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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

EMT data generation

The integration of inverter-based resources (IBRs) in power systems is accelerating, bringing with it significant benefits such as reduced greenhouse gas emissions, improved grid resilience, and increased energy independence. Despite these advantages, the widespread adoption of IBRs introduces several challenges, including issues related to grid stability, increased operational complexity, and the need for updated regulatory frameworks. To address these challenges, IEEE released Standard 2800 in 2022, which sets forth the necessary interconnection capabilities and performance criteria for IBRs connected to transmission and sub-transmission systems. This standard outlines the performance requirements to ensure the reliable integration of IBRs into the bulk power system. Furthermore, in 2023, the North American Electric Reliability Corporation (NERC) published a reliability guideline for electromagnetic transient (EMT) modeling of BPS-connected IBRs. This guideline provides recommendations for developing EMT model requirements, performing model quality checks, and implementing verification practices specifically for EMT models representing BPS-connected inverter-based resources in reliability studies conducted by transmission planners and planning coordinators. These standards and guidelines have a profound impact on EMT studies for transmission networks, influencing system stability analyses, grid recovery and resynchronization processes, fault ride-through evaluations, protection and coordination strategies, advanced control methodologies, and the inclusion of IBRs in transient models of transmission networks. As a result, the generation of EMT data is crucial for conducting various transient-based studies to understand the impact of IBRs. EMT data generation use cases serve as the basis for scenarios in event detection and identification use cases, providing comprehensive details about EMT data generation for transmission grids with inverter-based resources. These use cases supply sufficient training and validation datasets for subsequent EMT analysis algorithms.

Xia, Qianxue↗
DOE OSTI2025

Geographically Distributed Co-Simulation for the Interplay of Integrated Energy Systems and Power Grid

The increased penetration of renewable generation induces unbalanced demand-supply on a power grid, while integrated energy systems (IES) can provide high part-load efficiency and high flexibility to support grid resilience. To study the transients and improve dynamic operability, it’s important to investigate the interplay between IES and power grid concurrently using real-time co-simulation approaches. In this presentation, we showed the previous co-simulation test between NETL and INL and discussed how this co-simulation can be beneficial for both IES and power grid research. In addition, we gave an overview about the SuperLab2.0 project, which was a federated national platform to address future power grid challenges. (Virtual presentation to the MILLENNIUM CLEAN and SUSTAINABLE POWER workshop 2025).

Co-simulation↗
DOE OSTI2025

Practical Implementation of GPU-based Computing at the Grid Edge for Resilience Scenarios

This paper presents a practical implementation of GPU-accelerated computing at the grid edge to enhance power system resilience through next-generation smart meters. Advanced Metering Infrastructure (AMI) systems rely predominantly on centralized processing architectures, which limit real-time response capabilities during grid disturbances. This work proposes the integration of GPU-enabled computational platforms directly within smart meter to enable local execution support for power system analytics, fault detection algorithms, and optimization routines. The proposed framework uses the Julia programming language to leverage highperformance parallel computing capabilities while maintaining code portability and development efficiency. We use two experimental scenarios to benchmark the computational feasibility of this approach: sparse linear system solutions representative of power flow analyses, and multi-stage production cost simulations incorporating unit commitment and economic dispatch operations. Results demonstrate that computationally intensive power system algorithms, such as those supporting resilience scenario calculations, can be effectively executed at the distribution edge using commercially available embedded GPU hardware. Keywords—GPU acceleration, edge computing, smart meters, grid resilience, AMI, resilience.

De Souza, Reubun [School of Electrical Engineering↗
DOE OSTI2025

NARUC Resilience Framework

The NARUC Resilience Framework provides state regulators and other key stakeholders with a structured approach to considering policies and programs that will enhance grid resilience amid evolving technological, environmental and economic challenges. This Framework consolidates insights from nationwide workshops and peer discussions into six actionable components: (1) setting goals and objectives, (2) leveraging use cases, (3) establishing shared definitions, (4) ensuring inclusive process leadership, (5) addressing critical design questions, and (6) guiding implementation. This Framework is intended as a strategic tool for regulators to navigate resilience investments, prioritize affordability, integrate stakeholder needs, and foster collaboration across agencies, all while balancing cost-effectiveness with societal and economic resilience outcomes. By presenting a structured approach to decision-making rather than prescriptive solutions, the Framework supports nuanced, jurisdiction-specific resilience planning and is adaptable to the dynamic demands of modern energy systems

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Innovative Pathways to Net Zero Emissions: Subnational Strategies for Distributed Solar Deployment to Improve Grid Quality and Reduce Energy Costs in Argentina

Through Net Zero World, the National Renewable Energy Laboratory (NREL), the National Energy Secretariat of Argentina, La Pampa's Energy and Mining Secretariat, Pampetrol, and the Administracion Provincial de Energia de La Pampa (APELP) conducted an integrated analysis of the power system of the La Pampa province in Argentina. The study assessed the impact that solar and battery energy storage systems could have on the region grid's reliability and electricity costs, providing insights into long-term decarbonization strategies across Argentina. The analysis demonstrated that these systems are expected not only to help with decarbonization efforts but also to bolster grid resiliency, reduce line losses, and improve voltage regulation while lowering electricity costs. The paper offers a replicable framework for similar studies across other Argentine provinces, which could inform a national grid reliability plan and promote regional coordination. Such coordination will play a key role in supporting a nationwide clean energy transition as Argentina increases its share of renewable energy. By coordinating subnational energy plans with national strategies, Argentina can secure a resilient clean energy future, leveraging the substantial renewable resources available across its provinces.

14 SOLAR ENERGY↗
DOE OSTI2025

Electromagnetic Transient Simulation of Large-Scale Inverter-Based Resources With High-Granularity

The power grid is undergoing a significant transformation with the rapid increase in inverter-based resources (IBRs), including large-scale photovoltaic (PV) plants. Ensuring reliable and resilient grid operation in this new paradigm necessitates high-granularity electromagnetic transient (EMT) modeling that accurately captures the behavior of individual inverters and their interactions within IBR plants. Central to this approach is the detailed representation of both the IBR plant’s collector system and the dynamics of individual inverters. To achieve this, a high-granularity EMT model of a large-scale PV plant has been developed using advanced simulation algorithms, including matrix splitting and the Schur complement. These proposed techniques significantly enhance simulation speed, numerical stability, and accuracy while improving the modularity and efficiency of the collector system’s representation. The effectiveness of the proposed methods is validated through simulations of a representative large-scale PV plant consisting of 125 individual PV inverters, 25 IBR unit transformers, and a 52-bus collector system.

Choi, Jongchan [Oak Ridge National Laboratory (ORN↗
DOE OSTI2025

Second-generation downscaled earth system model data using generative machine learning

The second-generation Sup3rCC dataset provides high-resolution meteorological data generated through the downscaling of multiple earth system models (ESMs) from the Coupled Model Intercomparison Project Phase 6 (CMIP6). This downscaling is performed through application of a generative machine learning approach called Super-Resolution for Renewable Resource Data (sup3r). This dataset builds on the first-generation Sup3rCC data by applying improved bias correction methods and adding downscaled precipitation to the output variables. As with the first Sup3rCC version, the data still include temperature, wind speed and direction at multiple heights, pressure, three components of downwelling solar radiation, and relative humidity—all at 4-kilometer (km) hourly resolution over the contiguous United States. This is a 25x spatial enhancement and 24x temporal enhancement of the source 100-km daily-average ESM data. This extension of the Sup3rCC dataset includes data from six ESMs from two shared socioeconomic pathways (SSPs) totaling 400 years of data with multiple future projections of changing meteorological conditions. The scenario selection was based on a structured evaluation of historical ESM skill and comprehensive representation of possible trajectories of future climate change in temperature, humidity, precipitation, solar irradiance, and near-surface wind speeds. The inclusion of multiple future projections is intended to enable users to assess key drivers of un 36 certainty and variability. All data are double-bias corrected, resulting in a product that can be used out-of-the-box for energy system analysis with minimal historical bias. The potential applications of Sup3rCC data extend to various topics in renewable energy resource assessment, energy systems modeling, and grid resilience studies. High-resolution future meteorological projections are critical for evaluating the effects of changing meteorological conditions on renewable energy generation, energy demand, and for optimizing energy storage and grid infrastructure. The 4-km hourly resolution of the downscaled data enables understanding of spatial and temporal variability at the scales necessary for energy system operational planning. In addition, the dataset can support risk assessments by providing detailed information on possible future extreme weather events and long-term meteorological variability at scales relevant to energy infrastructure. By offering an enhanced representation of possible future meteorological conditions, the second-generation Sup3rCC dataset enables more precise modeling of energy resilience and adaptation strategies in response to changing meteorological conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Game Theory Approaches for System-level Incentive Design

This report presents a generalized Stackelberg game framework for designing and evaluating financial incentives that enhance power system resilience through strategic deployment of distributed energy resources(DERs) under various contingencies. The proposed approach addresses the challenge of coordinating individual community investment decisions to meet system-wide resilience objectives. The framework is demonstrated in a three-community test system subjected to two transmission contingency scenarios: inter-community line failure (Case 1) and complete main grid disconnection (Case 2). In both cases, three incentive levels are compared: a Base case with no financial incentives, and low and high incentive cases. In Case 1, the Base case (no incentives) results in a total installed DER capacity of 217.2 MW, with no load shedding due to alternative routing, but community costs remain high. Increasing incentives raises DER deployment to 286.9 MW, lowers aggregate community costs by $22M annually, and completely avoids the need for costly new transmission line construction. In Case 2, the Base case results in 24.3 MWh of unserved load; introducing incentives eliminates all load shedding and ensures up to 89 MWh of battery storage is available for emergency reserve. These results demonstrate that targeted incentives can dramatically improve grid resilience and cost-effectiveness. The framework thus offers policymakers and system planners a robust tool to quantify and compare the effectiveness of incentive programs for multi-community transmission networks behavior, system resilience, and economic efficiency.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Advanced Transmission Technologies (ATTs) Supplier Cohort Workshops Cohort Summary [Slides]

This Summary slide deck summarizes the key outcomes of the Advanced Transmission Technologies (ATTs) supplier cohort, part of Idaho National Laboratory’s (INL) Technical Assistance for Digital Assurance (TADA) program. The program aimed to strengthen grid resilience through cybersecurity controls, supply-chain security, and Cyber-Informed Engineering (CIE) for advanced transmission technologies. The cohort brought together vendors representing the full range of Grid-Enhancing Technologies (GETs), including providers of Dynamic Line Ratings (DLR), Advanced Power Flow Control (APFC), Transmission Topology Optimization (TTO), and High-Performance Conductors (HPCs). Discussions focused on institutional, integration, and operational barriers limiting GET adoption; cybersecurity risks at EMS/SCADA, cloud, and network integration points; and supply-chain transparency issues such as semiconductor dependence and SBOM/HBOM expectations. Participants also addressed operator trust, human-in-the-loop requirements, and challenges with utility adoption, while exploring how CIE can support secure deployment of GETs. This deck represents a consolidated summary of challenges and risks identified by vendors, cross-cutting themes and technology-specific insights from three cohort workshops, and actionable mitigations to guide utilities, vendors, and the Department of Energy in advancing secure, trusted deployment of GETs.

24 - POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Adapting Grid Criticality for Data Centers

This presentation explores the evolving definition of “critical load” in the electric grid, emphasizing the growing importance of digital infrastructure—particularly data centers—in grid resilience, restoration, and modernization. As utilities increasingly rely on AI-driven analytics and software-defined control systems, data centers have shifted from passive electricity consumers to essential computational hubs that enable National Critical Functions (NCFs) and support real-time grid operations. The deck examines the scale and impact of digital loads, the need for grid modernization to manage rapid load growth, and the diverse computing paradigms required for AI deployment. It introduces a tiered taxonomy for classifying critical loads, highlights operational dependencies between the grid and digital infrastructure, and discusses policy implications for integrating data centers into emergency planning and restoration protocols. Through case studies and practical frameworks, the presentation provides actionable insights for utilities, regulators, and planners navigating the digital transformation of the power sector.

29 - ENERGY PLANNING, POLICY AND ECONOMY↗
DOE OSTI2024

Multifunctional Heat Pump with Energy Storage Capability

Replacing gas furnaces with heat pumps on a large scale can pose challenges to the electrical grid. It will significantly increase the demand, strain the electrical grid, especially during peak usage times. To ensure that heat pumps contribute to reducing emissions, it's essential to increase the share of renewable energy in the grid. However, the supply of renewable energy is unstable. Large scale of electrification must address the concern of grid resilience to meet necessary heating/cooling demands and shift peak electric load. All these require future heat pumps having energy storage capability. These systems can store excess energy during low-demand periods and release it during high-demand periods, reducing stress on the grid. This paper will introduce an innovative configuration, control, and laboratory investigations of a multifunctional packaged heat pump. In addition to the original indoor and outdoor air coils, the heat pump has a parallel hydronic loop with a brazed plate heat exchanger (BHP). The hydronic loop circulates hot/chilled water to store heating/cooling energy in phase change material (PCM). It is capable of space cooling, space heating, cooling energy storage/defrosting, water heating/heating energy storage with outdoor air source or indoor air source, and cooling/heating energy free discharge. The laboratory studies and breadboard unit are presented. Additionally, building energy simulation demonstrates utility cost reduction potential via charging PCM panels/ceilings during off-peak hours and releasing the energy during peak hours to mitigate the peak power consumption.

Shen, Bo↗
DOE OSTI2026

Mitigating Data Center Impact on Grid Stability: A Coordinated Control Strategy Using Verrus StabiliGrid Architecture

Large data centers, which now represent a significant and growing share of the total U.S. grid load, can inadvertently destabilize the electrical grid when they disconnect simultaneously during brief voltage disturbances. The July 10, 2024, Eastern Interconnection incident, in which a sub-100-millisecond transmission fault triggered the cascading loss of approximately 1,500 MW of data center load, illustrates this vulnerability. While commercial battery energy storage systems (BESS) deployed in data centers provide device-level fault ride-through per IEEE 1547, they lack coordination with facility protection logic and uninterruptible power supplies (UPS), limiting their effectiveness as grid-stabilizing assets. This report presents the Verrus StabiliGrid architecture, a coordinated control framework that integrates BESS, UPS, and point-of-interconnection (POI) protection settings to enable data centers to ride through both undervoltage and overvoltage grid contingencies without disconnecting. The four-step strategy encompasses: (1) high-resolution power quality monitoring to detect the grid state during events such as undervoltage, overvoltage, underfrequency, and overfrequency; (2) POI protection settings that allow for extended ride-through and grid-connected operation during grid contingencies; (3) grid state-driven autonomous dispatch of assets to improve grid resilience by reducing power draw during undervoltage or absorbing more power during overvoltage events; and (4) coordinated post-recovery dispatch of data center assets to restore firm load to pre-contingency levels. Validated through controller-hardware-in-the-loop (C-HIL) simulations at the National Laboratory of the Rockies, results show grid import restoration to pre-fault levels within 100 milliseconds of voltage recovery. This work advances the ability of data centers to transition from passive, disturbance-sensitive loads to active participants in grid stability, a capability increasingly required by emerging NERC and ERCOT regulatory frameworks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Electricity Markets and Long-Duration Energy Storage: A Survey of Grid Services and Revenue Streams

Purpose of Review Long Duration Energy Storage (LDES) is increasingly viewed as a potential resource for providing grid services that enhance the stability and flexibility of electricity systems. While some LDES services are integrated into existing market frameworks, traditional mechanisms may not fully account for their operational characteristics, potentially leading to undervaluation. Within this context, this paper reviews the literature and industry practices to assess potential grid services for LDES, evaluates existing compensation mechanisms, and identifies challenges to full market integration. Recent Findings We first review existing literature and identify key grid services unique to LDES, including enhancing grid resilience during extreme weather events, enabling long-term energy shifting, and providing flexible and firm energy in systems with limited dispatchable resources. Here, we also review how LDES services are compensated in current market frameworks and the challenges associated with the full realization of LDES values. Additionally, we summarize market mechanisms for storage technologies across U.S. wholesale markets. We find that some markets are adjusting incentive structures, such as incorporating storage duration in capacity accreditation, to better align with system needs and LDES contributions to the grid. However, further refinements in capacity remuneration and dispatch timeframes may be needed for more effective realization of LDES value. Summary This review evaluates potential grid services for LDES, examines existing compensation mechanisms for LDES technologies, and identifies gaps between these mechanisms and LDES operational characteristics. The review concludes by outlining potential market enhancements for more effective LDES integration and articulating additional research needs to support its efficient participation in future power systems.

Flexible resources↗
DOE OSTI2025

Artificial Intelligence for Enhancing Multiscale Analysis: Buildings Focus

This project aims to develop multi-scale building energy data, potentially improving the representation of the U.S. buildings sector in GCAM-USA, an U.S.-focused human-energy-Earth systems model. Existing building energy datasets are typically limited to national or regional levels, which constrains the ability of models to capture fine-scale human-energy-Earth systems interactions and reduces their relevance for decision-making on issues such as energy security, resilience, and energy planning. By leveraging AI and advanced data integration methods, this work fuses multiple existing datasets to enhance the physical and geographic representation of both residential and commercial building energy use. So far, progress includes processing residential building data, designing the data structure for commercial buildings, and testing AI approaches for integrating datasets and addressing spatial-temporal gaps. This effort can not only advances GCAM-USA’s capability in modeling the buildings sector but also supports broader DOE missions, such as developing digital testbeds, enhancing grid resilience analysis, and improving building–energy system modeling at decision-relevant scales.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Machine Learning for Scalable and Optimal Load Shedding Under Power System Contingency

Prompt and effective corrective actions in response to unexpected contingencies are crucial for improving power system resilience and preventing cascading blackouts. The optimal load shedding (OLS) accounting for network limits has the potential to address the diverse system-wide impacts of contingency scenarios as compared to traditional local schemes. However, due to the fast cascading propagation of initial contingencies, real-time OLS solutions are challenging to attain in large systems with high computation and communication needs. In this paper, we propose a decentralized design that leverages offline training of a neural network (NN) model for individual load centers to autonomously construct the OLS solutions from locally available measurements. Our learning-for-OLS approach can greatly reduce the computation and communication needs during online emergency responses, thus preventing the cascading propagation of contingencies for enhanced power grid resilience. Numerical studies on both the IEEE 118-bus system and a synthetic Texas 2000-bus system have demonstrated the efficiency and effectiveness of our scalable OLS learning design for timely power system emergency operations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Data-Driven Modeling of High-Resolution Residential Load Profiles Using Low-Resolution Smart Meter Measurements

Accurate and high-resolution residential load profiles are essential for power system modeling, demand response planning, and effective grid operation. As the energy sector moves towards a more actively managed distribution system, the ability to understand residential energy consumption at a minute-by-minute scale becomes increasingly critical. High-resolution load profiles provide key insights into demand patterns and user behavior, enabling grid operators to design more effective energy solutions; however, residential load measurements in the field are typically recorded at low resolutions, such as 15-60 minutes, which makes it hard to study the characteristics of different residential customers. This paper addresses these challenges by introducing a data-driven approach to generate realistic, high-resolution residential load profiles based on lowre-solution measurements and weather information. The proposed method retains the key features of the actual residential load measurements while offering appliance-level energy consumption details for each residential building. The results demonstrate the effectiveness of the proposed load profile generator, proving its capability to support utilities in optimizing residential energy management and ensuring a more reliable and resilient grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

The Role of the U.S. Electric Distribution System in Serving Data Center and Other Large Loads

The rapid expansion of data centers in the United States is reshaping how the electric distribution system must plan for and accommodate large load interconnections. This report evaluates the role of the distribution grid in serving these loads, from small edge facilities to hyperscale campuses. Using national datasets, utility filings, and industry studies, we assess demand growth, reliability requirements, interconnection thresholds, and infrastructure needs at substations and feeders. The analysis highlights the mismatch between fast data center development timelines and slower utility planning and construction cycles, as well as strategies such as phased energization, on-site generation, hosting capacity maps, and structured interconnection frameworks. While focused on data centers, the insights also apply to other high-density loads such as advanced manufacturing, hydrogen production, and electrified transportation. The report concludes with approaches to align planning processes, transparency tools, and regulatory frameworks so utilities can manage new large loads in ways that support a reliable and resilient grid.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Cool rooms for indoor heat resilience: Evaluating affordable cooling strategies in heat-stressed California homes

Extreme heat conditions pose significant indoor survivability challenges for resource-constrained communities, which often lack access to cooling, have poorly insulated homes, and face compounding socioeconomic vulnerabilities. Moreover, concurrent power outages worsen health risks and heat-related illnesses. It is therefore crucial to develop innovative and affordable cooling approaches to protect vulnerable populations. This study assesses the efficacy of “cool rooms”– a designated space within a home equipped with passive and low-power active cooling measures to maintain safe indoor temperatures during extreme heat events and power disruptions. Using a physics-based building energy modeling approach, we evaluate the efficacy of various retrofit packages in maintaining thermal safety within the cool room under recent extreme heat conditions. The results indicate that passive measures can reduce 64% of hours with unmet standard effective temperatures, while the combination of passive and low-power active measures with built-in batteries further cuts this to 86%. Nevertheless, these strategies remain insufficient to maintain indoor thermal safety during extended outages. In contrast, integrating a solar-powered mini-split heat pump, whose technical potential was evaluated in this study, reduces indoor air temperatures below the 28 °C overheating threshold and significantly improves indoor habitability. The localized cool room strategy also offers potential for grid resilience by reducing peak electricity demand by up to 70% compared to whole house cooling during heat waves. The findings can inform the development of actionable heat mitigation plans and retrofit policies for residential communities with relatively low adoption of air conditioning such as warm marine climates.

Cool room↗