linear accelerators will be sufficient in most cases. Conclusion: With the use of this new platform for beam data commissioning, errors in beam data collection and treatment planning system modeling are greatly reduced. With the reduction in errors during acquisition, the resulting beam models are quite similar, suggesting that a common beam model may be possible in the future. Development is ongoing to create routine quality assurance tools to compare back to the beam data acquired during commissioning. I am a medical physicist for Alzyen Medical Physics, and perform commissioning services.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2014

Magnetorheological effect in the magnetic field oriented along the vorticity

In this work, we have studied the magnetorheological (MR) fluid rheology in the magnetic field parallel to the fluid vorticity. Experimentally, the MR fluid flow was realized in the Couette coaxial cylinder geometry with the magnetic field parallel to the symmetry axis. The rheological measurements were compared to those obtained in the cone-plate geometry with the magnetic field perpendicular to the lower rheometer plate. Experiments revealed a quasi-Bingham behavior in both geometries with the stress level being just a few dozens of percent smaller in the Couette cylindrical geometry at the same internal magnetic field. The unexpectedly high MR response in the magnetic field parallel to the fluid vorticity is explained by stochastic fluctuations of positions and orientations of the particle aggregates. These fluctuations are induced by magnetic interactions between them. Once misaligned from the vorticity direction, the aggregates generate a high stress independent of the shear rate, and thus assimilated to the suspension apparent (dynamic) yield stress. Quantitatively, the fluctuations of the aggregate orientation are modeled as a rotary diffusion process with a diffusion constant proportional to the mean square interaction torque. The model gives a satisfactory agreement with the experimental field dependency of the apparent yield stress and confirms the nearly quadratic concentration dependency σ{sub Y}∝Φ{sup 2.2}, revealed in experiments. The practical interest of this study lies in the development of MR smart devices with the magnetic field nonperpendicular to the channel walls.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2022

Community Structure and Microbial Associations in Sediment-Free Methanotrophic Enrichment Cultures from a Marine Methane Seep

We report Syntrophic consortia of anaerobic methanotrophic archaea (ANME) and sulfate-reducing bacteria (SRB) consume large amounts of methane and serve as the foundational microorganisms in marine methane seeps. Despite their importance in the carbon cycle, research on the physiology of ANME-SRB consortia has been hampered by the slow growth and complex physicochemical environment the consortia inhabit. Here, we report successful sediment-free enrichment of ANME-SRB consortia from deep-sea methane seep sediments in the Santa Monica Basin, California. Anoxic Percoll density gradients and size-selective filtration were used to separate ANME-SRB consortia from sediment particles and single cells to accelerate the cultivation process. Over a 3-year period, a subset of the sediment-associated ANME and SRB lineages, predominantly comprised of ANME-2a/2b (“Candidatus Methanocomedenaceae”) and their syntrophic bacterial partners, SEEP-SRB1/2, adapted and grew under defined laboratory conditions. Metagenome-assembled genomes from several enrichments revealed that ANME-2a, SEEP-SRB1, and Methanococcoides in different enrichments from the same inoculum represented distinct species, whereas other coenriched microorganisms were closely related at the species level. This suggests that ANME, SRB, and Methanococcoides are more genetically diverse than other members in methane seeps. Flow cytometry sorting and sequencing of cell aggregates revealed that Methanococcoides, Anaerolineales, and SEEP-SRB1 were overrepresented in multiple ANME-2a cell aggregates relative to the bulk metagenomes, suggesting they were physically associated and possibly interacting. Overall, this study represents a successful case of selective cultivation of anaerobic slow-growing microorganisms from sediments based on their physical characteristics, introducing new opportunities for detailed genomic, physiological, biochemical, and ecological analyses. Biological anaerobic oxidation of methane (AOM) coupled with sulfate reduction represents a large methane sink in global ocean sediments. Methane consumption is carried out by syntrophic archaeal-bacterial consortia and fuels a unique ecosystem, yet the interactions in these slow-growing syntrophic consortia and with other associated community members remain poorly understood. The significance of this study is the establishment of sediment-free enrichment cultures of anaerobic methanotrophic archaea and sulfate-reducing bacteria performing AOM with sulfate using selective cultivation approaches based on size, density, and metabolism. By reconstructing microbial genomes and analyzing community composition of the enrichment cultures and cell aggregates, we shed light on the diversity of microorganisms physically associated with AOM consortia beyond the core syntrophic partners. These enrichment cultures offer simplified model systems to extend our understanding of the diversity of microbial interactions within marine methane seeps.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2017

Crystal structure and optoelectronic properties of antiaromatic compound 3,4,9,10-tetrahydrodicyclopenta[cd,lm]perylene

An antiaromatic compound 3,4,9,10-tetrahydrodicyclopenta[cd,lm] perylene, was synthesized by a coupling reaction. Its crystal structure was determined by X-ray diffraction. Crystal structures shows that the antiaromatic compounds are aggregated to J-aggregation materials. It further results ultrafast charge separation at organic interface and electron transfer in the aggregation materials. UV-vis spectrum shows that title compound has a broad UV-vis light absorbance at the wavelength range from 250 to 470 nm and a 2.67 eV energy gap value between the highest occupied and the lowest unoccupied molecular orbital energy levels.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2018

Self-Organization of Phase Clusters in Homogeneously Disordered Polymer Composite Materials

The surface morphologies of homogeneously disordered polymer composite films and coatings prepared using mixtures of components with limited or negligible mutual solubility are studied by electron microscopy. We elaborate on the characteristic self-organization of phase clusters in our samples, in which one phase gives rise to the structural scaffold of the composite, an internal percolation cluster of particles. The cluster cavities filled with discrete particle aggregates of the other phase are characterized by a relatively narrow Gaussian-like size distribution. This topological structure arises if composites are prepared by observing specific concentration conditions or using structure modifiers that affect particle aggregation. Self-organization of phase clusters minimizes the entropy production when the components are mixed and gives rise to local ordering in spatial alternation of particle aggregates. The local order transforms into cellular disorder as the length scale increases.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

Diffusion of New Products with Recovering Consumers

We consider the diffusion of new products in the discrete Bass-SIR model, in which consumers who adopt the product can later “recover” and stop influencing their peers to adopt the product. To gain insight into the effect of the social network structure on the diffusion, we focus on two extreme cases. In the “most-connected” configuration where all consumers are inter-connected (complete network), averaging over all consumers leads to an aggregate model, which combines the Bass model for diffusion of new products with the SIR model for epidemics. In the “least-connected” configuration where consumers are arranged on a circle and each consumer can only be influenced by his left neighbor (one-sided 1D network), averaging over all consumers leads to a different aggregate model which is linear, and can be solved explicitly. We conjecture that for any other network, the diffusion is bounded from below and from above by that on a one-sided 1D network and on a complete network, respectively. When consumers are arranged on a circle and each consumer can be influenced by his left and right neighbors (two-sided 1D network), the diffusion is strictly faster than on a one-sided 1D network. This is different from the case of non-recovering adopters, where the diffusion on one-sided and on two-sided 1D networks is identical. We also propose a nonlinear model for recoveries, and show that consumers’ heterogeneity has a negligible effect on the aggregate diffusion.

97 MATHEMATICS AND COMPUTING↗