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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Resilience in an Evolving Electrical Grid

Fundamental shifts in the structure and generation profile of electrical grids are occurring amidst increased demand for resilience. These two simultaneous trends create the need for new planning and operational practices for modern grids that account for the compounding uncertainties inherent in both resilience assessment and increasing contribution of variable inverter-based renewable energy sources. This work reviews the research work addressing the changing generation profile, state-of-the-art practices to address resilience, and research works at the intersection of these two topics in regards to electrical grids. The contribution of this work is to highlight the ongoing research in power system resilience and integration of variable inverter-based renewable energy sources in electrical grids, and to identify areas of current and further study at this intersection. Areas of research identified at this intersection include cyber-physical analysis of solar, wind, and distributed energy resources, microgrids, network evolution and observability, substation automation and self-healing, and probabilistic planning and operation methods.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Application of Mobile Energy Storage for Enhancing Power Grid Resilience: A Review

Natural disasters can lead to large-scale power outages, affecting critical infrastructure and causing social and economic damages. These events are exacerbated by climate change, which increases their frequency and magnitude. Improving power grid resilience can help mitigate the damages caused by these events. Mobile energy storage systems, classified as truck-mounted or towable battery storage systems, have recently been considered to enhance distribution grid resilience by providing localized support to critical loads during an outage. Compared to stationary batteries and other energy storage systems, their mobility provides operational flexibility to support geographically dispersed loads across an outage area. This paper provides a comprehensive and critical review of academic literature on mobile energy storage for power system resilience enhancement. As mobile energy storage is often coupled with mobile emergency generators or electric buses, those technologies are also considered in the review. Allocation of these resources for power grid resilience enhancement requires modeling of both the transportation system constraints and the power grid operational constraints. These aspects are discussed, along with a discussion on the cost–benefit analysis of mobile energy resources. The paper concludes by presenting research gaps, associated challenges, and potential future directions to address these challenges.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

An Advanced Synchronized Time Digital Grid Twin Testbed for Relay Misoperation Analysis of Electrical Fault Type Detection Algorithms

Distributed energy resources and the number of relays are expected to rise in modern electrical grids; consequently, relay misoperations are also expected to grow. Relays can detect electrical fault types using an internal algorithm and can display the result using light indicators on the front of the relay. However, some relays’ internal algorithms for predicting types of electrical faults could be improved. This study assesses a relay’s external and internal algorithms with an Advanced Synchronized Time Digital Grid Twin (ASTDGT) testbed with paired relays. A misoperation relay analysis focused on measuring the accuracy of using the boundary admittance (the external algorithm) versus the set-default (the internal algorithm) relay method to determine the electrical fault types was performed. In this study, the internal and external relay algorithms were assessed with a synchronized time digital grid twin testbed using a real-time simulator. This testbed evaluated two sets of logic at the same time with the digital grid twin and paired relays in the loop. Different types of electrical faults were simulated, and the relays’ recorded events and electrical fault light indicator states were collected from the human–machine interfaces. This ASTDGT testbed with paired relays successfully evaluated the relay algorithm misoperations. The boundary admittance method had an accuracy of 100% for line-to-line, line-to-ground, and line-to-line ground faults.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

The Sonora Substellar Atmosphere Models. II. Cholla: A Grid of Cloud-free, Solar Metallicity Models in Chemical Disequilibrium for the JWST Era

Exoplanet and brown dwarf atmospheres commonly show signs of disequilibrium chemistry. In the James Webb Space Telescope (JWST) era, high-resolution spectra of directly imaged exoplanets will allow the characterization of their atmospheres in more detail, and allow systematic tests for the presence of chemical species that deviate from thermochemical equilibrium in these atmospheres. Constraining the presence of disequilibrium chemistry in these atmospheres as a function of parameters such as their effective temperature and surface gravity will allow us to place better constraints on the physics governing these atmospheres. This paper is part of a series of works presenting the Sonora grid of atmosphere models. In this paper, we present a grid of cloud-free, solar metallicity atmospheres for brown dwarfs and wide-separation giant planets with key molecular species such as CH 4 , H 2 O, CO, and NH 3 in disequilibrium. Our grid covers atmospheres with T eff ∈ [500 K, 1300 K], log g ∈ [3.0, 5.5] (cgs) and an eddy diffusion parameter of logK zz = 2,4 and 7 (cgs). We study the effect of different parameters within the grid on the temperature and composition profiles of our atmospheres. We discuss their effect on the near-infrared colors of our model atmospheres and the detectability of CH 4 , H 2 O, CO, and NH 3 using the JWST. We compare our models against existing MKO and Spitzer observations of brown dwarfs and verify the importance of disequilibrium chemistry for T dwarf atmospheres. Finally, we discuss how our models can help constrain the vertical structure and chemical composition of these atmospheres.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Medium Voltage Testbed for Comparing Advanced Power Line Sensors vs. Transformers with Electrical Grid Events

Electrical utilities have relied upon potential transformers (PTs) and current transformers (CTs) for very accurate metering and to provide reliable signals for protective relays. These devices measure phase voltages and currents and are commissioned by electrical engineers. PTs/CTs can detect and react to various electrical anomalies that could adversely affect electrical grid operations. Less expensive alternative sensing technologies offer the possibility of wider deployment, particularly in grids that employ distributed energy resources. In this work, the performance of an advanced medium-voltage sensor is compared with that of a reference PT and a CT and experimentally evaluated for different power grid scenarios on an advanced outdoor power line sensor testbed at the U.S. Department of Energy’s Oak Ridge National Laboratory. The sensor is based on a capacitive divider for voltage monitoring and a Rogowski coil with an integrator for current monitoring. This study simulated a power grid model based on a utility circuit at the Riverside EPB of Chattanooga. The simulation circuit was created with MATLAB/Simulink software and was integrated into an RT-LAB project to run with the OP4510 real-time simulator at the OPLST. During the tests, the real-time simulations were run for 40 s, and the signal to record the test event with the power meter was set at 30 s for the event-trigger circuit. The advanced outdoor power line sensor testbed has a real-time simulator that is used to generate transient scenarios (e.g., electrical faults, capacitor bank operation, and service restoration), while the analog signals are recorded by the same high-resolution power meter. The behaviors of analog signals, harmonic components, total harmonic distortion, and crest factors are assessed for this power line sensor and compared with those of the reference PT/CT because of the absence of testing standards for advanced outdoor power line sensors. The results showed that this OPLS technology responded identically to the PT and CT under all conditions.

Piesciorovsky, Emilio [ORNL]↗
DOE OSTI2020

Mathematical Models for Optimization of Grid-Integrated Energy Storage Systems

Energy storage has been proven to yield positive effects on planning, operation and control of electric grids. It has become a crucial task to properly model the energy storage systems (ESS) under the framework of grid optimization on transmission and distribution networks including microgrids. This paper presents a review on mathematical models and test cases of ESSs used for grid optimization studies, where the network constraints of power systems are included. The existing ESS models are mainly classified into two categories – linear and nonlinear models. The two main categories are further divided into several subcategories respectively; such as mixed-integer linear and convex nonlinear sub-categories. Based on the review and discussions, this paper aims at providing suggestions for choosing proper ESS models for specific grid optimization studies considering the chosen power network model.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Modeling the Interaction Between Energy Efficiency and Demand Response on Regional Grid Scales: Preprint

With increasing penetration of intermittent renewable generation at grid and distributed scales, flexible building loads can provide significant system value and support the evolving needs of the grid. The growing value of load flexibility may complicate the traditional separation between energy efficiency (EE) and demand response (DR). EE measures may compete in some cases with a building’s DR capabilities but complement one another in other cases. EE can also increase or decrease the need for DR at the system level and change the availability of DR to meet system needs. In this study we present a bottom-up approach to modeling interactive effects between EE and DR in buildings within two regions of the US electricity grid. From a library of building simulation models for different buildings and climates, we synthesize system-level demand profiles and the impacts of potential future EE portfolios. Coupling the underlying building models with a database of DR-enabling technologies, we then compute the quantity of DR that can be delivered in each scenario. The results show that EE and DR interactions are largely driven by the timing of EE savings that are measure-specific and the coincidence with system peak demand that is region-specific. We also find that perspective of the impacts matters – for instance that some EE measures reduce the system need for DR but also reduce the DR potential. Our results imply that utility EE and DR programs developed without considering interactive effects may lead to increased grid-management challenges over the long term.

buildings↗
DOE OSTI2021

Method and system for determining a geographical location of an unmanned aerial vehicle flown in proximity to a power grid

A method for determining geolocation of a UAV near a power grid includes detecting, via a transceiver, a carrier signal transmitted from a first grid node to identify the node's fixed geolocation. A response signal may be transmitted from a second grid node in response to the carrier signal to identify a fixed geolocation of the second grid node, or the UAV may process the carrier signal. A processor determines time-of-flight of the carrier signal, e.g., using the response signal, and derives the UAV's geolocation using the time-of-flight. Determining time-of-flight may include referencing a lookup table indexed by time-of-arrival at the transceiver of the modulated carrier and response signals. A timestamp may indicate time-of-transmission of the carrier and response signals, respectively. Deriving geolocation may include subtracting time-of-transmission of the response signal from that of the carrier signal. A system includes the processor and transceiver.

Moore, Andrew J.↗
DOE OSTI2022

A Distributed Trust Model Simulator for Energy Grid of Things Distributed Energy Resource Management System

The evolution of networks into more distributed, self-reliant nodes has mitigated single-point failures that plagued traditional centralized networks. Applied to power grids, distributed systems can increase the integrity and availability of grid services while also offering a power management solution. However, while distributed networks provide scalability, security, and sustainability compared to centralized networks, their distributed nature makes them harder for anomaly detection and prevention. Incorporating a Distributed Trust Model (DTM) System into an Energy Grid of Things Distributed Energy Resource Management System (EGOT DERMS) allows grid participants to be characterized and their communication to be analyzed for possible attacks. A Trust Model simulator is needed to evaluate and improve the DTM System.Trustworthiness is calculated using a Trust Model. While many trust models exist, most only consider 2-3 matrices to evaluate trust. The TM proposed in this thesis uses a Metric Vector of Trust (MVoT) monitoring 17 parameters when assessing trust. Moreover, unlike standard trust models, the proposed trust model establishes a method to test the trust between various actors within the network and probe the trust model itself. Using a Trust Model Simulator, MVoT calaculations, initial values, and parameters are fine-tuned to achieve high-confidence message classifications and minimize false positives. The DTM System and Trust Mode Simulation Suite allow for distributed trust evaluation with a real-time classification of EGOT DERMS actors, providing additional security for distributed systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Synchrophasors-based Master State Awareness Estimator for Cybersecurity in Power Grid: Testbed Implementation & Field Demonstration

The integration of distributed energy resources(DERs) and expansion of complex network in the distribution grid requires an advanced distributed state estimator to monitor the grid health at micro-level. The distribution state estimator will improve the situational awareness and resiliency of distributed power system. This paper proposes a synchrophasors-based master state awareness (MSA) estimator to enhance the cybersecurity in distribution grid by providing a real-time estimation of system operating states to control center operators. In this paper, the proposed MSA estimator utilizes only phasor measurements, bus magnitudes and angles, from phasor measurement units (PMUs),deployed in local substations, to estimate the system states and also detects data integrity attacks, such as load tripping attack that disconnects the load. To validate the proof of concept, we implement the proposed methodology in cyber-physical testbed environment at the Idaho National Laboratory (INL) Electric Grid Security Testbed. Further, to address the “valley of death” and support technology commercialization, field demonstration is also performed at the Critical Infrastructure Test Range Complex(CITRC) at the INL. Our experimental results reveal a promising performance in detecting load tripping attack and providing an accurate situational awareness through an alert visualization dashboard in real-time

42 ENGINEERING↗
DOE OSTI2022

Field Study of Grid-connected Heat Pump Water Heaters in the Southeast U.S.: The Next Right Thing

The integration of grid-connected functionality and advanced control algorithms into heat pump water heaters (HPWH) offers the capability to shift load with minimal customer impact. This capability provides a flexible grid resource to utilities, while the increased energy efficiency of HPWHs offers customers a lower electric bill. The combined utility/customer value from grid-connected HPWHs is compelling in the Southeast U.S. where residential electric water heating is prevalent and utility load management is common. This paper presents the results of a HPWH load shifting study conducted in Central Florida using the CTA-2045 standard. Building upon previous research in the Pacific Northwest, this study consisted of approximately 45 occupied homes equipped with HPWHs undergoing load shifting strategies weekly for over a year. Curtailment durations ranged from three to five hours in the morning, and four to five hours in the evening to coincide with high-value periods for utility coincident load for system-wide electric demand reductions. During the morning and afternoon, a one- or two-hour load-up event preceded curtailment. Baseline data were collected across varied Florida weather in which no load shifting events were implemented. Results from traditional load shifting strategies were analyzed across seasons and used to devise unique load shifting approaches to increase renewable energy use during periods of high solar energy generation. Regional impacts are forecasted for large-scale implementation of strategies. Lessons learned and recommendations are also provided for how utilities, manufacturers, and regional planners can maximize load shifting benefits from grid-connected HPWHs.

Heat pump water heaters, residential building, loa↗
DOE OSTI2021

Distributed, Intelligent Edge-Sensing for a Smarter Grid

The electric grid is undergoing major transformations and developments resulting in unprecedented levels of volatility, uncertainty, and stress on grid infrastructure. Smart sensors and methods aiding in advanced visibility and situational awareness are key for tackling these issues. In this work, a decentralized architecture is proposed, where sensing, local computation and control capability are embedded in the edge devices, communicating with a set of trusted 'data mules' in a 'delay-tolerant' manner, while functioning autonomously. This system has been designed and implemented as an overall platform – called Global Asset Monitoring, Management and Analytics (GAMMA) Platform intended to provide the backbone for a global array of sensors and actuators. Further, as a building block for advanced current sensing solutions, a smart, low-cost ‘clip-on’ current sensor based on PCB-embedded Rogowski coil has been developed. The sensor hosts a novel signal conditioning stage allowing an 'auto-tuning' feature, resulting in a universal current sensor design for measuring a wide range of currents, including faults for smart grid applications. Finally, the research proposes a method to instrument and monitor key parameters for the most common electric utility asset – the pole-top distribution transformer. The work done in this research enables scalable, edge-intelligent sensing solutions for monitoring grid infrastructure, allowing utility operators to gain advanced visibility in an economical way.

Kulkarni, Shreyas Bhalchandra↗
DOE OSTI2023

AI-Driven Smart Community Control for Accelerating PV Adoption and Enhancing Grid Resilience

The U.S. Department of Energy (DOE) has launched a Connected Communities program that supports projects that expand DOE's network of grid-interactive, efficient building communities nationwide. As an early pilot of Connected Communities, the National Renewable Energy Laboratory (NREL) and its partners have developed and demonstrated a community-scale, hierarchical control solution to address the potential grid issues arising from high penetration of solar photovoltaics (PV) as well as to improve grid reliability and resilience in this residential community. A field pilot study has been performed at an affordable housing development called the Basalt Vista Community, which was built for school teachers and other professionals in the local workforce and represents an autonomous energy grid with all-electric, energy-efficient homes. With no natural gas line in the community, this is the first all-electric net-zero community in rural Colorado. In the field pilot study, NREL has validated the performance of the hierarchical control solution, which consists of NREL's foresee home energy management systems (HEMS) and community aggregators, in increasing demand flexibility and self-consuming PV, reducing potential over-voltages, and supporting critical loads during emergency events. In this presentation, we will present the methodology, simulation and field pilot results, and lessons learned from the project.

all-electric community↗
DOE OSTI2020

Autonomous Intelligent Charging/Discharging of Electric Vehicles using Distributed Multi-Agent ADMM Framework for Grid Ancillary Services

The increasing popularity of Electric Vehicles (EVs) in the distribution grid along with technological advancement in EV electronics such as vehicle to grid (V2G) technique has enabled them to participate in grid ancillary services. To achieve this, the EVs need to establish a contract with third-party aggregators and connect to a charging unit, either residential or commercial. At any time they are connected, the EVs can decide to take part in the ancillary services program offered to them by the aggregators. If agreed, the aggregators will use the EVs as a power source capable of charging/discharging power according to the input signal, and in return, they will be compensated. This inter-temporal nature of charging/discharging is also transforming the traditional optimal power flow (OPF) problem into a dynamic OPF problem. This chapter aims at developing a multi-layer time-dependent optimization algorithm to utilize EV potential and provide ancillary services while maximizing its utilization function. Specifically, in the upper layer, an autonomous distributed ADMM algorithm is developed to optimize the cost for charging/discharging EVs while using them to regulate the voltage at each bus in the distribution grid. The distributed ADMM algorithm is also expanded to the lower layer where the individual EVs active and reactive power is controlled for voltage regulation while maintaining the desired state of the charge of the vehicle at the end of the charging period. Here, the effectiveness and performance improvement of the proposed multi-layer algorithm is illustrated through analytical analysis and simulation results.

Rahman, Towfiq↗
DOE OSTI2020

Autonomous Intelligent Charging/Discharging of Electric Vehicles using Distributed Multi-Agent ADMM Framework for Grid Ancillary Services

The increasing popularity of Electric Vehicles (EVs) in the distribution grid along with technological advancement in EV electronics such as vehicle to grid (V2G) technique has enabled them to participate in grid ancillary services. To achieve this, the EVs need to establish a contract with third-party aggregators and connect to a charging unit, either residential or commercial. At any time they are connected, the EVs can decide to take part in the ancillary services program offered to them by the aggregators. If agreed, the aggregators will use the EVs as a power source capable of charging/discharging power according to the input signal, and in return, they will be compensated. This inter-temporal nature of charging/discharging is also transforming the traditional optimal power flow (OPF) problem into a dynamic OPF problem. This chapter aims at developing a multi-layer time-dependent optimization algorithm to utilize EV potential and provide ancillary services while maximizing its utilization function. Specifically, in the upper layer, an autonomous distributed ADMM algorithm is developed to optimize the cost for charging/discharging EVs while using them to regulate the voltage at each bus in the distribution grid. The distributed ADMM algorithm is also expanded to the lower layer where the individual EVs active and reactive power is controlled for voltage regulation while maintaining the desired state of the charge of the vehicle at the end of the charging period. The effectiveness and performance improvement of the proposed multi-layer algorithm is illustrated through analytical analysis and simulation results.

Rahman, Towfiq↗
DOE OSTI2026

Responsible Adoption of Artificial Intelligence (AI) in Electric Grid Operations

The future of the grid will be powered by AI—or undermined by it. Artificial intelligence is rapidly reshaping grid operations, improving fault detection, forecasting accuracy, and real-time optimization. As AI systems move closer to operational decision loops, however, they introduce new consequence pathways: expanded attack surfaces, model integrity risks, regulatory exposure, and human-automation challenges. This talk presents a consequence-driven framework for deploying AI responsibly in the electric grid. Attendees will gain practical strategies to strengthen resilience, boost reliability, and deploy AI securely — ensuring the grid of the future is not only smarter but safer.

25 - ENERGY STORAGE↗
DOE OSTI2026

Integrating AI Data Centers with the Power Grid

The rapid expansion of artificial intelligence (AI) has triggered an unprecedented surge in electricity demand, with US data center energy use projected to double or triple 2023 levels by 2028. This exponential growth places strain on grid infrastructure, which can hinder timely construction of desired computing capacity. To bridge this supply-demand gap, utilities and AI developers are increasingly turning to demand flexibility, a strategy that incentivizes shifting or reducing power use during peak periods of grid stress. Data centers are uniquely equipped for flexible operations due to their digital workloads, built-in redundancy, and onsite energy assets. This article outlines four primary mechanisms to enable data center flexibility: computational load flexibility (shifting tasks temporally or geographically), flexible use of core facility infrastructure adjustments, energy storage utilization, and onsite electricity generation. To encourage adoption, utilities are deploying new tariff designs, including voluntary interruptible service riders, mandated flexibility requirements, and streamlined interconnection processes for flexible loads. For the highly capitalized and rapidly growing AI industry, the primary motivators for embracing these strategies are expediting facility interconnection, satisfying emerging regulatory mandates, and mitigating community resistance. While demand flexibility cannot substitute the long-term need for new bulk power generation, it serves as an essential, immediate solution for enabling near-term deployment. By transforming data centers from grid stressors into stabilizing assets, flexible operations can ensure reliable grid integration, ease market pressures, and support a resilient power system.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Modeling simultaneous particle shrinkage, dissolution and breakage using the modified moving grid technique

Simultaneous shrinkage, dissolution and breakage are important particle size reduction phenomena that characterize processes like the reactive degradation of solid chemicals. The dynamics of the particle size distribution (PSD) for such processes are non-trivial to model due to the number expending processes brought about by the eventual dissolution of particles. To this end, Population Balance Model (PBM) resolved through the sectional techniques is the natural approach. Here, we introduce a modified Moving Grid technique (m-MGT) to accurately resolve the particle size reduction phenomena. Our technique mimics the perpetual particle shrinkage through a continuously left-moving size grid and incorporates a strategic grid removal routine to capture the disappearance of particles. Coupled with the Fixed Pivot (FP) discretization for breakage, our m-MGT not only preserves the moment-related properties, but also benchmarked very well against the analytical number densities and exhibited a minimum of first-order convergence in all assessed case studies.

97 MATHEMATICS AND COMPUTING↗