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At least 847 records · Page 47

Storage Futures Study: Grid Operational Impacts of Widespread Storage Deployment

This report, the fifth in the Storage Futures Study series, uses cost-driven scenarios from the ReEDS model as a starting point to examine the operational impacts of grid-scale storage deployment and relationships between this deployment and the contribution of variable renewable energy. We use commercial production cost modeling software to evaluate hourly operation of five scenarios that reach between 210 gigawatts (GW) and 930 GW of installed storage by 2050. We find that storage plays an important role in these power systems between now and 2050 - by storing the lowest-marginal cost generation (often, overgeneration from solar or wind plants) and generating energy during the highest net load periods of the day and year. Storage helps with the integration of variable renewable energy and by providing an important resource to provide continued reliable power.

battery↗

Climate-Water Impacts on Interconnection-Scale Electricity System Planning

A growing literature emphasizes the importance of integrating climate change impacts into electricity system planning. Rising average temperatures can increase and shift electricity demand while reducing generator and transmission efficiency. Changes to water availability and quality can reduce the output of thermally cooled generators and hydropower. Electric power grids across the US and globally are undergoing transformational changes that present new opportunities and challenges to reliability assurance. However, electric utilities and system operators have limited internal capabilities to incorporate these effects into planning practices. This work addresses gaps in utility and system planner practices by integrating climate-water-electricity expertise from universities and U.S. Department of Energy National Laboratories with electricity system planners and stakeholders in the Western Electricity Coordinating Council (WECC). Using a highly collaborative approach, global climate model data, high-resolution hydrology models, and long-term electric sector capacity expansion tools are employed to analyze a range of climate outcomes for future electricity scenarios aligned with recent WECC planning studies. Doing so allows WECC to expand its climate-agnostic planning assessments to consider how future temperature and precipitation patterns could influence generation and transmission planning. We explore how changes to climate-water conditions can affect power plant investment and operation, system economics, and environmental impacts, providing an expanded perspective on interconnection-wide decision making under climate uncertainty.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

IM3 Projected U.S. Western Interconnection Grid Stress Dataset

This dataset provides projected grid stress and reliability results (including all model inputs and outputs from GO WEST and TEP) for Integrated Multisector, Multiscale Modeling (IM3) Phase 2 simulations across eight different scenarios for the U.S. Western Interconnection through 2055. The scenarios include combinations of two Shared Socioeconomic Pathways (SSP3 and SSP5) with four high-resolution climate projections specific to the United States from a set of Thermodynamic Global Warming (TGW) simulations. These climate projections include "hotter" and "cooler" variants for two Representative Concentration Pathways (RCP4.5 and RCP8.5). The resulting eight simulations are: rcp45cooler_ssp3 rcp45cooler_ssp5 rcp45hotter_ssp3 rcp45hotter_ssp5 rcp85cooler_ssp3 rcp85cooler_ssp5 rcp85hotter_ssp3 rcp85hotter_ssp5 GO WEST is an open-source power grid modeling framework for the U.S. Western Interconnection, which allows users to tailor the model depending on their research study and science questions. It covers 28 balancing authorities (BAs) and 12 states in U.S. Western Interconnection. GO WEST allows users to select different number of nodes and come up with a simplified network by utilizing 10,000 nodal topology of the U.S. Western Interconnection (ACTIVSg10k). Users can select different number of nodes, mathematical formulations (linear programming vs. mixed-integer linear programming), transmission line limit scaling factors, and hurdle rate scaling factors. GO WEST offers a unit commitment and economic dispatch (UC/ED) module to simulate grid operations on an hourly scale. In this sense, users can calibrate and validate their model versions by comparing model outputs to historical datasets. TEP is an open-source transmission capacity expansion model, built on the GO WEST framework. It utilizes linear programming to optimize transmission capacity addition investment on existing lines within the GO WEST framework. The TEP model only increases the thermal capacity of existing transmission lines and does not add new lines to the system, which leaves the topology preserved. In order to use TEP model, users need to create scenarios with the GO WEST framework. Please refer to README file for a detailed description of the dataset including individual files and references.

Capacity Expansion Model↗

Interconnection of Distributed Energy Resources in the Indian Context: IEEE 1547-2018 Adaptation for Locally-Appropriate Grid Code Development

The rapid growth of distributed energy resources (DERs) in India and ambitious renewable energy goals set forth by the Indian government have created the need for appropriate distribution interconnection standards to ensure continued system stability, reliability, and resilience. Existing DER interconnection codes in India, at the time of publishing this report, lack many of the critical grid support functionalities for DERs which may protect bulk system stability, such as event ride-through provisions, frequency droop control, or appropriate trip thresholds given the increasing importance of distributed generation. The formal adoption of IEEE 1547-2018 by the Bureau of Indian Standards (BIS) marks a significant step towards achieving appropriate interconnection of DERs, though the implementation of such a standard must be accompanied with careful consideration of the current codes, regulations, and operation of the Indian power system. Studies on the performance of the functionalities within 1547-2018, which properly incorporate local operating conditions, can inform decisions related to the adoption and adaptation of the clauses present in the standard. This report outlines several of these key considerations for stakeholders and provides analyses illustrating the performance of grid support functionalities on typical Indian distribution feeders.

1547↗

pyRMG: A framework for high-throughput, large-cell DFT calculations on supercomputers

Exascale computing delivers the raw power to simulate ever larger and more chemically realistic systems, but realizing this potential requires codes that can efficiently use thousands of processors. Our real-space multigrid (RMG) density functional theory (DFT) code’s grid-decomposition approach scales nearly linearly with the number of graphics processing units (GPUs), even for simulations exceeding thousands of atoms. This scalability makes RMG a compelling tool for high-throughput DFT studies of materials that would otherwise be bottlenecked in other codes (for example, by global fast Fourier transforms in plane-wave DFT). However, the limited workflow infrastructure for RMG has thus far constrained its adoption to a small user community. In this work, we present pyRMG, a Python package designed to streamline the setup and execution of RMG DFT calculations. Built on the pymatgen and ASE (Atomic Simulation Environment) computational materials science Python packages, pyRMG automates input generation and convergence checking, and it integrates with modern job schedulers (e.g., Flux) on leadership-class platforms such as Frontier and Perlmutter. Here, we demonstrate pyRMG for a high-throughput study of strain effects in 2D 2L-Bi 2 Se 3 /2L-NbSe 2 heterostructures, which offers chemical insights into this system and shows that RMG-based workflows can converge with limited user intervention.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comparing the economic performance of ice storage and batteries for buildings with on-site PV through model predictive control and optimal sizing

Integrating renewable energy and energy storage systems provides a way of operating the electrical grid system more energy efficiently and stably. Thermal storage and batteries are the most common devices for integration. However, it is not clear which integrated storage system performs better in terms of overall economics. Ice storage has low initial and maintenance costs, but there is an efficiency penalty for charging of storage and it can only shift electrical loads associated with building cooling requirements. A battery's round-trip efficiency, on the contrary, is quite consistent and batteries can be used to shift both HVAC and non-HVAC loads. However, batteries have greater initial costs and a shorter life. Finally, this research presents a tool, using model predictive control and optimal sizing, and provides a case study for comparing life-cycle economics of battery and ice storage systems for commercial buildings that have chillers for cooling and an on-site photovoltaic system.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A Comprehensive Analysis of PINNs for Power System Transient Stability

The integration of machine learning in power systems, particularly in stability and dynamics, addresses the challenges brought by the integration of renewable energies and distributed energy resources (DERs). Traditional methods for power system transient stability, involving solving differential equations with computational techniques, face limitations due to their time-consuming and computationally demanding nature. This paper introduces physics-informed Neural Networks (PINNs) as a promising solution for these challenges, especially in scenarios with limited data availability and the need for high computational speed. PINNs offer a novel approach for complex power systems by incorporating additional equations and adapting to various system scales, from a single bus to multi-bus networks. Our study presents the first comprehensive evaluation of physics-informed Neural Networks (PINNs) in the context of power system transient stability, addressing various grid complexities. Additionally, we introduce a novel approach for adjusting loss weights to improve the adaptability of PINNs to diverse systems. Our experimental findings reveal that PINNs can be efficiently scaled while maintaining high accuracy. Furthermore, these results suggest that PINNs significantly outperform the traditional ode45 method in terms of efficiency, especially as the system size increases, showcasing a progressive speed advantage over ode45.

97 MATHEMATICS AND COMPUTING↗

A Comprehensive Analysis of PINNs for Power System Transient Stability

The integration of machine learning in power systems, particularly in stability and dynamics, addresses the challenges brought by the integration of renewable energies and distributed energy resources (DERs). Traditional methods for power system transient stability, involving solving differential equations with computational techniques, face limitations due to their time-consuming and computationally demanding nature. This paper introduces physics-informed Neural Networks (PINNs) as a promising solution for these challenges, especially in scenarios with limited data availability and the need for high computational speed. PINNs offer a novel approach for complex power systems by incorporating additional equations and adapting to various system scales, from a single bus to multi-bus networks. Our study presents the first comprehensive evaluation of physics-informed Neural Networks (PINNs) in the context of power system transient stability, addressing various grid complexities. Additionally, we introduce a novel approach for adjusting loss weights to improve the adaptability of PINNs to diverse systems. Our experimental findings reveal that PINNs can be efficiently scaled while maintaining high accuracy. Furthermore, these results suggest that PINNs significantly outperform the traditional ode45 method in terms of efficiency, especially as the system size increases, showcasing a progressive speed advantage over ode45.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Turbulent Premixed Flame Propagation in Microgravity

A facility in which turbulent Couette flow could be generated in a microgravity environment was designed and built. To fit into the NASA Lewis drop tower the device had to be very compact. This means that edge effects and flow re-circulation were expected to affect the flow. The flow was thoroughly investigated using LDV and was found to be largely two dimensional away from the edges with constant turbulence intensities in the core. Slight flow asymmetries are introduced by the non symmetric re-circulation of the fluid outside the test region. Belt flutter problems were remedied by adding a pair of guide plates to the belt. In general, the flow field was found to be quite similar to previously investigated Couette flows. However, turbulence levels and associated shear stresses were higher. This is probably due to the confined re-circulation zone reintroducing turbulence into the test section. An estimate of the length scales in the flow showed that the measurements were able to resolve nearly all the length scales of interest. Using a new LES method for subgrid combustion it has been demonstrated that the new procedure is computational feasible even on workstation type environment. It is found that this model is capable of capturing the propagation of the premixed names by resolving the flame in the LES grid within 2-3 grid points. In contrast, conventional LES results in numerical smearing of the flame and completely inaccurate estimate of the turbulent propagation speed. Preliminary study suggests that there is observable effect of buoyancy in the 1g environment suggesting the need for microgravity experiments of the upcoming experimental combustion studies. With the cold flow properties characterized, an identical hot flow facility is under construction. It is assumed that the turbulence properties ahead of the flame in this new device will closely match the results obtained here. This is required since the hot facility will not enable LDV measurements. The reacting flow facility is also being constructed with planned drop tower experiments in mind. Therefore, issues related to safety and structural integrity are being take into account. Further development of the numerical model will also be carried out to include finite-rate kinetics for representative premixed cases. More detail analysis of the flame structure and propagation nature will be investigated. Simulations will also be compared to the flame properties observed in the experiments.

Menon, S.↗

Unstructured Grid Development for the Space Launch System Liftoff and Transition Lineloads Computational Analysis

Production of aerodynamic lineloads databases for the Space Launch System (SLS) vehicle at Liftoff and Transition (LOT) conditions has required the development of a Computational Fluid Dynamics (CFD) workflow capable of producing high-quality solutions for this unique phase of flight. Aerodynamic considerations included a wide range of flow angles (from 0°up to 90°total angle of attack), resulting leeside separation, and interaction effects between the three bodies of the integrated SLS vehicle, as well as the nearby launch tower. Computational mesh development for similar problems at the NASA Langley Research Center (such as for the Constellation/Ares launch vehicles) has primarily relied on in-house tools such as VGRID/POSTGRID, with grids designed for NASA-developed and maintained flow solvers such as USM3D and FUN3D. The workflow for such problems has evolved over the development of the various SLS configurations to incorporate new tools such as the Heldenpatch/Heldenmesh grid generator (Helden Aerospace) and CREATE-AV Kestrel (US Department of Defense) flow solver. This paper describes efforts to benchmark a grid generation approach for LOT problems using Heldenpatch/Heldenmesh and Kestrel, verified against prior best practices from VGRID/POSTGRID. Parameters studied include surface grid density, first-layer viscous cell height, and volume grid growth rate parameters. Resulting solutions are compared based on total force and moment values, sectional line loads, and surface pressures, all validated against existing wind tunnel aerodynamic databases where available for the SLS Block 1B Cargo configuration.

Space launch systems↗

Updates of MERRA-2 Data and Services at NASA GES DISC

Over40 years of NASA climate reanalysis datasets from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) are available at the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC). In addition to being used in traditional weather and climate research, MERRA-2 is also widely used in application studies of, e.g., wind and solar energy, air quality and health, food and drought, and heat waves. Two new MERRA-2 datasets were recently added at the GES DISC: (1) climate statistics derived fromMERRA-2 daily data to assist in the analysis of extreme temperature and precipitation events and of large-scale meteorological patterns from 1980 to the present and (2) gridded satellite and conventional observations processed in the MERRA-2 system, along with key statistics derived from the data assimilation, to help better understand how the quality of observations directly affect there analysis data. The GES DISC focuses its efforts on continually improving existing data services and to develop new data tools to satisfy various user communities. The newly added features include the following: Time series service: This is a new service for MERRA-2 data, which enables the easy and fast access of long-term hourly or daily time series at a location for popular parameters. The data is saved in a single le in Ascii format with a user- friendly structure. New analytic functions in the subsetter interface: Options for downloading daily minimum and maximum values have been added into the subsetter interface, in addition to the existing daily mean option, for all MERRA-2 and MERRA sub-daily products. Data format conversion to GeoTIFF has been implemented. New variables in Giovanni: Most monthly variables have been integrated into Giovanni, GESDISC’s online visualization and analysis tool. Due to the large data volume, hourly variables were selected based on user requests. More online information: New MERRA-2 documentation has been added: Data How-To, Data in Action, and FAQ. This presentation overviews two new MERRA-2 datasets and illustrates the new features of data services through a number of case studies. MERRA-2 data and services can be found at: https://disc.gsfc.gov/datasets?

Data management↗

Time-dependent treatment of scattering - Integral equation approaches using the time-dependent amplitude density

The time-dependent form of the Lippmann-Schwinger integral equation is used as the basis of several new wave packet propagation schemes. These can be formulated in terms of either the time-dependent wave function or a time-dependent amplitude density. The latter is nonzero only in the region of configuratiaon space for which the potential is nonzero, thereby in principle obviating the necessity of large grids or the use of complex absorbing potentials when resonances cause long collision times (leading, consequently, to long propagation times). Transition amplitudes are obtained in terms of Fourier transforms of the amplitude density from the time to the energy domain. The approach is illustrated by an application to a standard potential scattering model problem where, as in previous studies, the action of the kinetic energy operator is evaluated by fast Fourier transform (FFT) techniques.

Hoffman, David K.↗

The Parallel System for Integrating Impact Models and Sectors (pSIMS)

We present a framework for massively parallel climate impact simulations: the parallel System for Integrating Impact Models and Sectors (pSIMS). This framework comprises a) tools for ingesting and converting large amounts of data to a versatile datatype based on a common geospatial grid; b) tools for translating this datatype into custom formats for site-based models; c) a scalable parallel framework for performing large ensemble simulations, using any one of a number of different impacts models, on clusters, supercomputers, distributed grids, or clouds; d) tools and data standards for reformatting outputs to common datatypes for analysis and visualization; and e) methodologies for aggregating these datatypes to arbitrary spatial scales such as administrative and environmental demarcations. By automating many time-consuming and error-prone aspects of large-scale climate impacts studies, pSIMS accelerates computational research, encourages model intercomparison, and enhances reproducibility of simulation results. We present the pSIMS design and use example assessments to demonstrate its multi-model, multi-scale, and multi-sector versatility.

crop modeling↗

Progress on Optimizing Wind Farms and Rotor Designs Using Adjoints

Modern wind plants are increasingly tasked with multiple performance objectives. In addition to designing plants that maximize power output and minimize the levelized cost of energy (LCOE), the design and operation of wind plants is increasingly influenced by challenges regarding grid integration of variable generation renewables. This places a growing emphasis on making wind plants more controllable and predictable. WindSE is a Reynolds-averaged Navier-Stokes (RANS) model designed around analytical gradient and adjoint methods, with the ability to capture terrain-induced effects, as shown in Figure 1. The recent addition of an unsteady solver with an actuator line method (ALM) and ongoing work to enable massively parallel optimizations gives it a unique niche to explore coupled plant-level controls and design problems. This code is an open source python package built on the FEniCS framework that utilizes fast, parallel PETSc solvers to model fluid flow throughout wind-farm scale domains. Two recent studies performed using WindSE demonstrate the capability to optimize under a wide variety of flow conditions and objective functions. In the first, we present an optimization focused on modifying the layout of a wind farm with a fixed number of turbines for maximum total power output [1]. This study highlights the ability to quickly perform simulations using the steady Navier-Stokes solver combined with rotors represented as actuator disks while also stressing the importance of capturing terrain-induced effects. Gradient-based optimization using the RANS equations is viable due to the inclusion of efficiently computed adjoint derivatives. We interpret the physical results of the optimal layout and also discuss the computational cost of scaling to larger problems. In the second study, we present the capabilities of the unsteady Navier-Stokes solver, where rotor-blade profiles represented by actuator lines are optimized to enhance wake steering effects and overall power production [2]. We quantify the wind plant performance gains obtained from this type of simultaneous control co-design optimization as compared to optimizing the blade design and yaw independently. Figure 2 shows the differences between a baseline two-turbine system and an optimized system where we fine-tune the blade chord profile. Results and challenges from each study are quickly summarized and used to motivate the current development efforts within WindSE. Current and future work is focused on enabling higher-resolution studies with more degrees of freedom through parallelization of both the simulation and optimization algorithms. We present benchmarking results to show that WindSE performs well in both weak- and strong-scaling tests and further demonstrate that the optimizer obtains the same convergence rates in both shared- and distributed-memory environments. Using larger wind farms, we can study deep-array effects within an optimization context, allowing the use of objective functions that have been previously unstudied. As an example, we present ongoing work on a blockage metric which characterizes the loss of available kinetic energy due to wake effects from multiple upstream turbines.

adjoint optimization↗

Bridging the Gap for Powering Data Centers

The rapid expansion of data centers, primarily driven by artificial intelligence, is outpacing the adaptability of the U.S. electric grid. This report, developed by Idaho National Laboratory (INL) , presents a gap analysis of some of the infrastructure challenges associated with large-scale data center deployment. Drawing from a national workshop hosted by INL in October of 2025, the report synthesizes stakeholder insights, survey data, and technical discussions to identify critical barriers and research needs. Key findings highlight the growing preference for behind-the-meter generation, the perceived inadequacy of legacy interconnection processes, and the urgent need for improved coordination between utilities, regulators, and data center developers. Environmental concerns such as water use and noise pollution, as well as economic constraints like equipment lead times and cost allocation, are also explored. The report outlines national lab capabilities in modeling, simulation, and technical assistance, and proposes targeted R&D priorities to support resilient, scalable, and efficient integration of data centers into the grid.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Simulation of a PCM Integrated Heat Pump Using Time-of-Use Utility Structure based Control Strategy for Demand Response

To mitigate the variation in demand on the electric grid, thermal energy storage (TES) is an alternative to electric batteries and constructing new peaking power plants. The aggressive carbon reduction goals of the United States are accelerating the electrification of building equipment. If space heating and cooling in the US were electrified using conventional heat pump technologies, the winter electric grid peak would approximately double. Integrating TES with heat pump (HP) enables electrification of space cooling and heating devices without overtaxing the grid.This paper evaluates the benefits of a novel phase change material (PCM) integrated heat pump configuration via simulation. A one-dimensional PCM heat exchanger model which discretizes the PCM tank and refrigerant tubes into small control volumes is developed. Each control volume can have different PCM temperatures, PCM properties, and heat transfer coefficients. The PCM tank is charged by a wrapped tank condenser and discharged by an internal refrigerant coil. The PCM heat exchanger model is integrated into DOE/ORNL Heat Pump Design Model for heat pump system simulation.To demonstrate the performance of the PCM integrated heat pump, a case study in Chicago was performed. A Time-of-Use utility structure-based control strategy is implemented to schedule the PCM tank charging and discharging mode switching. Compared with a conventional electric heat pump, the PCM integrated heat pump shows superior performance on load shifting and utility cost reduction. As a result, the proposed system demonstrates 24.6% utility saving for cooling application and 25.8% utility saving for heating application.

Li, Zhenning↗

Impact Analysis of High-Altitude Electromagnetic Pulse Coupling Effects on Power Grid Protection Relays

Protection relays are important equipment used for protection, control, and metering functions in the power grid. These relays are used to protect critical and difficult-to-replace equipment, like generators, transformers, and capacitor banks. Once the protection devices are disturbed or damaged, a high risk of power generation interruption occurs. Therefore, it is important and necessary to study the relay’s immunity to electromagnetic pulse (EMP) events. As a preliminary step toward empirical experimentation on actual equipment, this manuscript outlines an economical and efficient methodology for evaluating the impact of an EMP. An impedance measurement strategy was employed to model the equipment, setting the stage for subsequent immunity analyses. These analyses included the pulse current injection (PCI) method, which utilized an injecting probe to introduce the transient, and frequency domain electromagnetic (FEKO) simulation, which integrated electromagnetic coupling effects into the transient simulation. The impedance measurement and simulation results in this paper provide a reliable basis for gauging equipment performance in the face of HEMP threats. The results obtained using the PCI and FEKO simulations demonstrated the performance of different port responses under a high-altitude EMP, indicating the requirement for some protection to ensure the reliable operation of relays.

42 ENGINEERING↗

Africa Battery Energy Storage Systems (BESS) Capacity Building Utility-Scale Storage: BESS Valuation, Tariffs, and Remuneration [Slides]

Utility-scale Battery Energy Storage Systems (BESS) are key to enhancing grid reliability, integrating renewable energy, and providing operational flexibility. Designing effective valuation, remuneration, and tariff frameworks is essential to ensure both system benefits and financial viability for developers. This presentation outlines a structured methodology for evaluating BESS projects, covering policy and legal considerations, cost and revenue analysis, benchmarking, financial sensitivity, and risk assessment, while ensuring alignment with public interest. It also explores valuation of multiple storage services - bulk energy, ancillary services, and infrastructure support - and monetization strategies through capacity payments, energy tariffs, tolling, arbitrage, and non-wires alternative payments. Technical factors, including round-trip efficiency, degradation, and storage duration, are integrated into financial and operational modeling to quantify both system-wide and project-level benefits. Through case studies and simulation-based approaches, this framework provides regulators, utilities, and developers with practical guidance for tariff design, payment structures, and investment decisions, maximizing the economic and societal value of BESS deployment.

25 ENERGY STORAGE↗