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DOE OSTI2020

Continuous-time look-ahead flexible ramp scheduling in real-time operation

This paper develops a novel continuous-time look-ahead optimization model for co-optimizing balancing energy and flexible ramp products in real-time power systems operation. In addition, a continuous-time day-ahead operation model is developed to commit and schedule an adequate subset of generating units for providing balancing energy and ramping requirements in real-time operation. The up and down flexible ramp products are defined as continuous-time decision trajectories that continuously supply the real-time up and down ramping requirements of the system. The deliverability of flexible ramp products is secured through reserving the respective power requirements in generation capacity constraints of generating units. A function space solution method is proposed to reduce the dimensionality of day-ahead and real-time models through projecting them into finite-dimensional function spaces spanned by Bernstein polynomials, where the real-time operation decisions are modeled with a higher accuracy level than day-ahead decisions. Simulations are conducted on the IEEE-RTS system using CAISO load data, and the numerical results showcase the effectiveness of the proposed model in supplying the energy and flexible ramp requirements and avoiding ramping scarcity in the system, while reducing the operation costs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Conditional diffusion machine-learning framework for mapping valence electron distribution from convergent beam electron diffraction

Quantitative convergent beam electron diffraction (CBED) enables determination of aspherical valence electron distributions through refinement of low-order structure factors, which are highly sensitive to chemical bonding and charge density variations. However, conventional quantitative CBED (QCBED) requires solving a highly nonlinear inverse problem with many coupled parameters, and computationally intensive dynamical diffraction calculations, making it time-consuming and difficult to apply to complex systems. More broadly, reconstructing charge density and orbital electron distribution from diffraction data has long been a central challenge in both x-ray and electron crystallography. Here, in this study, we introduce an artificial-intelligence (AI)-based framework that replaces traditional refinement with a data-driven inverse solver. Using a large synthetic CBED dataset generated by Bloch-wave simulations, we train a conditional diffusion model to directly infer crystal structural parameters and multipole density formalism parameters, and hence valence electron distributions, from CBED patterns alone. By learning from forward simulations across realistic parameter space, the model effectively solves the inverse problem. Compared with direct regression approaches, the diffusion-based framework provides posterior parameter distributions for rigorous uncertainty quantification while preserving quantitative fidelity and reducing analysis time by orders of magnitude. By eliminating the need for external single-crystal x-ray diffraction data and complex nonlinear refinement, this approach enables practical, high-throughput, and in situ quantitative CBED, enabling real-time mapping of valence electron distributions and their correlation with functional responses in quantum and energy materials.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2016

Highly Efficient Non-Oxidative Methane Conversion with Continuous Hydrogen Removal

A non-oxidative methane conversion catalytic system has been successfully developed. Ball-milling and annealing above 1973 K are necessary in order to synthesize the unique methane activation catalyst. Characterization and evaluation of catalysts shows that the surface area should be carefully controlled to minimize coke deposition. The influence of temperature, pressure, space velocity and hydrogen concentration on catalytic process was systematically studied. The reaction conditions were optimized to a combination of 1323 K, ambient pressure and a space velocity of 4900 ml/g·h. A process, using 0.5% Fe/SiO 2 catalyst under these conditions, yield a methane conversion of 15.62%, with product distribution of 40.05% C 2 , 26.48% BTX and 10.7% naphthalene and demonstrated stable operation of at least 50 hours. This result meets the milestone in the phase I proposal. A non-oxidative methane catalyst-integrated SOFC reactor was accomplished, using nickel-free cells of both ScSZ oxygen-ion conductor and BZY proton conductor. With in-situ hydrogen removal enabled by SOFC, hydrogen concentration in the reactor was effectively reduced, shifting reaction equilibrium and boosting methane conversion. However, due to the high temperature requirement of this reaction, most available proton-conducting SOFCs become oxygen-ion conducting, leading to side reactions and counteracting the benefits from hydrogen removal. To take advantage of the enhanced oxygen-ion conductance of SOFC at high temperatures, we have also paired the nickel-free SOFCs with high-performance oxidative coupling of methane (OCM) catalysts. The SOFC-OCM tubular membrane reactor, employing a Mn-Ce-Na 2 WO 4 /SiO 2 -based catalyst, demonstrates a remarkable performance of 60.7% methane conversion with 41.6% C 2 + selectivity, 5.8 ethylene-to-ethane ratio and 19.4% ethylene yield. The use of integrated SOFC-OCM reactor enables better hydrocarbon selectivity and higher ethylene-to-ethane ratio, eliminating the need of an expensive air separation unit and preventing the direct co-feed of explosive methane-oxygen mixture. We believe this presents a great promise towards commercialization as an advanced methane conversion technology.

02 PETROLEUM↗

DOE OSTI1991

Nuclear Safety [Vol. 32, No. 4, October-December 1991]

Nuclear Safety is a review journal that covers significant developments in the field of nuclear safety. Its scope includes the analysis and control of hazards associated with nuclear energy, operations involving fissionable materials, and the products of nuclear fission and their effects on the environment. Primary emphasis is on safety in reactor design, construction, and operation; however, the safety aspects of the entire fuel cycle, including fuel fabrication, spent-fuel processing, nuclear waste disposal, handling of radioisotopes, and environmental effects of these operations, are also treated. Table of Contents for this issue follows. GENERAL SAFETY CONSIDERATIONS: 477 Report on the International Symposium on the Use of Probabilistic Safety Assessment for Operational Safety—PSA '91, S. Chakraborty and M. Khatib-Rahbar; 488 Good Relationships Are Pivotal in Nuclear Data Bases, A. S. Heger and B. V. Koen; 494 Technical Note: The Interagency Nuclear Safety Review Panel's Evaluation of the Ulysses Space Mission, J. A. Sholtis, Jr., D. A. Huff, L. B. Gray, N. P. Klug, and R. O. Winchester; ACCIDENT ANALYSIS: 502 The Severe Accident Analysis Program for the Savannah River Nuclear Production Reactors, M. L. Hyder; CONTROL AND INSTRUMENTATION: 511 A Framework for Selecting Suitable Control Technologies for Nuclear Power Plant Systems, R. A. Kisner; DESIGN FEATURES: 521 Containments for Gas-Cooled Power Reactors History and Status, P.W. Williams; ENVIRONMENTAL EFFECTS: 537 Indoor Radon: A Natural Risk, N. H. Harley and J.H. Harley; On the Importance of the Atmospheric Parameters in the Fission Products Distribution of a Severe Reactor Accident, M. C. Barla and A. R. Bayulken; Book Review: Health Effects of Exposure to Low Levels of Ionizing Radiation BEIR V, C. R. Richmond; WASTE AND SPENT FUEL MANAGEMENT: 555 Activities Related to Waste and Spent Fuel Management, M. D. Muhlheim and E. G. Silver OPERATING EXPERIENCES: 567 Effects of Component Aging on the Westhinghouse Control Rod Drive System, K. Sullivan and W. Gunther; 577 Reactor Shutdown Experience, Compiled by J. W. Cletcher, 580 Selected Safety-Related Events, Compiled by G. A. Murphy; 582 Operating U 8 Power Reactors, Compiled by M. D. Muhlheim and E. G. Silver, RECENT DEVELOPMENTS: 596 General Administrative Activities, Compiled by M. D. Muhlheim and E. G. Silver; 610 Reports, Standards, and Safety Guides, D. S. Queener; 614 Proposed Rule Changes as of June 30, 1991; ANNOUNCEMENTS: 520 Workshop on PC PRAISE: A Probabilistic Fracture Mechanics Personal Computer Code for Nuclear Power Plant Piping Reliability Assessment; 536 Fifth Workshop on Nuclear Power Plant Containment Integrity; 624 New OECD "International Information System on Occupational Exposure (ISOE)"; 625 Harvard School of Public Health Announces Short Courses; 625 Eighth Power Plant Dynamics, Control and Testing Symposium; 626 Second Training Course on Off-Site Emergency Planning and Response for Nuclear Accidents; 618 The Authors; 622 Reviewers of Nuclear Safety, Vol 32.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Mapping structural heterogeneity at the nanoscale with scanning nano-structure electron microscopy (SNEM)

Here, in this work, we explore the use of scanning electron diffraction (also known as 4D-STEM) coupled with electron atomic pair distribution function analysis (ePDF) to understand the local order (structure and chemistry) as a function of position in a complex multicomponent system, a hot rolled, Ni-encapsulated, Zr 65 Cu 17.5 Ni 10 Al 7.5 bulk metallic glass (BMG), with a spatial resolution of 3 nm. We show that it is possible to gain insight into the chemistry and chemical clustering/ordering tendency in different regions of the sample, including in the vicinity of nano-scale crystallites that are identified from virtual dark field images and in heavily deformed regions at the edge of the BMG. In addition to simpler analysis, unsupervised machine learning was used to extract partial PDFs from the material, modeled as a quasi-binary alloy, and map them in space. These maps allowed key insights not only into the local average composition, as validated by EELS, but also a unique insight into chemical short-range ordering tendencies in different regions of the sample during formation. The experiments are straightforward and rapid and, unlike spectroscopic measurements, don’t require energy filters on the instrument. We spatially map different quantities of interest (QoI’s), defined as scalars that can be computed directly from positions and widths of ePDF peaks or parameters refined from fits to the patterns. We developed a flexible and rapid data reduction and analysis software framework that allows experimenters to rapidly explore images of the sample on the basis of different QoI’s. The power and flexibility of this approach are explored and described in detail. Because of the fact that we are getting spatially resolved images of the nanoscale structure obtained from ePDFs we call this approach scanning nano-structure electron microscopy (SNEM), and we believe that it will be powerful and useful extension of current 4D-STEM methods.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Elementary framework for cold field emission from quantum-confined, non-planar emitters

For suitably small field emitters, the effects of quantum confinement at the emitter tip may have a significant impact on the emitter performance and total emitted current density (ECD). Since the geometry of a quantum system uniquely determines the magnitude and distribution of its energy levels, a framework for deriving ECD equations from cold field electron emitters of arbitrary geometry and dimensionality is developed. In the interest of obtaining semi-analytical ECD equations, the framework is recast in terms of plane wave solutions to the Schrödinger equation via the use of the Jeffreys-Wentzel-Kramers-Brillouin approximation. To demonstrate the framework's consistency with our previous work and its capabilities in treating emitters with non-planar geometries, ECD equations were derived for the normally unconfined cylindrical nanowire (CNW) and normally confined (NC) CNW emitter geometries. As a function of the emitter radius, the NC CNW emitter ECD profile displayed a strong dependence on the Fermi energy and had an average ECD that exceeded the Fowler-Nordheim equation for typical values of the Fermi energy due to closely spaced, singly degenerate energy levels (excluding electron spin), comparatively large electron supply values, and the lack of a transverse, zero-point energy. Such characteristics suggest that emitters with non-planar geometries may be ideal for emission from both an electron supply and electrostatics perspective.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2017

Computational and Experimental Studies of Mixing of a Light Gas in the ERCOSAM–SAMARA Projects

Severe accidents in NPP with VVER can be accompanied by hydrogen entering the containment space. The aim of the present work is an experimental and computational study of the possibility of hydrogen stratification in the containment in a scenario replicating the sequence of events occurring during a severe accident with hydrogen emission in a light-water reactor taking account of the impact of accident control on the distribution of a light gas. Euratom and the government corporation Rosatom performed the studies as part of two parallel projects – ERCOSAM and SAMARA. The experimental studies show that heat exchangers aand recombiners do bring about complete mixing of the light gas; a sprinkler system affords mixing of the stratified layer. The experimental studies confirm the results of numerical modeling.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2015

Solitary waves in a self-gravitating opposite polarity dust-plasma medium

A more general and realistic dusty plasma model, namely, self-gravitating opposite polarity dust-plasma system (containing inertial positive and negative dust, and inertialess ions and electrons following Maxwellian distribution) is considered. The possibility for the formation of solitary electrostatic and self-gravitational potential structures in such a dust-plasma system is thoroughly examined. The standard reductive perturbation method, which is valid for small but finite amplitude solitary structures, is employed. The parametric regimes for the existence of solitary electrostatic and self-gravitational potential structures, and their basic properties (viz., polarity, amplitude, width, and speed) are found to be significantly modified by the combined effects of positively charged dust component and self-gravitational field. The applications of the present investigation in different space dusty plasma environments and laboratory dusty plasma devices are briefly discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Nonlinear models for coupling the effects of stimulated Raman scattering to inertial confinement fusion codes

Laser plasma instabilities (LPI) reduce driver-target coupling, alter implosion symmetry, and therefore can fundamentally limit fusion performance in inertial confinement fusion (ICF). Developing a predictive modeling capability for LPI effects can critically advance the success of the field. We perform vector particle-in-cell simulations of multi-speckled laser beams undergoing stimulated Raman scattering (SRS) at various densities and intensities relevant to mainly indirectly driven and a subset of parameter space for directly driven ICF systems, focusing on the regimes with intensities above the onset of electron trapping. Based on the wavenumber of the SRS daughter electron plasma wave, we identify several regions with underpinning SRS saturation physics: the electron-trapping dominated region with intermediate kλD values, the strong Landau damping region at larger kλD values, and the region where the Langmuir decay instability arises at lower kλD values. We develop a nonlinear SRS reflectivity model that features the base trapping-dominated scaling of (kλD)−4 and its modifications. Electron trapping deforms the initialized electron distribution functions, and we have developed a new δf-Gaussian-mixture algorithm for an accurate characterization of the trapped hot electron population. With this SRS hot electron description, we construct a nonlinear energy deposition model and a hot electron source model—based on a modified Manley–Rowe relation—suitable for including SRS effects as a sub-grid module in a high-fidelity ICF design code.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Quantitative investigation of the short-range magnetic correlations in the candidate quantum spin liquid NaYbO 2

Here, we present a neutron diffraction study of NaYbO 2 , a candidate quantum spin-liquid (QSL) compound hosting a geometrically frustrated triangular lattice of magnetic Yb 3+ ions. We observe diffuse magnetic scattering that persists to at least 20 K, demonstrating the presence of short-range magnetic correlations in this system up to a relatively high-energy scale. Using a reverse Monte Carlo and magnetic pair distribution function analysis, we confirm the predominant antiferromagnetic nature of these correlations and show that the diffuse scattering data can be well described by noninteracting layers of Heisenberg or XY spins on the triangular lattice. We rule out Ising spins and short-range-ordered stripe or 120° phases as candidate ground states of NaYbO 2 . These results are consistent with a possible QSL ground state in NaYbO 2 and showcase the benefit of a combined reciprocal- and real-space analysis of materials with short-range magnetic correlations.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

A Fast and Accurate Transient Stability Assessment Method Based on Deep Learning: WECC Case Study

Transient stability is one of the critical aspects of power system stability assessment. The increasing integration of inverter-based resources and the retirement of conventional synchronous generators result in the decreasing system inertia and growing complexity of system operating conditions. Using a few selected typical operating conditions cannot guarantee system transient stability in all operating conditions, and the time-domain simulation of all operating conditions requires tremendous time and is often infeasible. This paper proposes a more efficient transient stability assessment method based on deep learning. The binary search method is used to determine the critical clearing time (CCT) in creating training databased by time-domain simulation. This method is fast and accurate with 1 ms resolution. The buses whose CCTs are lower than 200 ms are considered critical buses. Buses close to each other are grouped based on their mutual admittance matrix to reduce the search space of the critical buses. This paper also proposes the generator feature normalization based on the physical model. Case study on the reduced 240-bus WECC system model demonstrates that the proposed method can predict CCT accurately and efficiently.

critical clearing time↗

DOE OSTI2015

SU-E-T-632: Preliminary Study On Treating Nose Skin Using Energy and Intensity Modulated Electron Beams with Monte Carlo Based Dose Calculations

Purpose: Uneven nose surfaces and air cavities underneath and the use of bolus present complexity and dose uncertainty when using a single electron energy beam to plan treatments of nose skin with a pencil beam-based planning system. This work demonstrates more accurate dose calculation and more optimal planning using energy and intensity modulated electron radiotherapy (MERT) delivered with a pMLC. Methods: An in-house developed Monte Carlo (MC)-based dose calculation/optimization planning system was employed for treatment planning. Phase space data (6, 9, 12 and 15 MeV) were used as an input source for MC dose calculations for the linac. To reduce the scatter-caused penumbra, a short SSD (61 cm) was used. Our previous work demonstrates good agreement in percentage depth dose and off-axis dose between calculations and film measurement for various field sizes. A MERT plan was generated for treating the nose skin using a patient geometry and a dose volume histogram (DVH) was obtained. The work also shows the comparison of 2D dose distributions between a clinically used conventional single electron energy plan and the MERT plan. Results: The MERT plan resulted in improved target dose coverage as compared to the conventional plan, which demonstrated a target dose deficit at the field edge. The conventional plan showed higher dose normal tissue irradiation underneath the nose skin while the MERT plan resulted in improved conformity and thus reduces normal tissue dose. Conclusion: This preliminary work illustrates that MC-based MERT planning is a promising technique in treating nose skin, not only providing more accurate dose calculation, but also offering an improved target dose coverage and conformity. In addition, this technique may eliminate the necessity of bolus, which often produces dose delivery uncertainty due to the air gaps that may exist between the bolus and skin.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

DOE OSTI2021

PowerGridworld: A Framework for Multi-Agent Reinforcement Learning in Power Systems [SWR-22-07]

NREL's PowerGridworld provides a modular simulation environment for training heterogenous, grid-aware, multi-agent reinforcement learning (RL) policies at scale. The package enables the user to create component gym environments that can be composed into more complex agents. For example, a grid interactive building environment can be created by composing together component environments each encapsulating the building, PV, and battery physics. These multi-component environments can then be combined into multi-agent simulation where each agent's power consumption/injection becomes an input for solving the optimal power flow on a distribution feeder modeled in OpenDSS. Information from OpenDSS, such as bus voltages and line flows, can be included in the agents' observation spaces to enable grid-aware rewards. The default API for the PowerGridworld simulator conforms to RLLib's MultiAgent API and thus enables distributed training using HPC and cloud resources.

Biagioni, David↗

DOE OSTI2024

Quantum surrogate models for uncertainty quantification

Surrogate models are a critical ingredient to computation-based design and validation of many DOE mission-relevant physical systems. When first-principles computation of properties of a physical systems becomes pro hibitive, surrogate models are the only path towards achieving tasks such as uncertainty quantification (UQ), exploration of design space, and validation of design choices. In this project we have developed and demonstrated a new surro gate modeling paradigm for complex models that is data-driven, non-intrusive, and has the potential to be versatile and equipped with performance guaran tees. This combination of features is absent in existing surrogate modeling tools. The framework we have developed in this project exploits a quantum-classical correspondence to establish a quantum system that mimics the dynamics of the classical Hamiltonian system from which data in the form of temporal snapshots is provided. Since quantum dynamics propagates distributions over observables, the framework is naturally suited to propagation of epistemic uncertainties in the form of distributions over initial state and parametric uncertainties. In this project, we take the first step in establishing this novel framework by deriving a quantization and de-quantization procedure, demonstrating the accuracy of the quantum surrogate models these define using two model systems, and defining the next steps in maturing the framework towards a tool applicable to Sandia mission-relevant problems.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Informing electrification strategies of residential neighborhoods with urban building energy modeling

Electrifying end uses is a key strategy to reducing GHG emissions in buildings. However, it may increase peak electricity demand that triggers the need to upgrade the existing power distribution system, leading to delays in electrification and needs of significant investment. There is also concern that building electrification may cause an increase of energy costs, leading to further energy burden for low-income communities. This study uses the urban scale building modeling tool CityBES to assess the electrification impacts of more than 43,000 residential buildings in a neighborhood of Portland, Oregon, USA. Energy efficiency upgrades were investigated on their potential to mitigate the increase of peak electricity demand and energy burden. Simulation results from the calibrated EnergyPlus models show that electrification with heat pumps for space heating and cooling as well as for domestic water heating can reduce CO2e emissions by 38%, but increase peak electricity demand by about 9% from the baseline building stock. Combining electrification measures and energy efficiency upgrades can reduce CO2e emissions by 48% while reducing peak electricity demand by 6% and saving the median household energy costs by 28%. City and utility decision makers should consider integrating energy efficiency upgrades with electrification measures as an effective residential building electrification strategy, which significantly reduces carbon emissions, caps or even decreases peak demand while reducing energy burden of residents.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2017

Parallel Multivariate Spatio-Temporal Clustering of Large Ecological Datasets on Hybrid Supercomputers

A proliferation of data from vast networks of remote sensing platforms (satellites, unmanned aircraft systems (UAS), airborne etc.), observational facilities (meteorological, eddy covariance etc.), state-of-the-art sensors, and simulation models offer unprecedented opportunities for scientific discovery. Unsupervised classification is a widely applied data mining approach to derive insights from such data. However, classification of very large data sets is a complex computational problem that requires efficient numerical algorithms and implementations on high performance computing (HPC) platforms. Additionally, increasing power, space, cooling and efficiency requirements has led to the deployment of hybrid supercomputing platforms with complex architectures and memory hierarchies like the Titan system at Oak Ridge National Laboratory. The advent of such accelerated computing architectures offers new challenges and opportunities for big data analytics in general and specifically, large scale cluster analysis in our case. Although there is an existing body of work on parallel cluster analysis, those approaches do not fully meet the needs imposed by the nature and size of our large data sets. Moreover, they had scaling limitations and were mostly limited to traditional distributed memory computing platforms. We present a parallel Multivariate Spatio-Temporal Clustering (MSTC) technique based on k-means cluster analysis that can target hybrid supercomputers like Titan. We developed a hybrid MPI, CUDA and OpenACC implementation that can utilize both CPU and GPU resources on computational nodes. We describe performance results on Titan that demonstrate the scalability and efficacy of our approach in processing large ecological data sets.

Sreepathi, Sarat↗

DOE OSTI2026

A Review of Distributed Wind Interconnection Technology and Standards

The objectives of this report are to discuss the uniqueness of power converters in distributed wind (DW), identify challenges in complying with existing standards, prioritize technological innovations to facilitate interconnection of DW energy systems, and, where necessary, propose potential clarifications or revisions to standards. This report evaluates IEEE 1547-2018, IEEE 1547.1-2020, and UL 1741 SB standards and their implications for DW. A standards review and interviews of DW industry stakeholders were conducted to identify challenges in the application of current standards to DW. The study concludes with a combination of recommendations of pathways towards facilitating DW product commercialization and DW interconnection, which draws on participation from multiple stakeholders in the space. These solutions can continue to be explored to improve DW standards compliance, improve the applicability of the standards to DW, reduce certification testing barriers, and ensure the safe and reliable operation of DW energy resources and electric power systems.

17 WIND ENERGY↗

DOE OSTI2019

Embedded Optical Sensing Systems For Distribution Transformer Monitoring

Traditional utility monitoring systems do not provide real-time visibility into the condition of transformers or accurate performance measurements. This has resulted in the use of lagging indicators, such as oil sample analysis, typically requiring expensive field visits, grid outages, and laboratory sample testing. This presentation reviews the use of optical sensing systems for managing transformers and improving grid resiliency and safety. The sensing systems allow direct internal monitoring of critical transformer components. Versatility covering different monitoring parameters of interest in embedded configurations for new transformers and a retrofittable configuration for older transformers is achieved by applying hair-thin multiplexed fiber-optic and other low-profile optical sensors in combination with a high-resolution optical readout and advanced analytics. Under an initiative funded by the DOE Office of Electricity, PARC, GE and Con Edison built, tested, and qualified commercial network transformers with embedded optical sensing systems. The parameters monitored were validated across a range of scenarios with lab instruments typically used for qualification testing. An ongoing field trial to demonstrate the robustness of the technology for remote monitoring through the industrial internet under demanding grid deployment conditions in New York City is showing promise toward scale-up of the technology. This presentation will provide an overview of the typical pain points in managing transformers and parameters for monitoring. It will also cover the requirements for highly constrained installations that need to have a larger capacity and flexible rating but that must fit into a tight space. The unique capabilities of optical sensing systems and a low-cost approach to interpreting the signals from sensors in transformers for predictive maintenance will be covered. The presentation will discuss the compatibility of the sensors in the transformer environment. It will discuss the validation testing per IEEE standards that enabled the solution to be implemented in field-deployable commercial transformers. The initial results from the field deployment and the potential for the technology to provide systematic alerts for unsafe/unexpected events will be discussed. The technology could enable utility professionals to gain information they can use to better plan for maintenance/management, and improve grid performance. This would in turn accommodate DERs and other evolving grid market dynamics.

24 POWER TRANSMISSION AND DISTRIBUTION↗