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At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Use of Machine Learning on PMU Data for Transmission System Fault Analysis

Synchrophasor technology has been used for monitoring, control, and protection of bulk power system for over 10 years. Deployment of phasor measurement units (PMUs) in the USA power system has surpassed 3000 units installed in the transmission substations as stand-alone intelligent electronic devices (IEDs) or as a software add-on to other devices such as digital protective relays (DPRs) or digital fault recorders (DFRs). By now, thousands of terabytes of PMU data may have been captured and stored by various transmission system operators (TSOs) and independent system operators (ISOs). This creates an opportunity to deploy advanced machine learning (ML) techniques to detect and classify faults recorded by PMUs automatically to be used by the system operators for rapid, critical decision-making when manual analysis of the past or unfolding events is not feasible. In this paper we offer a brief background on how the automated fault analysis may be done using DPR and/or DFR data, and compare some of the legacy approaches to the new ML approaches in the context of the system-wide PMU recordings. We then offer insights from developing practical ML solutions that have been applied on field recordings captured by close to 450 PMUs from all three US interconnections (Western, Eastern and ERCOT) over two years (2016-2017). We identify and illustrate ML challenges we addressed: inaccurate data, data with scarce and temporally imprecise fault labels, data recorded by PMUs sparsely located at substations resulting in the fault records taken afar from the ends of the faulted lines, data containing only positive sequence values, and data taken at different voltage levels. We then illustrate the ML model results for fault analysis under different application scenarios. The novelty of this study is not only in the design, implementation, and performance analysis of the ML algorithms, but also in the use of advanced fault modelling and simulation approaches to improve the training results when developing supervised ML models for fault detection and classification. Extensive simulations of faults were conducted on a 14-bus power system to create a training dataset with over 1400 accurately labelled faults. This dataset was applied to enhance the accuracy of fault detection and classification of machine learning-based models trained with small number of labelled faults in large datasets recorded in the grid interconnections ranging from 5,000 to 70,000 buses.

Synchrophasors, Machine Learning, Fault Analysis, ↗
DOE OSTI2026

Laboratory Evaluation of Federated, Hierarchical Controls for Distribution Power System Management: Preprint

The connection of more loads and distributed energy resources (DERs) to the distribution power system brings both challenges and opportunities to system operators. There are opportunities to aggregate flexible loads and DERs to provide transmission grid services, but the coordinated actions of DERs being managed by independent, third-party DER aggregators to support transmission system operations can present challenges. We developed a federated DER management architecture and control framework that aims to manage heterogeneous DERs to deliver reliable transmission grid services while respecting distribution system constraints. The controls include stochastic day-ahead optimization, model predictive control, and a simple real-time management scheme. We present simulation results obtained from a realistic laboratory test bed of federated controls managing DERs within a substation service area to make the substation net power follow the optimal net power determined by the day-ahead optimization based on cost and limiting reverse power flow.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Change in Brooklyn and Queens: How New York?s Reforming the Energy Vision Program and Con Edison Are Reshaping Electric Distribution Planning

The New York City boroughs of Brooklyn and Queens are undergoing a period of gentrification, infrastructure rebuilding, new construction, and load growth not experienced in decades. Significant numbers of residents are moving in, and structures that had been abandoned or were in disrepair are being refurbished and modernized to accommodate the burgeoning population. Homes, businesses, and industries are reviving areas long in decline, and Brooklyn's growth has made it the nation's fourth most populous city, according to the U.S. Census Bureau.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Availability and Maintenance Modeling for GIS Equipment Served in High-Speed Railway Under Incomplete Maintenance

Gas-insulated substation (GIS) equipment served in the traction power-supply system (TPSS) of the high-speed railway (HSR) suffers from extremely severe traction load conditions during its lifetime. In this paper, three major issues related to the actual field maintenance operations of GIS equipment in TPSS are addressed: 1) s-dependent degradation and shock process; 2) both spatial and temporal failure thresholds of shocks; and 3) incomplete maintenance (i.e., nonignorable maintenance time). To model the deterioration and failure process of GIS equipment, the hard failure model and the soft failure model are proposed. The characteristic function is utilized to bridge the s-dependent degradation and shock process in the soft failure model, while the extreme shock model (with spatial threshold) and δ-shock model (with temporal threshold) are introduced in the hard failure model. Furthermore, the index of availability, which combines both reliability and maintainability, is derived under the incomplete maintenance consideration. Based on the balance of availability and maintenance cost, the maintenance strategy with periodic inspections for GIS equipment in the long-run time span is developed. In conclusion, optimizations of three decision parameters (i.e., inspection period, extreme shock threshold, and δ-shock threshold) are implemented to achieve the best performance (with high availability and low maintenance cost) of the maintenance strategy.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2019

Topology Estimation using Graphical Models in Multi-Phase Power Distribution Grids

Power distribution grids are structurally operated radially, such that energized lines form a collection of trees with a substation at the root of each tree. The operational topology may change from time to time, however tracking these changes, even though important for the distribution grid operation and control, is hindered by limited real-time monitoring. This work develops a learning framework to reconstruct the radial operational structure of the distribution grid from synchronized voltage measurements. To detect operational lines our learning algorithm uses conditional independence tests for continuous random variables that is applicable to a wide class of probability distributions and Gaussian injections in particular. Furthermore, our algorithm applies to the practical case of unbalanced three-phase power flow. The performance is validated on AC power flow simulations over three phase IEEE distribution grid test cases.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Trap‐Engineering the Persistent Luminescence of Ca 3 Ga 4 O 9 :Tb 3+ via Al 3+ Substitution for Optical Data Storage

Abstract Optically stimulated luminescence (OSL) materials hold great potential for optical data storage (ODS) and anticounterfeiting applications. Nevertheless, the scarcity of suitable luminescent materials with deep‐level traps remains a significant obstacle. Herein, a host substation strategy have been employed to tune the persistent luminescence (PersL) and OSL properties of Ca 3 Ga 4 O 9 :Tb 3+ by Al 3+ substitution through trap engineering and demonstrated their potential. Specifically, the photoluminescence of the Ca 2.985 (Ga 1‐y% Al y% ) 4 O 9 :0.5%Tb 3+ of Tb 3+ is first investigated due to its different occupancies of Ca 2+ . The influence of host substitution on the crystal structure, trap depth, trap density, PersL, and OSL properties have further investigated. A series of strong PersL and OSL peaks from the Ca 2.985 (Ga 1‐y% Al y% ) 4 O 9 :0.5%Tb 3+ with bluish‐green emissions have been observed. The Ca 2.985 (Ga 1‐y% Al y% ) 4 O 9 :0.5%Tb 3+ have shown controllable photon release upon thermal and optical stimuli, enhancing their performance for ODS. Thermally stimulated luminescence suggests that vacancy and defect concentrations inside the Ca 3‐x% (Ga 1‐y% Al y% ) 4 O 9 :x%Tb 3+ can be manipulated by Tb 3+ doping and Al 3+ substitution, which ultimately leads to the formation of deep traps and a broad distribution of traps with increased deep trap concentration. The work demonstrates that trap engineering through Al 3 ⁺ substitution is an effective method for tuning PersL and OSL properties of Ca 2.985 (Ga 1‐y% Al y% ) 4 O 9 :0.5%Tb 3+ for ODS.

Abeywickrama, Thulitha M. [Department of Chemistry↗
DOE OSTI2020

One Electron Multiple Proton Transfer in Model Organic Donor–Acceptor Systems: Implications for High-Frequency EPR

EPR spectroscopy is an important spectroscopic method for identification and characterization of radical species involved in many biological reactions. The tyrosyl radical is one of the most studied amino acid radical intermediates in biology. Often in conjunction with histidine residues, it is involved in many fundamental biological electron and proton transfer processes, such as in the water oxidation in photosystem II. As biological processes are typically extremely complicated and hard to control, molecular bio-mimetic model complexes are often used to clarify the mechanisms of the biological reactions. In this work, we present theoretical calculations to investigate the sensitivity of magnetic resonance parameters to proton-coupled electron transfer events, as well as conformational substates of the molecular constructs which mimic the tyrosine-histidine (Tyr-His) pairs found in a large variety of proteins. Upon oxidation of the phenol, the Tyr analog, these complexes can perform not only one-electron one-proton transfer (EPT), but also one-electron two-proton transfers (E2PT). It is shown that in aprotic environment the g X -components of the electronicg-tensor are extremely sensitive to the first proton transfer from the phenoxyl oxygen to the imidazole nitrogen (EPT product), leading to a significant increase of the g X -value of up to 0.003, but are not sensitive to the second proton transfer (E2PT). In the latter case, the change of the g X -value is much smaller (ca. 0.0001), which is too small to be distinguished even by high-frequency EPR. The 14 N hyperfine values are also too similar to allow differentiation between the different protonation states in EPT and E2PT. The magnetic resonance parameters were also calculated as a function of the rotation angles around single bonds. It was demonstrated that rotation of the phenoxyl group results in large positive changes (> 0.001) in the g X -values. Analysis of the data reveals that the main source of these changes is related to the strength of the H-bond between phenoxyl oxygen and the proton(s) on N 1 and N 2 positions of the imidazole.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2017

Experience in the Implementation of an Automatic System for Stabilizing the Mode of a Power District in Terms of Voltage and Reactive Power

Questions regarding the creation of a power district two-level control system for voltage and reactive power overflows are examined. Objectives and tasks are designated for the control system, and resolution of this makes it possible to increase the power efficiency of the power grid company. A methodology for controlling equipment at the substation (SS) level is briefly described, as well as expansion and test results on a dynamic model of the power grid.

42 ENGINEERING↗
DOE OSTI2018

Comparing the Effects of Nb, Pb, Y, and La Replacement on the Structural, Electrical, and Magnetic Characteristics of Bi-Based Superconductors

In this study, the effects of Pb, Nb, La, and Y replacements were investigated on Bi-based superconducting materials. In preparing the samples, we used a method called solid-state reaction method. The patterns of the X-ray diffraction of all samples indicated presence of Bi-2212 and Bi-2223 phases. The results obtained from XRD revealed that with increase of the melting point of substation elements, the Bi-2223 phase decreased while the Bi-2212 phase and impurity phases of samples grew. From the electrical resistivity measurements using the four-probe method, it was found that sample A with Pb and sample B with La replacements had the maximum and minimum critical temperatures of 111.4 and 81.6 K, respectively. Based on hysteresis loop (M–H) measurement using Bean’s model, estimation of critical current density (J{sub c}) showed that sample A with Pb and sample B with La substitution had the maximum and minimum values respectively. These results may be due to the melting point of these elements with values of 888, 1512, 2315, and 2425 {sup ∘}C for PbO, Nb{sub 2}O{sub 5}, La{sub 2}O{sub 3}, and Y{sub 2}O{sub 3}, respectively. These elements were replaced by Bi{sub 2}O{sub 3} with a melting point of 817 {sup ∘} C. Further, the samples were prepared at the temperature of 845 {sup ∘}C. It seems at this temperature, these elements not only dissolve within the main matrix and participate in the formation of the Bi-2212 phase during the sintering process but they also participate in the development of the variety of the impurity phases as confirmed by XRD results.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Quantum computing based hybrid deep learning for fault diagnosis in electrical power systems

Quantum computing (QC) and deep learning have shown promise of supporting transformative advances and have recently gained popularity in a wide range of areas. Here, this paper proposes a hybrid QC-based deep learning framework for fault diagnosis of electrical power systems that combine the feature extraction capabilities of conditional restricted Boltzmann machine with an efficient classification of deep networks. Computational challenges stemming from the complexities of such deep learning models are overcome by QC-based training methodologies that effectively leverage the complementary strengths of quantum assisted learning and classical training techniques. The proposed hybrid QC-based deep learning framework is tested on a simulated electrical power system with 30 buses and wide variations of substation and transmission line faults, to demonstrate the framework’s applicability, efficiency, and generalization capabilities. High computational efficiency is enjoyed by the proposed hybrid approach in terms of computational effort required and quality of diagnosis performance over classical training methods. In addition, superior and reliable fault diagnosis performance with faster response time is achieved over state-of-the-art pattern recognition methods based on artificial neural networks (ANN) and decision trees (DT).

42 ENGINEERING↗
DOE OSTI2020

Spatio-temporal impacts of a utility’s efficiency portfolio on the distribution grid

Energy Efficiency has historically focused on delivering savings to offset growth in energy supply. Today’s growing emphasis on decarbonization of the energy supply is driving renewables adoption and increased interest in electrification. As a result, energy efficiency is being assessed not just in its ability to offset load growth, but also for its ability to alleviate location-specific constraints on transmission and distribution infrastructure. This work demonstrates that advanced measurement and verification modeling techniques can be used to estimate the spatio-temporal grid impact of a portfolio of energy efficiency programs. It extends measurement-based methods to an entire Demand Side Management portfolio and uses a single model to predict annual as well as seasonal building energy use with near-zero bias. In addition, new metrics are introduced to assess grid level impacts of energy efficiency. The results show that the efficiency program portfolio delivers savings of over 12% at the territory-wide proxy level, with substation and feeder level savings ranging from 0.4% to 26%, and ~5%-42% respectively. Overall, these savings impacted 1.0%–1.4% of the energy used at these locations in the grid. This work provides a methodology with potential to connect efficiency with distribution planning, carrying implications for non-wires alternatives and targeted delivery of efficiency programs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Impact analysis of DERs on bulk power system stability through the parameterization of aggregated DER_a model for real feeders

With an ever increasing percentage of distributed energy resources (DERs) connected behind the meter in the distribution system, it is becoming increasingly important to equip transmission planners with the visibility of DER dynamic performance in distribution system. Not having visibility of the disconnection of DERs with the occurrence of transmission events, could result in an erroneous view of the stability of bulk power system. Here, in this paper, a parameterized aggregated model (DER_a) serves as a representation of the distribution-level dynamics of real residential feeders, which is used for analysis of bulk power system stability. The parameters are obtained by executing dynamic Monte Carlo simulations. Faults are then induced at the substation level causing the DERs to trip which subsequently enables the parameterization of the low and high voltage breakpoints (v l0 , v l1 , v h0 , and v h1 ) of the DER_a model’s partial voltage trip block. These parameters are then utilized to study the effectiveness of the DER_a model to represent the behavior of the aggregated DERs’ response and their impact on the bulk power system. The case study shows the ability of the positive-sequence DER_a model to provide an accurate estimation of DERs that are susceptible to trip due to 3-$\phi$ and 1-$\phi$ faults of transmission.

14 SOLAR ENERGY↗
DOE OSTI2026

Exploring Wildfire & Energy data toward State Prioritization Index (WESPI)

Energy infrastructure can both induce and suffer risks from wildfires ranging from direct damage to energy assets such as substations and power lines to Public Safety Power Shutoffs. Recent wildfire events underscore the need for data-driven approaches that help states and utilities proactively plan for wildfire risk. Existing national tools such as Federal Emergency Management Agency (FEMA)’s National Risk Index (NRI) are valuable for community hazard planning. However, they are less suited for energy infrastructure, as they emphasize population and building exposure rather than system vulnerabilities. In this paper, we explore relationships between energy and wildfire data and present a Wildfire-Energy State Prioritization Index (WESPI). Our methodology combines data from the US Forest Service’s Fire Simulation (FSIM) dataset with energy resilience metrics, historical fire incidents, and geospatial data on transmission lines and fire stations. Correlation analyses suggest that FSIM burn probability is more strongly associated with power outage metrics (ρ = 0.32) than NRI wildfire frequency, and counties with a greater density of fire stations experience more frequent, but less intense wildfires. We further leverage data for burn probability, transmission line density, and fire station density to develop a Wildfire-Energy State Prioritization Index (WESPI) to highlight counties where wildfire hazard, infrastructure exposure, and limited suppression capacity converge. The index provides a consistent, scalable framework for state energy offices and utilities to screen counties for vegetation management, optimization of outage management system deployment, and to inform wildfire mitigation plans.

Critical infrastructure↗
DOE OSTI2016

Structural, magnetic, and Mössbauer spectroscopy of Cu substituted M-type hexaferrites

Highlights: • Single BaM hexaferrite structural phases with Cu substations were prepared. • The magnetocrystalline anisotropy decreased with Cu substitution. • The coercivity was significantly modified while the magnetization remained high. • Hexaferrites with 0.2–0.4 Cu possess properties suitable for magnetic recording. • Ionic distributions from structural refinement agreed with Mössbauer spectroscopy. - Abstract: BaFe{sub 12−x}Cu{sub x}O{sub 19} hexaferrites were prepared using ball milling and sintering at 1100 °C. Refinement of the X-ray diffraction patterns was carried out to determine the structural parameters and the ionic distribution over the crystallographic sites. The preferential site occupation and valence state of Cu was consistent with the results obtained from the analysis of Mössbauer spectra. Further, the magnetic parameters of the samples were discussed in light of the structural and Mössbauer analyses. The magnetic phase transition temperature was found to decrease with the level of Cu substitution, in accordance with the reduction of the superexchange interactions. Further, the magnetic softening of the hexaferrite and the significant reduction in magnetocrystalline anisotropy with Cu substitution was consistent with the ionic distribution in the lattice. This study clearly demonstrated the feasibility of using a simple method to fabricate hexaferrites with a modified coercivity, while maintain the saturation magnetization high enough for practical applications.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Application of active quenching of second generation wire for current limiting

Superconducting fault current limiters (SFCL's) are increasingly implemented in the power grid as a protection of substation equipment from fault currents. Resistive SFCL's are compact and light, however they are passively triggered and thus may not be sufficiently sensitive to respond to faults in the distribution grid. Here, we explore the prospect of adding an active management feature to a traditional resistive SFCL. A flexible radio-frequency coil, which is an integral part of the switching structure, acts as a triggering device. We show that the application of a short, 10 ms, burst of ac magnetic field during the fault triggers a uniform quench of the wire and significantly reduces the reaction time of the wire at low currents. The ac field burst generates a high density of normal zones, which merge into a continuous resistive region at a rate much faster than that of sparse normal zones created by the transport current alone.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2014

Structural Basis for Catalytic Activation of a Serine Recombinase

Sin resolvase is a site-specific serine recombinase that is normally controlled by a complex regulatory mechanism. A single mutation, Q115R, allows the enzyme to bypass the entire regulatory apparatus, such that no accessory proteins or DNA sites are required. Here, we present a 1.86 {angstrom} crystal structure of the Sin Q115R catalytic domain, in a tetrameric arrangement stabilized by an interaction between Arg115 residues on neighboring subunits. The subunits have undergone significant conformational changes from the inactive dimeric state previously reported. The structure provides a new high-resolution view of a serine recombinase active site that is apparently fully assembled, suggesting roles for the conserved active site residues. The structure also suggests how the dimer-tetramer transition is coupled to assembly of the active site. The tetramer is captured in a different rotational substate than that seen in previous hyperactive serine recombinase structures, and unbroken crossover site DNA can be readily modeled into its active sites.

59 BASIC BIOLOGICAL SCIENCES↗