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At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

From Bricks to Clicks: Mapping the White Space in Building Innovation

It is a critical national imperative to transform the buildings sector, yet innovation is impeded by deployment failures that leave promising technologies stranded. Conventional market reports and techno-economic analysis provide an insufficient understanding of markets and resource allocation for emerging building technologies. They omit crucial commercialization factors such as ecosystem maturity and adoption friction, where the coordinated participation of a network of suppliers, contractors, financiers, regulators, and integrators is required to scale solutions. This study addresses these gaps by introducing an evaluation framework grounded in front-line data from six years of the DOE's IMPEL incubator, comprising experience from 300 building-sector innovators and the adjacent, complex ecosystem. Our methodology synthesizes top-down market analysis with bottom-up, practitioner-level data across five megatrends: (M1) Affordable materials and industrialized construction; (M2) Healthy and efficient mechanical systems; (M3) Intelligent building operations; (M4) Buildings as grid assets; and (M5) High-density power and cooling for data centers and therein identify twelve "white space" technology opportunities. Next, we develop a multi-criteria scoring rubric to rank these opportunities based on parameters, i.e., Affordability, Quality of Life, Reliability, and Security, yielding composite ‘Demand’ and ‘Maturity’ indices. Our results indicate that the most significant white spaces may not be incremental products but a new class of ‘Ecosystem Enablers’, such as logistics platforms, orchestration layers, and automated compliance software that solve structural deployment gaps. This paper summarizes this transparent, evidence-based, practitioner-informed evaluation framework for policymakers and investors to re-evaluate policy and resource allocation and unlock scalable market transformation.

Singh, Reshma↗
DOE OSTI2023

Implementing a Terrestrial Timing Solution: Best Practices

This document is an overview and guide on the concept of precision time and how an alternative terrestrial timing solution to the Global Positioning System (GPS) can be implemented. What follows is a set of recommendations and best practices, derived from research at Oak Ridge National Laboratory (ORNL), across industry, and within the U.S. government, to implement a system of precision timing synchronization to support resilient operations for the U.S. grid. Precision time is a fundamental necessity for operating the grid today, and it becomes even more important as the grid modernizes with clean energy sources, microgrids, and precision sensors placed throughout the grid system to ensure failureresistant operations. The Global Navigation Satellite System (GNSS), which includes (GPS), is currently the primary provider of precision timing today. A terrestrial-based system for time delivery and synchronization to augment GPS is outlined below and it would provide secure time, synchronized with Coordinated Universal Time (UTC), in the event of outages or other interruptions associated with time delivery.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

Computational Algorithms for Unit Commitment with AC Power Flows (Final Report)

Security-constrained unit commitment (SCUC) is a key component in power system operations. When AC power flow constraints are considered in the SCUC model (AC-SCUC), the problem becomes extremely difficult due to its discrete and non-convex nature, as described in “Grid Optimization Competition Challenge 3 Problem Formulation (GOCC)”. There are four main challenges: (i) Discrete decisions regarding unit online/offline status and start-up/shut-down procedures for every single unit. The number of discrete decision variables increases considerably when a system integrates multiple generators; (ii) Configuration-based combined-cycle formulations, and multi-commodity models that include ramping products, spin/non-spin products, and regulation up/down products. The combined-cycle units introduce additional discrete decision variables and auxiliary service products further complicate the model by connecting multi-commodity products’ continuous and discrete variables; (iii) SCUC models with AC power flow constraints are far more complex due to massive bilinear terms in the large-scale nonlinear power balance equations. The nonlinear power balance equations are further complicated by the discrete step control variables of shunts; (iv) N − 1 contingency analysis. The size of the model increases linearly with the number of contingencies considered, greatly increasing the size of the optimization model. Accordingly, there is an emergent need to develop a robust algorithm capable of deriving a high-quality solution in a short time and passing through contingency tests simultaneously. In this project, we explore innovative techniques to address this challenging problem by integrating advanced polyhedral theory, approximation methods, relaxation strategies, decomposition techniques, and parallel computing. Each technique approaches the problem from a different perspective, leveraging its specific strengths to tackle distinct challenges. Each individual method has demonstrated its effectiveness in the PI’s previous research. Their integration is expected to significantly reduce the computational time required to solve the proposed complex problem. Successful completion of this project has the potential to transform the industry by enhancing optimization solvers capable of handling large-scale day-ahead energy market clearing models within strict time constraints, while incorporating AC power flow constraints. This advancement will lead to reduced overall generation costs and, consequently, increased social welfare.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Device-Centric Firmware Malware Detection for Smart Inverters using Deep Transfer Learning

Since future power grids are inverter-dominant grids and inverters are getting smarter by incorporating remote access and seamless firmware update, it is anticipated that malware attackers will directly target smart inverters. However, malware threats targeting smart inverters have been less studied yet. This paper explores potential malware attacks targeting smart inverters and proposes a deep transfer-learning (DTL)-based malware detection framework for smart inverters. The proposed DTL method can significantly reduce development time and efforts for an artificial intelligence-based malware detection algorithm while improving detection accuracy. The experimental result shows that the proposed method achieves 98% of firmware malware detection accuracy. Furthermore, this approach will be transformative to other smart grid devices enabling seamless firmware update.

artificial intelligence↗
DOE OSTI2024

Federated Architecture for Secure and Transactive Distributed Energy Resource Management Solutions

There are fewer conventional, dispatchable generation resources and more variable renewable energy (VRE) and distributed energy resources (DERs). There is more uncertainty from bulk-level VRE and net demand from distribution systems with high DER levels. FAST-DERMS aims to develop and demonstrate a scalable solution for managing uncertainties in supply and demand at the grid edge. We propose that distribution system operators (DSOs) provide firm net load forecasts to the bulk system operator's energy management system (EMS).

distributed energy resources↗
DOE OSTI2025

Enhanced Power Grid Maintenance Planning and Quantum-Inspired Combinatorial Prospects

Efficient and reliable scheduling of maintenance for power generation and transmission infrastructure is essential for minimizing operational costs and ensuring grid stability. This paper introduces an integrated optimization framework for coordinated maintenance scheduling of generators and transmission lines under resource and reliability constraints. The model minimizes a composite cost function including maintenance and generation costs, as well as penalties for delayed maintenance, while satisfying N−1 security constraints, operational limits, and crew availability. Case studies on the IEEE 300-bus test system demonstrate the effectiveness of the proposed approach in producing feasible and cost-effective maintenance schedules. To address scalability and combinatorial complexity, the model is mapped into a Quadratic Unconstrained Binary Optimization (QUBO) problem, enabling exploration of solution approaches based on Quantum Imaginary Time Evolution (QITE). While the QUBO reformulation provides a foundation for future quantum-inspired optimization, this study focuses primarily on the development and demonstration of the classical optimization framework and illustrates the potential applicability of QITE in large-scale maintenance scheduling.

Chen, Yang [ORNL] (ORCID:0000000271693874)↗
DOE OSTI2022

DGTile

SAND2022-12898 O DGTile is a lightweight C++17 adaptive mesh library meant to support explicit discontinuous Galerkin applications on high performance computing machines. DGTile uses a block-based adaptive mesh refinement approach, where the underlying mesh data structure is an octree in three dimensions, where each leaf node of the tree represents a Cartesian grid. Over each grid, DGTile provides modal discontinuous Galerkin basis functions to facilitate simulations. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Granzow, Brian↗
DOE OSTI2025

DOE Challenges and Opportunities Associated with Accountable Nuclear Material Needs for Development and Commercialization of Fusion Nuclear Energy

Fusion energy represents a transformative opportunity to deliver a safe, plentiful, and carbon-free source of reliable primary power. In recent years, fusion research and development have accelerated significantly, particularly within the US, driven by decades of foundational public investment. Notably, in 2024 the US Department of Energy (DOE) established a comprehensive Fusion Energy Strategy aimed at collaborating with industry partners to enable the deployment of fusion power plants and grid integration by the 2030s. This strategy is chiefly implemented through the DOE Office of Science (SC) Fusion Energy Sciences program. This project was initiated to identify potential approaches for the Office of Environment, Safety, and Health (NA-ESH-12) within DOE’s National Nuclear Security Administration to begin engagement with the fusion community on future accountable material needs. The goal of the project is to inform and influence the supply of and demand for accountable nuclear materials as fusion energy is developed and commercialized. NA-ESH-12 must proactively engage with the fusion community regarding the production and management of accountable nuclear materials. Given the complexity and scale of materials required for research, pilot projects, and eventual commercial reactors, early coordination is vital. The project’s objective is to provide insights that will shape the supply and demand landscape for critical nuclear materials, ensuring that DOE is prepared to effectively support fusion energy development and commercialization. In FY 2025, an initial limited review was conducted to identify the status of the fusion energy community’s progress toward full-scale energy production and the need for accountable nuclear material. This included communications with SC, NA-ESH-12, Savannah River National Laboratory, and Oak Ridge National Laboratory, and attending the Rutgers University–sponsored Supply Chain Workshop: Scaling the Fusion Industry and the International Atomic Energy Agency’s Ninth DEMO Programme Workshop. The review to date indicates that the amounts of tritium, lithium-6, and deuterium required by the fusion industry will be dependent on fuel type, breeding technology, blankets, and R&D improvements. One concern is that the commercial sector does not have a sufficient supply chain to meet the demand for development and commercialization for fusion energy production. The supply and demand estimates for these materials should be routinely reviewed as fusion technologies mature.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Arctic Community Engagement: Enhancing Energy Affordability, Resilience, Security

The changing Arctic geopolitical and natural environment presents significant new challenges and opportunities for innovation, economic development, and sustainable energy, as well as enhancing resilience and security in Alaska communities and the greater Arctic region. NREL's Arctic strategy focuses on addressing the impacts of climate change, developing a clean energy and weatherization workforce in the arctic, advancing energy innovation, developing climate appropriate and affordable housing, and ensuring energy security in an era of growing geopolitical threats.

Alaska↗
DOE OSTI2020

Recommended Functionalities for Improving Cybersecurity of Distributed Energy Resources

The current electric grid is transitioning through increasing penetration of distributed energy resources (DERs), which include intermittent renewable generation resources on the distribution side. Both the monitoring and control of DERs require extensive data-exchange and communication networks. These networks lead to cyber vulnerabilities and risks of new kinds of cyberattacks that may be extremely destructive for power system operations. Although current standards, such as IEEE Std. 1547-2018, do not discuss cybersecurity measures for DERs, cybersecurity controls should be developed for securing DER systems at the device level, communications level, and applications level. This paper discusses the current industry's best practices related to DER cybersecurity and proposes recommended functionalities for improving the cybersecurity posture of DERs, specifically at the device/distribution level. These practical recommendations have been discussed and verified with the industry through a DER cybersecurity working group.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Probabilistic Grid Reliability Analysis with Energy Storage Systems

SAND2025-12025O The Probabilistic Grid Reliability Analysis with Energy Storage Systems (ProGRESS) software tool is an open-source tool for assessing the resource adequacy of the evolving electric power grid integrated with energy storage systems (ESS). This tool uses a simulation engine to create diverse scenarios that test the limits of the modern power grid consisting of a high-volume ESS and variable energy resources (VER). Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Nguyen, Tu↗
DOE OSTI2020

Detection of DoS Attacks Using ARFIMA Modeling of GOOSE Communication in IEC 61850 Substations

Integration of Information and Communication Technology (ICT) in modern smart grids (SGs) offers many advantages including the use of renewables and an effective way to protect, control and monitor the energy transmission and distribution. To reach an optimal operation of future energy systems, availability, integrity and confidentiality of data should be guaranteed. Research on the cyber-physical security of electrical substations based on IEC 61850 is still at an early stage. In the present work, we first model the network traffic data in electrical substations, then, we present a statistical Anomaly Detection (AD) method to detect Denial of Service (DoS) attacks against the Generic Object Oriented Substation Event (GOOSE) network communication. According to interpretations on the self-similarity and the Long-Range Dependency (LRD) of the data, an Auto-Regressive Fractionally Integrated Moving Average (ARFIMA) model was shown to describe well the GOOSE communication in the substation process network. Based on this ARFIMA-model and in view of cyber-physical security, an effective model-based AD method is developed and analyzed. Two variants of the statistical AD considering statistical hypothesis testing based on the Generalized Likelihood Ratio Test (GLRT) and the cumulative sum (CUSUM) are presented to detect flooding attacks that might affect the availability of the data. Our work presents a novel AD method, with two different variants, tailored to the specific features of the GOOSE traffic in IEC 61850 substations. The statistical AD is capable of detecting anomalies at unknown change times under the realistic assumption of unknown model parameters. The performance of both variants of the AD method is validated and assessed using data collected from a simulation case study. We perform several Monte-Carlo simulations under different noise variances. The detection delay is provided for each detector and it represents the number of discrete time samples after which an anomaly is detected. In fact, our statistical AD method with both variants (CUSUM and GLRT) has around half the false positive rate and a smaller detection delay when compared with two of the closest works found in the literature. Our AD approach based on the GLRT detector has the smallest false positive rate among all considered approaches. Whereas, our AD approach based on the CUSUM test has the lowest false negative rate thus the best detection rate. Depending on the requirements as well as the costs of false alarms or missed anomalies, both variants of our statistical detection method can be used and are further analyzed using composite detection metrics.

IEC 61850 electrical substations↗
DOE OSTI2021

Modeling Data Flows with Network Calculus in Cyber-Physical Systems: Enabling Feature Analysis for Anomaly Detection Applications

The electric grid is becoming increasingly cyber-physical with the addition of smart technologies, new communication interfaces, and automated grid-support functions. Because of this, it is no longer sufficient to only study the physical system dynamics, but the cyber system must also be monitored as well to examine cyber-physical interactions and effects on the overall system. To address this gap for both operational and security needs, cyber-physical situational awareness is needed to monitor the system to detect any faults or malicious activity. Techniques and models to understand the physical system (the power system operation) exist, but methods to study the cyber system are needed, which can assist in understanding how the network traffic and changes to network conditions affect applications such as data analysis, intrusion detection systems (IDS), and anomaly detection. In this paper, we examine and develop models of data flows in communication networks of cyber-physical systems (CPSs) and explore how network calculus can be utilized to develop those models for CPSs, with a focus on anomaly and intrusion detection. This provides a foundation for methods to examine how changes to behavior in the CPS can be modeled and for investigating cyber effects in CPSs in anomaly detection applications.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Advanced-Research-on-Integrated-Energy-Systems-Based Analysis to Support Resilient System Upgrades: Energy to Communities Energyshed In-Depth Partnership with Molokai, Hawaii

The Molokai, Hawaii, Energy to Communities (E2C) Energyshed project represents a collaborative effort between the National Laboratory of the Rockies, Shake Energy Collaborative, the Molokai Clean Energy Hui, Sustainable Molokai, and Ho'ahu Energy Cooperative Molokai to advance Molokai's Community Energy Resilience Action Plan (CERAP). Supported by Hawaiian Electric Company and the Hawaii State Energy Office, the initiative aims to develop a community-defined portfolio of renewable energy solutions that enhance energy resilience while aligning with the Hawaiian Electric Integrated Grid Plan (IGP) and Molokai's energy goals. Phase 1 focused on technical analyses and community engagement to co-design feasible energy scenarios. Challenges such as grid upgrades, storage sizing, and inverter ride-through standards were addressed to align technical and operational requirements with community preferences. The project equips Molokai with actionable data and insights to implement energy initiatives while ensuring resilient and culturally informed solutions. Future efforts aim to finalize project designs, secure interconnection agreements, and deploy energy projects that reflect community priorities and technical feasibility.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

2022 Small Turbine Certification Awardee: NPS Solutions

Inverters convert the direct current power generated by wind turbines into the alternating current needed to serve local loads and feed onto the electricity grid. Although distributed wind systems typically supply electricity for homes and businesses near the turbines, these systems can also provide clean power to strengthen grid resilience. Certification to UL 1741 SA ensures that inverters will enable distributed wind turbines to provide grid support services and stay online when the grid experiences stability issues. Small companies often find the electrical listing process too complex and expensive to undertake on their own, so few distributed wind turbine inverters are certified to this standard. A U.S. Department of Energy (DOE) Competitiveness Improvement Project (CIP) award is helping NPS Solutions (NPS) secure this critical certification for the inverter in its 100-kilowatt NPS 100C wind turbine, which is optimized for on-site generation at farms, businesses, schools, hospitals, and remote locations.

CIP↗
DOE OSTI2024

Cybersecurity Lessons Learned from Vehicle to Grid Engagement

As the transportation industry continues to become electrified, introduction of additional digital devices within associated actions such as recharging bring additional potential for cybersecurity attacks. Devices that are designed, implemented, and operated with cybersecurity as a crucial consideration exacerbate these concerns by failing to provide strict boundaries on access to and use of the equipment. Emerging use cases such as Vehicle to Grid (V2G) charging may expand the potential physical effects of a cybersecurity attack by providing indirect access to electrical components of a building microgrid or portions of the larger power grid. This paper serves as an overview of findings and recommendations based on cybersecurity testing performed at a V2G implementation site operated by a member of the Memorandum of Understanding (MOU) to Establish the Vehicle-to-Everything (V2X) Collaboration [1]. The Department of Energy Office of Cybersecurity, Energy Security, and Emergency Response is a signatory of the MOU, and has funded this research paper and associated body of work regarding V2X cybersecurity. Sandia has a large background of previous research focused on Electric Vehicle (EV) cybersecurity, such as reference [2], which includes an overall survey of EV infrastructure cybersecurity and recommendations based on those findings. This report seeks to expand knowledge of EV cybersecurity status and needs by focusing on a specific implementation of V2G charging, and providing recommendations based on the relevant findings. This report serves as a publicly available, sanitized description of applied vulnerability testing on an operational V2G implementation. A more in-depth technical version of the report is provided to the MOU partner, but not available at the time of writing due to inclusion of proprietary information. V2G charging comes with many research problems that must be solved before the technology can securely implemented in sites with unrestricted public access or where cybersecurity attacks could have increased consequences, such as government offices. V2G charging requires many stakeholders such as end users, host sites, equipment vendors, and integrators, which all rely on operational safety and security as well as security and trustworthiness of any associated financial transactions.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2022

Review of Electric Vehicle Charger Cybersecurity Vulnerabilities, Potential Impacts, and Defenses

Worldwide growth in electric vehicle use is prompting new installations of private and public electric vehicle supply equipment (EVSE). EVSE devices support the electrification of the transportation industry but also represent a linchpin for power systems and transportation infrastructures. Cybersecurity researchers have recently identified several vulnerabilities that exist in EVSE devices, communications to electric vehicles (EVs), and upstream services, such as EVSE vendor cloud services, third party systems, and grid operators. The potential impact of attacks on these systems stretches from localized, relatively minor effects to long-term national disruptions. Fortunately, there is a strong and expanding collection of information technology (IT) and operational technology (OT) cybersecurity best practices that may be applied to the EVSE environment to secure this equipment. In this paper, we survey publicly disclosed EVSE vulnerabilities, the impact of EV charger cyberattacks, and proposed security protections for EV charging technologies.

33 ADVANCED PROPULSION SYSTEMS↗