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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Characterization and Analysis of the Energy-Reporting Accuracy of Connected Devices

Emerging energy-efficient building systems increasingly exhibit greater functionality, often requiring multiple operating modes (e.g. white-tunability for lighting products and data traffic for devices with networked, integrated sensors). This increased functionality makes energy consumption estimates more complex. Given that these functions consume energy, the energy performance of such building systems is dependent on what operating modes they use and how much time they spend in each mode. Devices and systems that can report their own energy consumption mitigate this energy-performance uncertainty. This study explores the energy-reporting accuracy of market-available connected electrical outlets. The study considers two residential-market products (five units each, one outlet per unit) and three commercial-market products (two units each, 18 to 24 outlets per unit) with the ability to report power drawn and/or energy consumed by devices connected to their receptacles. The products were purchased through typical market channels. Pacific Northwest National Laboratory (PNNL) conducted testing in December 2018 at its Connected Lighting Test Bed (CLTB), using a custom-developed test setup and method adapted from industry standards. The setup collected energy-consumption data reported by the outlet devices under test (DUTs) at one-minute intervals and compared that data with measurements taken by a reference meter over a range of test conditions. The residential products reported power draw but not interval or cumulative energy consumption. The commercial products reported both power draw and cumulative energy consumption. Relative reporting error (RRE) was calculated for all measurements, and analysis of the results revealed variations across devices and test conditions. The total number of measurements (50 for each residential product, 60 for each commercial product) offers an appreciable comparison of performance at the make/model level. The average RRE of the residential products derived from reported power draw was -0.02% and -1.20%. The average RRE for two of the three the commercial products derived from reported power draw was worse than those of the residential products (-2.40%, -2.72%, -0.36%). The internal integration of power over time, used to calculate cumulative energy consumption, typically occurs at current and voltage sampling rates much higher than once per minute. This suggests that the average commercial-product RRE derived from reported energy consumption should be very consistent and better than performance based on reported power draw. However, the RRE derived from reported energy consumption varied significantly across the three makes of commercial-market products and was uniformly less accurate than performance based on reported power draw. Subsequent analysis identified a number of root causes for this decrease in performance, most of which were related to reporting resolution. The goals of this study are to generate awareness of building systems capable of reporting their own energy consumption, further interest in the value of energy data for a variety of uses, draw attention to how the accuracy of reported metrics can be characterized, and quantify the performance variation found in marketavailable products. The results of this study and subsequent related work may be relevant to stakeholders in industry-specification and standards-development organizations. The methods this study employs could inform test and measurement procedures and performance classifications for connected outlets, lighting products, and other building systems capable of reporting their own energy consumption. The study concludes with stakeholder recommendations, including the following: • Energy-reporting device and system manufacturers developing products that report energy consumption should characterize the accuracy of reported metrics using a reference meter calibrated by an independent laboratory that was accredited by an ILAC MRA signatory (and whose scope of accreditation explicitly covers energy measurement), and should include this information on product data sheets. • Standards and specification development organizations should develop application-specific performance classifications that end users can understand and relate to their energy-data use needs (e.g., 2% accuracy class for utility streetlight energy billing needs, or 10% accuracy class for ESCO performance verification needs). • Current or potential owners, operators, and specifiers of energy-reporting building systems should rigorously analyze the dependency of current and planned energy-data use cases on accuracy, noting in particular the dependence (or lack thereof) on relative vs. absolute accuracy, and on trueness vs. precision (i.e., repeatability), and should communicate use-case needs to industry standards and specification organizations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Barriers to Balcony Solar and Plug-In Distributed Energy Resources in the United States

Plug-in distributed energy resources (DERs), such as balcony solar, backfeed power to the home through a standard plug. These systems may represent the future of residential solar and storage, particularly as recent net metering policies have reduced the economic appeal of rooftop solar. While plug-in DERs have seen widespread success in Europe, their U.S. market is stagnant. This paper reviews the technical, interconnection, and regulatory barriers hindering the adoption of plug-in DERs. We first discuss the technical barriers, which include touch safety, breaker masking, and bidirectional ground-fault circuit interrupters. We then examine utility perspectives on plug-in DERs and strategies for navigating interconnection challenges. Finally, we discuss regulatory hurdles related to UL standards and the National Electrical Code.

Gerber, Daniel L. (ORCID:0000000219720679)↗
DOE OSTI2026

Advancing Concentrating Solar Thermal Modeling Using System Advisor Model (SAM)

Concentrating solar thermal (CST) technologies play a critical role in enabling dispatchable power and high-temperature industrial heat applications. Accurate and flexible modeling tools are essential for evaluating system performance, guiding technology research and development, and informing investment decisions. The National Laboratory of the Rockies's System Advisor Model (SAM) is a widely used techno-economic simulation platform for CST systems, providing detailed performance and financial modeling capabilities for multiple CST system configurations. SAM integrates physics-based performance models with financial analysis to simulate the behavior of complex energy systems under realistic operating conditions. For CST technologies (including tower, parabolic trough, and linear Fresnel), SAM enables hourly simulations using site-specific weather data that ensure feasible operating conditions and convergence of mass and energy between core system components (i.e., solar field, receiver, thermal energy storage, and power cycle). These capabilities allow researchers and developers to evaluate annual energy production, capacity factors, levelized cost of energy (LCOE), and system dispatch strategies. A key advantage of SAM lies in its flexibility for parametric analysis and large-scale computational studies. Users can vary system design parameters such as heliostat field layout, receiver dimensions, thermal energy storage capacity, power block sizing, and installation cost assumptions to investigate their impact on system performance and financial metrics. When combined with automated scripting through LK, SDKTool, or Python interfaces, SAM enables high-throughput simulation workflows that support sensitivity analysis, technology benchmarking, and optimization studies. These approaches are particularly valuable for next-generation CST concepts, where design spaces are large and system interactions are complex. Another important capability of SAM is its support for dispatch optimization and thermal energy storage modeling, which are central to the value proposition of CST technologies. The ability to simulate integrated storage and flexible power generation allows researchers to explore strategies that maximize grid value, improve capacity utilization, and enhance integration with variable resources such as photovoltaic and wind generation. This poster will present an overview of SAM's thermal system modeling capabilities including concentrating solar. Additionally, we will highlight new feature developments including: 1) implementing Google's OR-Tools optimization platform for faster and more robust dispatch optimization, 2) developing a new power load following controller for modeling behind-the-meter applications, 3) enabling direct modeling of CSP-PV hybrid systems with the inclusion of battery storage, and 4) developing a multi-receiver falling particle Gen3 system model.

14 SOLAR ENERGY↗
DOE OSTI2023

Improving the Long-term Cycle Performance of xLi 2 MnO 3 ·(1-x)LiMeO 2 /Li 4 Ti 5 O 12 Cells via Prelithiation and Electrolyte Engineering

Toward the development of high energy density and long lifetime batteries for behind-the-meter storage (BTMS) applications, Li- and Mn-rich layered oxide cathode (xLi 2 MnO 3 ·(1-x)LiMeO 2 , Me = Ni, Mn, and etc., LMR-NM) and Li 4 Ti 5 O 12 (LTO) anode system was examined. To mitigate the major degradation mechanisms at each electrode (i.e., loss of Li inventory (LLI) at the anode and transition metal dissolution and oxygen release at the cathode), two approaches were taken—prelithiating the LTO electrode and varying the electrolyte solvent compositions. The effect of prelithiation and electrolyte engineering on the long-term cycle performance of LMR-NM/LTO cells were systematically evaluated via electrochemical analyses and post-mortem characterizations. By using a prelithiated LTO anode and supplying additional Li to the system, the capacity retention of LMR-NM/LTO system was improved. The degree of enhancement was dependent on the types of electrolytes used, as their decomposition products determined the level of LLI. With increased capacity retention, however, the cathode was utilized to a greater extent, resulting in more severe loss of the cathode active material. Thus, all degradation mechanisms should be considered comprehensively when designing high performance LMR-NM/LTO cells to account for their complex interplay.

25 ENERGY STORAGE↗
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 OSTI2025

Application of automated iterative target detection for standoff hyperspectral imaging

The utility of hyperspectral imaging (HSI) has been well established for a wide array of applications but has generated a need for automated screening of high volumes of large HSI cubes. We report two important automated algorithms for more efficient standoff processing: atmospheric correction and target detection. The atmospheric correction method is based on a fast asymmetric least squares approach that is applied on a pixel-by-pixel basis. Here, the correction can be applied to entire images without manually identifying regions of interest and utilizes only in-scene information, no ancillary modeling of the atmosphere is required. An iterative target detection approach is also introduced which demonstrates faster speeds relative to moving window approaches. The target detection algorithm classifies each pixel as true target detections, near target detections, clutter, and no-calls. The algorithms were tested on forty images of twenty-two solid mineral targets placed at a 14-meter standoff distance allowing general observations on expected detection performance for a variety of minerals. In addition to identifying anomalous pixels, the inclusion of “no-calls” reduced the number of false detections significantly.

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Advanced Semi-Supervised Learning with Uncertainty Estimation for Phase Identification in Distribution Systems

The integration of advanced metering infrastructure (AMI) into power distribution networks generates valuable data for tasks such as phase identification; however, the limited and unreliable availability of labeled data in the form of customer phase connectivity presents challenges. To address this issue, we propose a semi-supervised learning (SSL) framework that effectively leverages labeled and unlabeled data. Our approach incorporates self-training, label spreading, and Bayesian neural networks (BNNs) to enhance phase identification with AMI data. Our method uses an ensemble of multilayer perceptron classifiers in a self-training setup, iteratively adding high-confidence pseudo-labels to improve robustness. We also apply label spread to propagate labels based on data similarity, which enhances generalization across diverse distributions. In addition, we employ a BNNs with uncertainty estimation, boosting confidence in predictions and reducing phase identification errors. In our case study, we achieved approximately 98% +/- 0.08 accuracy with uncertainty using minimal and unreliable labeled data from a real U.S. utility, Duquesne Light Company. Our SSL approach, combined with uncertainty estimation, provides an efficient solution for phase identification in AMI data, ultimately improving the reliability of smart grid applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Smart Meter Data: A Gateway for Reducing Solar Soft Costs with Model-Free Hosting Capacity Maps

Public-facing solar hosting capacity (HC) maps, which show the maximum amount of solar energy that can be installed at a location without adverse effects, have proven to be a key driver of solar soft cost reductions through a variety of pathways (e.g., streamlining interconnection, siting, and customer acquisition processes). However, current methods for generating HC maps require detailed grid models and time-consuming simulations that limit both their accuracy and scalability—today, only a handful out of almost 2,000 utilities provide these maps. This project developed and validated data-driven algorithms for calculating solar HC using data from AMI without the need of detailed grid models or simulations. The algorithms were validated on utility datasets and incorporated as an application into NRECA’s Open Modeling Framework (OMF.coop) for the over 260 coops and vendors throughout the US to use. The OMF is free and open-source for everyone.

14 SOLAR ENERGY↗
DOE OSTI2026

Advanced Semi-Supervised Learning With Uncertainty Estimation for Phase Identification in Distribution Systems

The integration of advanced metering infrastructure (AMI) into power distribution networks generates valuable data for tasks such as phase identification; however, the limited and unreliable availability of labeled data in the form of customer phase connectivity presents challenges. To address this issue, we propose a semi-supervised learning (SSL) framework that effectively leverages labeled and unlabeled data. Our approach incorporates self-training, label spreading, and Bayesian neural networks (BNNs) to enhance phase identification with AMI data. Our method uses an ensemble of multilayer perceptron classifiers in a self-training setup, iteratively adding high-confidence pseudo-labels to improve robustness. We also apply label spread to propagate labels based on data similarity, which enhances generalization across diverse distributions. In addition, we employ a BNNs with uncertainty estimation, boosting confidence in predictions and reducing phase identification errors. In our case study, we achieved approximately 98% +/- 0.08 accuracy with uncertainty using minimal and unreliable labeled data from a real U.S. utility, Duquesne Light Company. Our SSL approach, combined with uncertainty estimation, provides an efficient solution for phase identification in AMI data, ultimately improving the reliability of smart grid applications.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Low-Cost Heliostat for High-Flux Small-Area Receivers (Final Technical Report)

This project analyzed a two-stage heliostat concept consisting of a tracking stage and a concentrating stage. The tracking stage uses mirrors mounted on a common drive that move to track the sun. The concentrating stage consists of stationary mirrors that each have a unique angle to direct rays towards a small-area, high-flux, point-focused receiver. By splitting the collection and concentrating process into two stages, multiple small, inexpensive mirrors can share a structure and be controlled by a single drive in the tracking stage. The project effort developed modeling techniques that were specifically relevant to this two-stage heliostat concept. Both field-level and unit-level models were developed. The field-level model does not explicitly consider unit-level losses which are predicted by the unit-level model and then integrated into the field-level model through a correlation referred to as an efficiency modifier. This approach is referred to as the two-model approach; the development and demonstration of this two-model approach for a multi-stage heliostat technology is a key outcome of this work. The field-level model is used to design a field that hits a specific design day power given a set of heliostat design parameters. An oversized field is simulated and then heliostat units are removed based on their annual energy production in order to generate the highest performing field. The field reduction procedure fits a smooth curve fit to annual energy production as a function of position in the field which has the effect of reducing the noise that is otherwise caused by the Monte Carlo ray tracing technique. This approach is referred to as the annual energy fit method and substantially reduces computational run time for a given field level modeling accuracy. The annual energy fit approach enables the selection of a properly sized, high-performing field using orders of magnitude fewer rays than would otherwise be possible and the development of this approach is a second key outcome of this work. These models are used within a genetic optimization algorithm in order to optimize the geometric parameters associated with a heliostat in order to achieve the lowest cost per unit of collected design day power. The cost modeling that underlies the optimization is a simple, scaling type analysis backed up by a much more detailed Design for Manufacture and Assembly (DFMA) analysis. Although the figure of merit used for optimization was not cost per mirror area, this metric is reasonable to use as a means of comparison. The optimally designed 500 kW design has a tracking mirror specific cost of $181.85/m 2 , which is significantly larger than the target value and also larger than the current state of the art. The cost of the torque-tube type linkages contributed substantially to the overall cost. Based on this observation, potentially attractive alternative design configuration utilizing a capstan type actuation system should be investigated. Finally, NREL compared the performance of the two-stage heliostat to the performance of a focused and different sized flat conventional heliostats and showed that, as expected, additional losses versus the convention heliostat caused by a worse cosine efficiency, two stages of reflection, and interstage interactions. The two-stage heliostat requires around 75% more reflective area than a flat 1x1 meter conventional heliostat (similar to a focused heliostat) and 40% more than a flat 2x2 meter conventional heliostat.

14 SOLAR ENERGY↗
DOE OSTI2021

Wind Turbine Blade Finishing Automation: Robotic Toolpath Generation

Wind turbine blades are now over 100 meters long and can reach heights of several meters while in the finishing area of the factory. Because of this, automation should be used to lower the manufacturing cost and make the process safer for blade manufacturing technicians. This session will present a novel method that generates a six degree of freedom robotic toolpath with 3D cameras for the finishing of wind turbine blades to drive down the levelized cost and make wind energy even more competitive in the utility scale energy generation industry.

3d imaging↗
DOE OSTI2023

Designing Li 4 Ti 5 O 12 /LiMn 2 O 4 Cells: Negative-to-Positive Ratio and Electrolyte

Li 4 Ti 5 O12/LiMn2O 4 (LTO/LMO) system is a promising candidate for behind-the-meter storage (BTMS) applications due to its critical-material-free chemistry exhibiting good safety and long lifetime. In this paper we design LTO/LMO cells to mitigate their major degradation mechanism, loss of Li inventory, and improve their long-term cyclability. First, LMO electrodes with different loadings (2.61, 3.29, and 4.26 mAh cm -2 ) are paired with an LTO electrode (3.35 mAh cm -2 ) to create varying negative-to-positive ratios (N/P>1, =1, and <1). Additionally, conventional ethylene carbonate (EC)/ethyl methyl carbonate (EMC) mixture electrolyte and safety enhanced EC-only electrolyte are examined. We show that storing additional Li inventory in the cathode (i.e., using a thicker electrode and having N/P<1) is a convenient method to enhance the capacity retention of LTO/LMO cells, but only if the electrode utilization is not limited by the Li + ion transport. For systems that suffer from limited transport properties, prelithiating the anode will be more effective since LTO (~165 mAh g -1 LTO ) can store the same amount of capacity using less material compared to LMO (~100 mAh g -1 LMO ). In this work, we demonstrate how the electrolyte properties and the electrode thickness of LTO/LMO cells can be designed to enhance their performance.

25 ENERGY STORAGE↗
DOE OSTI2025

Deep Factorization Machine Learning for Disaggregation of Transmission Load Profiles with High Penetration of Behind-The-Meter Solar

The ever-growing integration of distributed energy resources (DERs), especially behind-the-meter (BTM) solar generations, poses imperative operational challenges to system operators such as regional transmission organizations (RTOs). It is important for RTOs to effectively and accurately extract actual load profiles at the transmission level for a single node with significant BTM solar injection. This paper first illustrates the necessity of disaggregating the daily actual load profile of a single node. Furthermore, by segmenting nodes with selected timeseries features, nodes with significant BTM solar generation are identified. Lastly, a bi-level framework is proposed, comprising reference node disaggregation and DeepFM nodal disaggregation, aimed at disaggregating the nodal load profiles from which system operators require more information. By adopting a hybrid Deep Factorization Machine (DeepFM) model, the model achieve accurate results by extracting both linear and nonlinear relations between nodes in the same region and the zonal load and nodal load profile. To overcome the lack of ground truth, this paper segments the load profile into daytime, nighttime, and zero-crossing points and utilizes the latter two for evaluation purposes. The proposed disaggregation procedure is validated using real world, minute-level, normalized, and anonymized nodal data in the PJM service territory.

42 ENGINEERING↗
DOE OSTI2020

Opportunities to Implement Solutions to Achieve Remedial Action Objectives in Consideration of Stakeholder Interests - 20365

A case study in the implementation of a soils excavation and removal project conducted at a Formerly Utilized Sites Remedial Action Program (FUSRAP) Maywood Superfund Site (FMSS) vicinity property; an active commercial business, in a densely populated area, with significant operational, technical and, logistical constraints that were expected to limit areas that could be remediated. The United States Army Corps of Engineers-led (USACE) team successfully navigated complex overlapping stakeholder interests to achieve a more efficient and complete removal of contaminated soils and debris while minimizing unnecessary excess costs to the Government. This paper centers on FUSRAP activities at the FMSS vicinity property located at 149-151 Maywood Avenue, Maywood, Bergen County, New Jersey. For most of its FUSRAP history, this ∼109,000 square meter (27-acre) property housed a now-demolished ∼26,000 square meter (6.5-acre) warehouse operated by Sears Logistics Services, a unit of the Sears Roebuck Company (Figure 2). Sears ended its property lease and vacated the warehouse in December 2016. Given that long history and for the purposes of this paper, the property will be referred to as the 'Sears property' or simply 'the property.' The Sears property is approximately 109,000 square meters (27-acres) and is currently zoned for commercial use. The property is bound to the north and northwest by 100 West Hunter Avenue (the Stepan Company), to the northeast by 205 Maywood Avenue, to the east by Maywood Avenue, to the south by 23 West Howcroft Road, and to the west by businesses on NJ Route 17 and the NJ Route 17 roadway. Until December 2016, the property housed a warehouse and distribution center operated by Sears Logistical Services. On-site structures were demolished by the property owner in 2017. The warehouse covered the north section of the property along the Stepan Company property line. A railroad spur from the adjacent property now known as the Maywood Interim Storage Site (MISS) ended at the northeast corner of the warehouse. Wetlands were located east of the warehouse; the rest of the property was covered with paved parking lots and grassed areas. During remediation at the property, opportunities frequently arose where the project team was able to coordinate effectively with stakeholders to sequence remediation activities to facilitate removal of otherwise inaccessible soils and identify opportunities for materials reuse when supported by residual radiological and chemical levels. Some specific opportunities include: - remediating individual truck loading dock bays to maintain tenant operations; - working along a busy highway and in a utility corridor containing a 30-inch high pressure gas main; - remediating Lodi Brook and associated wetlands requiring bypass pumping and other diversionary structures to maintain local community stormwater drainage; - protecting during remediation and supporting access to facilitate tenant/owner maintenance of critical fire protection and water supply system service lines buried in contaminated soils and necessary for safe warehouse operations; and - coordinating with stakeholders to ensure non-radiological contaminants of concern for the site (unaffiliated with FUSRAP) were addressed by the responsible party in a manner that maximized benefit to all parties while supporting an efficient overall site remediation program. Once the property was vacant and the warehouse structure and radiologically non-impacted above-grade structures were demolished, the project identified an opportunity to significantly reduce the volume of waste associated with the foundation of the former warehouse, a foundation suspected of being partially constructed in radiologically contaminated soils. The project developed and implemented supplemental radiological verification survey and sampling strategies based on radiological cross-contamination risk potential with process flow-charts and screening-level based decision points; a program that classified saw-cut sections of concrete based on observed residual surface radioactivity conditions using a combination of gamma sensitive sodium-iodide scans and beta sensitive Geiger-Muller direct measurements. The proposed approach was reviewed with stakeholders with feedback, including consideration of applicable State of New Jersey Site Remediation Program criteria and guidance before implementation. Once classified, additional sampling was performed at frequencies driven by screening. The sampling methods, stockpile sampling frequencies, criteria and, approach to data evaluation were developed in consideration of existing site cleanup standards, regional background ranges, State of New Jersey radiological remediation program guidance, and specific stakeholder input With the property remediation and survey efforts nearly completed, it is relevant to examine retrospectively the objectives, assumptions and limitations in the remedial design (i.e., what was planned) versus what was able to be accomplished through effective teaming. Benefits to other environmental remediation site programs include better understanding of how to work effectively with stakeholders to achieve win-win outcomes, and approaches to site remediation, waste minimization and materials reuse that were successful in their overall outcomes. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Modeling occupancy-driven building loads for large and diversified building stocks through the use of parametric schedules

Building energy modeling provides a fundamental tool to assess the potential for energy efficiency to contribute to reducing world energy consumption and global emissions. Occupancy-related operations are a key source of uncertainty for building energy analysis, particularly for aggregated building stocks. At a district or city level, it is critical to estimate aggregated power load profiles for sizing power grid infrastructure, power plant capacity allocation, and energy efficiency measures. The stochastic nature of behavior-related operations complicates the creation of models that accurately capture building load profiles for entire building stocks. This research introduces a new methodology called parametric schedules to model occupancy-driven schedules for large and diverse building stocks. In contrast to computationally expensive methodologies proposed in the literature, our work does not use a recursive time-consuming step. Occupancy is estimated by the extrapolation of operation times directly from metered electric consumption data; occupancy-related schedules are stochastically assigned to each building model, guaranteeing diversity of operation times in the stock. Our procedure has been tested on a large, diversified data-set of 25,000 commercial buildings in Los Angeles, California. It proved to be able to adequately represent the stochastic schedules diversity of the stock and to refine the stock calibration process by 1%. This innovative approach represents a useful asset for utility companies, grid operators, urban planners, and balancing authorities, seeking to improve building stock modeling and better estimate the impact of energy conservation measures. – This work is part of a larger stock modeling tool called ComStock, which is under development by NREL.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Learning Distribution Grid Topologies: A Tutorial

Unveiling feeder topologies from data is of paramount importance to advance situational awareness and proper utilization of smart resources in power distribution grids. This tutorial summarizes, contrasts, and establishes useful links between recent works on topology identification and detection schemes that have been proposed for power distribution grids. The primary focus is to highlight methods that overcome the limited availability of measurement devices in distribution grids, while enhancing topology estimates using conservation laws of power-flow physics and structural properties of feeders. Grid data from phasor measurement units or smart meters can be collected either passively in the traditional way, or actively, upon actuating grid resources and measuring the feeder's voltage response. Analytical claims on feeder identifiability and detectability are reviewed under disparate meter placement scenarios. Such topology learning claims can be attained exactly or approximately so via algorithmic solutions with various levels of computational complexity, ranging from least-squares fits to convex optimization problems, and from polynomial-time searches over graphs to mixed-integer programs. Although the emphasis is on radial single-phase feeders, extensions to meshed and/or multiphase circuits are sometimes possible and discussed. Here this tutorial aspires to provide researchers and engineers with knowledge of the current state-of-the-art in tractable distribution grid learning and insights into future directions of work.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Laser ablation of high-loading Li-ion battery electrodes improves accessible capacity and cycle life for Behind-the-Meter Storage

Adoption of Behind-the-Meter Storage (BTMS) requires design of batteries that enable high safety, long cycle life, and low cost at the system level. Pairing Li 4 Ti 5 O 12 (LTO) with LiMn 2 O 4 (LMO) achieves targets related to safety and cycle life, but these materials' low energy densities contribute to higher cost at the system scale. Increasing electrode loading is a simple approach to improve energy density, but comes with a trade-off in electrode utilization due to long, tortuous Li + diffusion pathways. Here, laser ablation is used to microstructure (pattern) high-loading electrodes to enhance electrode performance through improved Li + diffusion pathways. Four cell types, comprising combinations of standard or patterned anode and cathode, were prepared to evaluate the effects of laser ablation at each electrode. A rate test shows that patterning electrodes enhances active material utilization at ≳1C rates. Patterning the cathode yields the most benefit, as cells with a patterned cathode demonstrate a ~20% higher accessible capacity than those without at 1.4C. Additionally, 1C capacity retention of cells with patterned cathode (91% through 3000 cycles) is significantly improved over cells with only the anode patterned (64%) and non-patterned electrodes (50%). Characterization of post-mortem cells before and after refreshing their electrolyte suggests that 1C capacity retention is improved by mitigation of electrode "dry-out". We hypothesize that the microstructure acts as a reservoir of additional electrolyte, or a path for gas to escape, so that active material remains wetted throughout long-term cycling, and/or the microstructure may reduce localized, gas-forming overpotentials in the high-loading electrode.

25 ENERGY STORAGE↗
DOE OSTI2022

Astrometric gravitational-wave detection via stellar interferometry

Here, we evaluate the potential for gravitational-wave (GW) detection in the frequency band from 10 nHz to 1 μ Hz using extremely high-precision astrometry of a small number of stars. In particular, we argue that nonmagnetic, photometrically stable, hot white dwarfs (WD) located at ~kpc distances may be optimal targets for this approach. Previous studies of astrometric GW detection have focused on the potential for less precise surveys of large numbers of stars; our work provides an alternative optimization approach to this problem. Interesting GW sources in this band are expected at characteristic strains around h c ~10 -17 × (μHz/ $f$ GW ). The astrometric angular precision required to see these sources is Δθ~h c after integrating for a time T~1/$f$GW. We show that jitter in the photometric center of WD of this type due to starspots is bounded to be small enough to permit this high-precision, small-N approach. We discuss possible noise arising from stellar reflex motion induced by orbiting objects and show how it can be mitigated. The only plausible technology able to achieve the requisite astrometric precision is a space-based stellar interferometer. Such a future mission with few-meter-scale collecting dishes and baselines of $\mathscr{O}$(100 km ) is sufficient to achieve the target precision. This collector size is broadly in line with the collectors proposed for some formation-flown, space-based astrometer or optical synthetic-aperture imaging-array concepts proposed for other science reasons. The proposed baseline is however somewhat larger than the km-scale baselines discussed for those concepts, but we see no fundamental technical obstacle to utilizing such baselines. A mission of this type thus also holds the promise of being one of the few ways to access interesting GW sources in this band.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗