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DOE OSTI2025

2025 Large Load Literature Review

This literature review catalogs more than 90 publications focused on large loads, and groups the documents and resources thematically into 12 categories, (listed below). The 2026 Large Load Literature Review and Data Sources summary reports are available here: https://emp.lbl.gov/publications/2026-large-load-literature-review -Load forecasting -Data sources -Reliability and resource adequacy -Large load interconnection -Demand flexibility -Generation -Co-location -Data center location/infrastructure -Large load tariffs -Policy options -Maps and tools -Design and operations

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2026

Calibration of urban building energy model using smart meter data for district peak load prediction

Urban building energy modeling (UBEM) is a powerful approach to assessing baseline building energy performance and retrofits with new technologies across building stocks in cities. However, the accuracy of UBEM is often constrained by the limited availability of reliable data about building characteristics and operations, such as envelope efficiency levels, HVAC system performance, and end-use load patterns. Existing research has performed UBEM calibration using annual or monthly energy consumption data, which falls short when higher-resolution time series applications are needed, such as peak load prediction for utility operation planning. This study presents a new framework for calibrating building energy models at urban scale using smart meter data, targeting the accurate prediction of summer peak electricity loads to support robust grid planning. The framework first integrates various data sources to enhance baseline input assumptions for building models, and then calibrates the baseline models through a pattern-matching approach. A case study using CityBES and two years of AMI data from over 9000 residential customers in Portland, Oregon, demonstrated the workflow and its effectiveness. The calibrated models achieved a daily peak load mean absolute percentage error of 2.6 % during the heatwave in the calibration year, and 2.0 % in the validation year using another year of AMI data. Using the calibrated models, we analyzed the demand flexibility potential of the district building stock as an application of UBEM calibration. The findings affirm the appropriate use of UBEM for peak electric load forecasting and demand side management at the utility distribution system level.

AMI data↗

DOE OSTI2025

Networked Microgrid Topology Reconfiguration to Promote Fairness in Proactive Load Shedding

Increasing occurrences of natural disasters and grid emergency events consistently challenge the safe and reliable operations of power systems. During such emergency situations, system operators may proactively shed load to mitigate risks. However, uncoordinated implementation of load shedding may disrupt electricity supply and even lead to cascading failures. Meanwhile, it is crucial to address potential biases affecting different customers when executing load shedding. This paper addresses the dynamic topology reconfiguration problem for networked microgrids with distributed energy resources under emergency conditions. Specifically, we propose a novel rolling-horizon optimization model that integrates fairness-aware constraints into the networked microgrid topology reconfiguration. Unlike existing approaches that focus solely on efficiency or apply fairness considerations in static settings, our method explicitly incorporates temporal fairness constraints to restrict repeated or excessive load curtailment for load blocks. Moreover, the fairness-aware constraints are specifically developed for the context of dynamic networked microgrid topology reconfiguration, and are designed to be convex or amenable to linear reformulations, which offers a more tractable alternative to traditional models with non-convex formulations. Numerical studies on a modified IEEE 13-bus system and a larger-sized SMART-DS networked microgrid system demonstrate the performance of the proposed algorithm towards more fairness-aware networked microgrid topology reconfiguration decision-making.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Slender-body approach for computing second-order wave loads in the frequency domain

This work presents a slender-body approach to evaluate the second-order wave loads acting on a floating structure in the frequency domain. The approach is in the same spirit as the common use of Morison’s equation to approximate the wave loads without solving the radiation/diffraction problem. To do so, we employ Rainey’s equation, which can be seen as an extension of the inertial part of Morison’s equation to include nonlinear effects. We introduce modifications to Rainey’s formulation in order to evaluate wave kinematics at the mean body position instead of the original approach of considering instantaneous displacements. We also propose a simple approximation to partially account for wave scattering effects on the second-order loads based on the analytical solution of a surface-piercing bottom-mounted vertical circular cylinder. Though limited to structures composed of cylinders, this slender-body approach is orders of magnitude faster than computing second-order wave coefficients with a radiation/diffraction code. We implemented this approach for difference-frequency (slow drift) loads in an open-source frequency-domain floating wind turbine model. We present comparisons against results obtained with radiation/diffraction theory for three reference floating wind turbine designs: the OC3-Hywind spar, the OC4-DeepCwind semisubmersible, and the VolturnUS-S semisubmersible. In general, the results show that the proposed slender-body approach with the correction to approximate wave scattering effects provides useful estimations of the difference-frequency wave loads and the resulting motions of the floater.

17 WIND ENERGY↗

DOE OSTI2024

Validation of new and existing methods for time-domain simulations of turbulence and loads

We seek to obtain a second-by-second match between the simulated and measured structural loads of a utility-scale wind turbine. To obtain the one-to-one load simulations, we start with the furthest upstream component of the modeling chain: the turbulent inflow. We consider new and existing methods to generate constrained-turbulence flow fields. The new method is based on large-eddy simulations (LES) and machine learning (ML). The existing methods include Kaimal-based TurbSim and the superstatistical wind field model. The inflow measurements used to constrain these simulations are obtained with a nacelle-mounted scanning lidar. We compare the flow fields for the different inflow simulation approaches and validate their associated load predictions against measurements collected in the Rotor Aero-dynamics, Aeroelastics, and Wake (RAAW) field campaign. We find that the rotor-position control developed for this study is key in enabling the time match between measurements and simulations. When this control approach is used, the load simulation performance tracks with the inflow simulation fidelity, with LES+ML yielding errors ≤ 4% for the damage-equivalent loads of flapwise bending moment, and tower fore-aft bending moments.

17 WIND ENERGY↗

DOE OSTI2026

Load Profiles Data for the EVI-RoadTrip Web Tool

The dataset contains EVI-RoadTrip outputs, minute-by-minute load profiles in kW for each station in the simulation based on assumed utilization and network density. The load profiles are aggregated to lower spatial resolution (e.g., state-level, corridor-level) by summation of all station loads associated with the respective geography. This results in a load profile for each scenario that summarizes the corridor's, state's, or county's load profile in minute-level resolution.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Deep-Learning-Based Multi-Timescale Load Forecasting in Buildings: Opportunities and Challenges from Research to Deployment

Electricity load forecasting for buildings and campuses is becoming increasingly important as the penetration of distributed energy resources (DERs) grows. Efficient operation and dispatch of DERs require reasonably accurate predictions of future energy consumption in order to conduct near-real-time optimized dispatch of on-site generation and storage assets. Electric utilities have traditionally performed load forecasting for load pockets spanning large geographic areas, and therefore, forecasting has not been a common practice by buildings and campus operators. Given the growing trends of research and prototyping in the grid-interactive efficient buildings domain, characteristics beyond simple algorithm forecast accuracy are important in determining the algorithm's true utility for smart buildings. Other characteristics include the overall design of the deployed architecture and the operational efficiency of the forecasting system. In this work, we present a deep-learning-based load forecasting system that predicts the building load at 1-hour intervals for 18 hours in the future. We also discuss challenges associated with the real-time deployment of such systems as well as the research opportunities presented by a fully functional forecasting system that has been developed within the National Renewable Energy Laboratory's Intelligent Campus program.

building load forecasting↗

NASA NTRS2016

Effects of Zoledronate and Mechanical Loading during Simulated Weightlessness on Bone Structure and Mechanical Properties

Space flight modulates bone remodeling to favor bone resorption. Current countermeasures include an anti-resorptive drug class, bisphosphonates (BP), and high-force loading regimens. Does the combination of anti-resorptives and high-force exercise during weightlessness have negative effects on the mechanical and structural properties of bone? In this study, we implemented an integrated model to mimic mechanical strain of exercise via cyclical loading (CL) in mice treated with the BP Zoledronate (ZOL) combined with hindlimb unloading (HU). Our working hypothesis is that CL combined with ZOL in the HU model induces additive structural and mechanical changes. Thirty-two C57BL6 mice (male,16 weeks old, n8group) were exposed to 3 weeks of either HU or normal ambulation (NA). Cohorts of mice received one subcutaneous injection of ZOL (45gkg), or saline vehicle, prior to experiment. The right tibia was axially loaded in vivo, 60xday to 9N in compression, repeated 3xweek during HU. During the application of compression, secant stiffness (SEC), a linear estimate of slope of the force displacement curve from rest (0.5N) to max load (9.0N), was calculated for each cycle once per week. Ex vivo CT was conducted on all subjects. For ex vivo mechanical properties, non-CL left femurs underwent 3-point bending. In the proximal tibial metaphysis, HU decreased, CL increased, and ZOL increased the cancellous bone volume to total volume ratio by -26, +21, and +33, respectively. Similar trends held for trabecular thickness and number. Ex vivo left femur mechanical properties revealed HU decreased stiffness (-37),and ZOL mitigated the HU stiffness losses (+78). Data on the ex vivo Ultimate Force followed similar trends. After 3 weeks, HU decreased in vivo SEC (-16). The combination of CL+HU appeared additive in bone structure and mechanical properties. However, when HU + CL + ZOL were combined, ZOL had no additional effect (p0.05) on in vivo SEC. Structural data followed this trend with ZOL not modulating trabecular thickness in CL + NAHU mice. In summary, our integrated model simulates the combination of weightlessness, exercise-induced mechanical strain, and anti-resorptive treatment that astronauts experience during space missions. Based on these results, we conclude that, at the structural and stiffness level, zoledronate treatment during simulated spaceflight does not impede the skeletal response to axial compression. In contrast to our hypothesis, our data show that zoledronate confers no additional mechanical or structural benefit beyond those gained from cyclical loading.

Mechanical Loading↗

NASA NTRS2017

A Universal Threshold for the Assessment of Load and Output Residuals of Strain-Gage Balance Data

A new universal residual threshold for the detection of load and gage output residual outliers of wind tunnel strain{gage balance data was developed. The threshold works with both the Iterative and Non{Iterative Methods that are used in the aerospace testing community to analyze and process balance data. It also supports all known load and gage output formats that are traditionally used to describe balance data. The threshold's definition is based on an empirical electrical constant. First, the constant is used to construct a threshold for the assessment of gage output residuals. Then, the related threshold for the assessment of load residuals is obtained by multiplying the empirical electrical constant with the sum of the absolute values of all first partial derivatives of a given load component. The empirical constant equals 2.5 microV/V for the assessment of balance calibration or check load data residuals. A value of 0.5 microV/V is recommended for the evaluation of repeat point residuals because, by design, the calculation of these residuals removes errors that are associated with the regression analysis of the data itself. Data from a calibration of a six-component force balance is used to illustrate the application of the new threshold definitions to real{world balance calibration data.

wind tunnel balance↗

NASA NTRSDate not supplied

In-Space Loads Analysis of SLS/Orion

The Space Launch System and Orion spacecraft experience unique load cases during upper stage flight since the Orion must deploy its solar arrays before the upper stage engine fires. The low frequency bending modes of the deployed arrays have the potential to interact with the slosh modes of the upper stage, and with the upper stage flight steady-state accelerations this can induce high loads in the array mechanisms. A time-domain transient response solution is used to evaluate the array mechanism loads, sensitivities are noted, and the final loads are determined to be within the capability of the mechanism. Section loads and accelerations are also recovered and assessed.

SLS↗

NASA NTRSDate not supplied

In-Space Loads Analysis of SLS/Orion

The Space Launch System and Orion spacecraft experience unique load cases during upper stage flight since the Orion must deploy its solar arrays before the upper stage engine fires. The low frequency bending modes of the deployed arrays have the potential to interact with the slosh modes of the upper stage. In combination with the upper stage flight steady-state accelerations this can induce high loads in the array mechanisms. A time-domain transient response solution is used to evaluate the array mechanism loads, sensitivities are noted, and the final loads are determined to be within the capability of the mechanism. Section loads and accelerations are also recovered and assessed.

SLS↗

NASA NTRS2023

The Effects of Off-Axis Loading on the Compression After Impact Strength of Quasi-Isotropic Face Sheet Honeycomb Core Sandwich Structure

This study presents experimental results of compression after impact (CAI) testing of aluminum honeycomb core sandwich structure with face sheets made of co-cured T1100/3960 quasi-isotropic carbon/epoxy when tested at +22.5⁰ and -22.5⁰ with respect to the 0⁰ fibers. In a previous study examining the CAI strengths of honeycomb sandwich structure, it was found that specimens had different CAI strengths, based on a [-45/90/+45/0]s layup, depending on whether they were tested in the 0⁰ direction (face sheet layup of [-45/90/+45/0]s) or 90⁰ direction (face sheet layup of [+45/0/-45/90]s). The CAI strength results showed that the specimens tested in the 90⁰ direction had a 19% drop in CAI strength compared to specimens tested in the 0⁰ direction. This was attributed to the 0⁰ load bearing plies in the 0⁰ direction specimens being “tucked in” at the center of the specimen thus providing more stability against microbuckling. This raised the question as to what CAI strength would specimens tested at +22.5⁰ (face sheet layup of [-22.5/- 67.5/+67.6/+22.5]s) and -22.5⁰ (face sheet layup of [-67.5/+67.5/+22.5/-22.5]s) have compared to specimens tested in the 0⁰ and 90⁰ direction. Results presented in this study show that the specimens loaded at +22.5⁰ and -22.5⁰ have a similar average CAI strength compared to the specimens loaded in the 0⁰ direction. The specimens loaded in the 90⁰ direction exhibit 16% lower average CAI strength. Additional specimens were tested in the +45⁰ direction to put the 0⁰ load bearing fibers on the outside of the specimen to see if this would decrease the strength as has been documented for undamaged strength. These specimens have average CAI strength values between the 0⁰ direction average CAI strength values and the 90⁰ direction average CAI strength values.

Sandwich structure↗

NASA NTRSDate not supplied

Space Launch System Day of Launch Loads for Artemis I

NASA’s Space Launch System (SLS) was successfully launched on November 16, 2022. During the years leading up to the first flight, Artemis I, a DOLILU (Day of Launch I-Load Update) process was developed to design, verify, and upload the first stage flight trajectory on day-of-launch to ensure a safe flight. The evaluation of integrated vehicle loads is a key component of the DOLILU process. The SLS Artemis I DOL loads project has involved methodology development, software development, software testing and certification, operator training, and simulation and launch support. The resulting DOL process successfully calculated loads for all launch opportunities within the window, with the robust nature of the process contributing to all opportunities being go for loads.

SLS↗

NASA NTRSDate not supplied

SLS Payload Launch Loads Analysis Using the NTRC Method

Norton-Thevenin Receptance Coupling (NTRC), as described in several NASA Engineering and Safety Center (NESC) papers shows promise in enabling loads development for payloads with less computational cost and analyst time as compared to a full integrated vehicle coupled loads analysis (CLA). NTRC allows the free vehicle responses and impedance (accelerance) at the payload to vehicle interface (derived from integrated vehicle CLA) to be used with a payload model in a payload CLA. Due to the NTRC damping differing from the full integrated vehicle damping, results are slightly different, so coverage factors were developed to ensure NTRC results enveloped results from a traditional CLA. NTRC results with coverage factors were very close to full CLA results. The Space Launch System (SLS) coupled loads team has developed an implementation of the NTRC method to enable support of co-manifested payloads with analysis needs that do not fit the primary SLS load cycle schedule. The NTRC method was successfully used to support the European System Providing Refueling, Infrastructure, and Communications (ESPRIT) module for Gateway planned to fly on Artemis V and has been adopted as the SLS approach for supporting payload CLA requests that do not align with vehicle load cycles.

SLS↗

NASA NTRSDate not supplied

Application of Norton-Thevenin Receptance Coupling (NTRC) to Space Launch System (SLS) Payload Coupled Loads Analysis (CLA)

SLS↗

DOE OSTI2025

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

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

42 ENGINEERING↗

DOE OSTI2026

Machine Learning for Fairness-Aware Load Shedding: A Real-Time Solution via Identifying Binding Constraints: Preprint

Timely and effective load shedding in power systems is critical for maintaining supply-demand balance and preventing cascading blackouts. To eliminate load shedding bias against specific regions in the system, optimization-based methods are uniquely positioned to help balance between economic and fairness considerations. However, the resulting optimization problem involves complex constraints, which can be time-consuming to solve and thus cannot meet the real-time requirements of load shedding. To tackle this challenge, in this paper we present an efficient machine learning algorithm to enable millisecond-level computation for the optimization-based load shedding problem. Numerical studies on both a 3-bus toy example and a realistic RTS-GMLC system have demonstrated the validity and efficiency of the proposed algorithm for delivering fairness-aware and real-time load shedding decisions.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2025

Controlled Enzyme Cargo Loading in Engineered Bacterial Microcompartment Shells

Bacterial microcompartments (BMCs) are nanometer-scale organelles with a protein-based shell that serve to colocalize and encapsulate metabolic enzymes. They may provide a range of benefits to improve pathway catalysis, including substrate channeling and selective permeability. Several groups are working toward using BMC shells as a platform for enhancing engineered metabolic pathways. The microcompartment shell of Haliangium ochraceum (HO) has emerged as a versatile and modular shell system that can be expressed and assembled outside its native host and with non-native cargo. Further, the HO shell has been modified to use the engineered protein conjugation system SpyCatcher–SpyTag for non-native cargo loading. Here, we used a model enzyme, triose phosphate isomerase (Tpi), to study non-native cargo loading into four HO shell variants and begin to understand maximal shell loading levels. We also measured activity of Tpi encapsulated in the HO shell variants and found that activity was determined by the amount of cargo loaded and was not strongly impacted by the predicted permeability of the shell variant to large molecules. All shell variants tested could be used to generate active, Tpi-loaded versions, but the simplest variants assembled most robustly. We propose that the simple variant is the most promising for continued development as a metabolic engineering platform.

59 BASIC BIOLOGICAL SCIENCES↗