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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 523 records · Page 29
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A Sequential Model Predictive and Deep Reinforcement Learning-Based Controller for Distribution System Outage Mitigation under Hurricane Events

This paper proposes a proactive outage mitigation framework for power distribution networks to withstand hurricane-induced disruptions. It leverages Model Predictive Control (MPC) to identify safe lines for proactive switching during hurricanes, minimizing the risk of cascading failures and voltage violations. The switching strategies optimized by MPC are sequentially integrated with a Deep Reinforcement Learning agent using the Advantage Actor-Critic algorithm, enabling dynamic line switching to maximize connected buses and minimize voltage violations in real time. Using a probabilistic hurricane model, the framework predicts line failures and adapts to varying conditions to enhance grid resilience. Simulations on the IEEE 123-bus system demonstrate its effectiveness in maintaining high connectivity and minimizing disruptions. Real-time testing with an RTDS confirms the practicality and reliability of the proposed approach.

Selim, Alaa [University of Connecticut]↗
DOE OSTI2023

Subordinated Gaussian Processes for Solar Irradiance

Traditionally the power grid has been a one-way street with power flowing from large transmission-connected generators through the distribution network to consumers. This paradigm is changing with the introduction of distributed renewable energy resources (DERs), and with it, the way the grid is managed. There is currently a dearth of high fidelity solar irradiance datasets available to help grid researchers understand how expansion of DERs could affect future power system operations. Realistic simulations of by-the-second solar irradiances are needed to study how DER variability affects the grid. Irradiance data are highly non-stationary and non-Gaussian, and even modern time series models are challenged by their distributional properties. We develop a subordinated non-Gaussian stochastic model whose simulations realistically capture the distribution and dependence structure in measured irradiance. We illustrate our approach on a fine resolution dataset from Hawaii, where our approach outperforms standard nonlinear time series models.

MATHEMATICS AND COMPUTING,SOLAR ENERGY↗
DOE OSTI2024

A Comprehensive Strategy for Grid Forming Control in DC Coupled Photovoltaic and Battery Energy Storage Inverters

This paper presents an integrated DC-DC and DCAC grid-forming control strategy for DC-coupled photovoltaic (PV) plus battery energy storage systems, considering the effect of DC link voltage variations caused by direct PV connections. A power reference algorithm determines power distribution between the PV and battery to the grid while observing device power ratings to prevent the over-rating of components and keep the battery's state of charge within an acceptable range. The simulated utility-scale model in MATLAB/Simulink illustrates its ability against extreme phase angle variation contingencies in the grid while controlled through grid-forming control with a fast dynamic on DC link voltage. The simulation results confirm the effectiveness of the proposed control in integrating PV plus battery configurations with grid forming control and maintaining reliable grid operation under severe grid disturbances.

battery, boost, control, energy storage, grid form↗
DOE OSTI2025

Towards improved neutral exhaust in the HSX stellarator

To improve our knowledge of neutral exhaust in non-resonant divertors, a particle exhaust study is performed for the Helically Symmetric eXperiment (HSX). The chaotic magnetic field topology in the plasma edge is examined with connection lengths and Lyapunov exponents. Plasma flux tubes are identified and these flux tubes deposit particles onto plasma facing components. This helps determine the areas where neutrals are generated and provides guidance on where to put baffles. As shown using EMC3-EIRENE simulations, the introduction of baffles can help increase the neutral pressure at and away from the strike line locations. Furthermore, it is demonstrated that baffle design cannot only be based on placing structures at locations with small connection lengths.

Baffles↗
DOE OSTI2024

Decoupling Power Quality Issues in Grid-Microgrid Network Using Microgrid Building Blocks

Microgrids are evolving as promising options to enhance reliability of the connected transmission and distribution systems. Traditional design and deployment of microgrids require significant engineering analysis. However, Microgrid Building Blocks (MBB), consisting of modular blocks that integrate seamlessly to form effective microgrids, are promising technologies to enable faster and broader adoption of microgrids. Back-to-Back converter placed at the point of common coupling of microgrid is an integral part of MBB. This paper presents applications of MBB to decouple power quality issues in grid-microgrid network serving power quality sensitive critical loads such as data centers, new grid-edge technologies such as vehicle-to-grid generation, and emergency condition loads such as electric vehicle charging loads during evacuation prior disaster events. Simulation results show that MBB effectively decouple the power quality issues across networks and allow network with low power quality to transfer high-power quality power to connected networks during emergency conditions.

Acharya, Samrat S. [BATTELLE (PACIFIC NW LAB)]↗
DOE OSTI2023

Smart Data Mapping for Connecting Power System Model and Geospatial Data

Knowing the geospatial locations of power system model elements is the foundation for analyzing system vulnerability to natural hazards and connecting loads with end users and their communities. However, power system models and geospatial data for power grid assets may have been developed asynchronously without close coordination. Creating a direct mapping between the two may be a challenging task, considering heterogeneous data structures, target uses, historical legacies, and human errors. This work aims to build an automatic data mapping workflow to connect power system model elements and geospatial data for transmission network, and to support energy grid resilience studies for Puerto Rico. The primary steps in this workflow include constructing graphs using geospatial data, and aligning them to the transmission networks defined in the power system data. The results have been evaluated against existing manual mapping practices for part of the Puerto Rico Power Grid model to illustrate the performance of such auto-mapping solutions.

Resilience, geospatial data, grid transmission net↗
DOE OSTI2025

Architectural Approaches for Integrating ADMS and DERMS: Challenges, Comparisons, and Real-World Use Cases

The electrical distribution landscape is rapidly transforming due to the proliferation of distributed energy resources (DERs) such as solar panels, wind turbines, battery storage systems, combined heat and power units, and electric vehicles, introducing variability and uncontrollability that traditional grid operators are ill-equipped to manage. This transformation is further accelerated by advancements in Information and Communication Technology infrastructure that connects control centers with end devices, demanding automation and a deeper understanding of new technologies by utility personnel. Advanced grid control techniques using system-level optimization, Artificial Intelligence, and Machine Learning at the enterprise level and distributed level are evolving to address these issues. There is also an opportunity to utilize the enormous data created by these new DER technologies in the grid. Advanced Distribution Management Systems (ADMS) and Distributed Energy Resource Management Systems (DERMS) are critical in addressing these challenges by automating grid operations and enhancing reliability. Given the relatively recent development of ADMS and DERMS, and the still relatively low level of ADMS and DERMS deployment in the industry, there is a notable deficiency in the comprehensive understanding of the challenges and benefits associated with these new technologies, especially with their complementary natures and integration architectures. This paper aims to bridge the knowledge gap in ADMS and DERMS integration, presenting three distinct integration architectures currently available, and discussing the challenges and benefits of each architecture to guide utilities, industry professionals, and researchers in optimizing grid management and decision-making processes for a resilient and efficient energy future.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Optimizing mixed cool thermal storage systems across a connected community

A high level of electric demand flexibility must be integrated into our building infrastructure to enable greater renewable energy penetration in the grid. In the U.S., 9% of electricity generated is used to cool buildings in a periodic manner, making this end-use an ideal target for active management through cool thermal energy storage (CTES) technologies. Historic uses for CTES are designed around central chilled water plants, but these systems cool less than 25% of U.S. commercial floorspace. Emerging technologies are under development to serve the many smaller distributed cooling systems, such as rooftop units (RTUs), and have the potential to add CTES to an additional 66% of cooled commercial floorspace. However, these unitary thermal storage systems (UTSS) lack the modeling and analysis tools to evaluate them in the future interactive grid context. Here, this study develops the modeling and optimization tools necessary to simultaneously examine central and distributed ice storage systems within the multi-building, connected community context. An integrated simulation-optimization workflow is created to allow for rapid customized analysis. Results demonstrate the energy and flexibility tradeoffs of various implementations.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2022

Dynamic Load Inrush Current Mitigation in Islanded Microgrids Powered by Grid-Forming Inverters

Grid-forming inverters in a microgrid may trip due to high inrush current caused by a switched connection of an inductive load, e.g., a relatively large induction motor. The control scheme presented in this article includes virtual inertia control method superimposed on the cascaded controller. This article studies the impact of cascaded control scheme used for grid-forming inverter to mitigate the inrush current effects and enhance the inverter’s robustness for the safe connection of inductive and dynamic loads. Experimental tests are performed using the virtual inertia method for generating the reference angle for synchronous frame conversion. The experimental performance and sensitivity of the controller to different controller gain settings for a switched connection of an induction motor are discussed. The cascaded operation significantly mitigates the inrush currents while the inverters can perform a normal operation. The performance of the control method is tested in a laboratory-scale hardware setup of a 208V microgrid fed by 5kVA and 10kVA inverters, and the results are presented.

Gursoy, Mehmetcan↗
DOE OSTI2022

A Medium Voltage Three-Stage Power Converter Topology for Distribution Grid Scale Energy Storage Systems

This work proposes a three-stage converter topology with a medium frequency isolation transformer for direct integration of energy storage systems into medium voltage distribution grids. The distributed architecture of the topology, using standard AC/DC converters, has been developed with the aim of plug-and-play capability and voltage and power scalability. The medium frequency transformer facilitates improved power density, while its 20:1 voltage translation capability enables the use of limited voltage level (500 Vdc) of the commercially available batteries. This paper presents the topology structure and details how it can be scaled to reach the full range of the distribution grid voltages and the required power levels. A transformer design for 500 Hz rated frequency is discussed. The control scheme of the converter equipped with voltage support, frequency support, and black start capabilities is also presented. Control hardware-in-the-loop results using OPAL-RT, with converter switching models connected to a weak IEEE-4 node test feeder modified for the aforementioned grid services, are provided to show the topology feasibility.

Chinthavali, Madhu Sudhan↗
DOE OSTI2025

Reinforced AEM Separators Based on Triblock Copolymers for Electrode-decoupled RFBs

Washington University in St. Louis (WUSTL), in collaboration with The University of Texas at San Antonio (UTSA) and Giner Inc. developed highly selective anion exchange membranes (AEMs) and a novel electrode-decoupled redox flow battery (RFB) for grid scale energy storage as part of the ARPA-E IONICS program (with connections to the DAYS program in the later part of the project). RFBs exhibit the crucial characteristic of system-level decoupled scaling of energy and power which makes them cost effective for the multi-GWh scales envisioned for grid-scale energy storage solutions. This has led to extensive (and deserved) research interest and attention. This project aimed to enhance the design space available for redox-flow batteries (RFBs) by enabling the long-term separation of disparate cationic (elemental) actives using a highly selective membrane separator, while concurrently permitting the transport of anions to balance charge. The approach proposed was to design and develop a highly selective anion-exchange membrane (AEM), which would in turn permit the design and development of electrode-decoupled RFBs. Pairs of (different element) cationic species with redox reactions exhibiting a large difference in their standard electrode potentials were identified to develop high voltage, high power RFBs while disrupting the existing paradigm of using a single element which can ionize to more than two soluble oxidation states (e.g.: Vanadium).

25 ENERGY STORAGE↗
DOE OSTI2024

A Novel Authentication Management for the Data Security of Smart Grid

Bidirectional wireless communication is employed in various smart grid components such as smart meters and control and monitoring applications where security is vital. The Trusted Third Party (TTP) and wireless connectivity between the smart meter and the third party in the key management-based encryption techniques for the smart grid are expected to be totally trustworthy and dependable. In a wired/wireless medium, however, a man-in-the-middle may seek to disrupt, monitor and manipulate the network, or simply execute a replay attack, revealing its vulnerability. Recognizing this, this study presents a novel authentication management (model) comprised of two layer security schema. The first layer implements an efficient novel encryption method for secure data exchange between meters and control center with the help of two partially trusted simple servers (constitutes the TTP). In this setting, one server handles the data encryption between the meter and control center/central database, and the other server administers the random sequence of data transmission. The second layer monitors and verifies exchanged data packets among smart meters. It detects abnormal packets from suspicious sources. To implement this node-to-node authentication, One class support vector machine algorithm is proposed which takes advantages of the location information as well as the data transmission history (node identification, packet size, and data transmission frequency). This schema secures data communication, and imposes a comprehensive privacy throughout the system without considerably extending the complexity of the conventional key management scheme.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Maximum-impact Adversary Design for Network-based Control System: A Case Study on Grid-interactive Efficient Buildings

The Internet of Things (IoT) technology has dramatically improved the efficiency of today's building operation and management. By connecting controllable devices into a communication network, control signals can be easily passed to the devices, and operating status can be acquired from measurable ends with minimal effort. However, this all-connected configuration could also expose the network-based control system (NBCS) to malicious actions, such as cyberattacks. One of the common NBCSs is the building automation system. With the promotion of grid-interactive efficient buildings (GEBs), there has been increasing attention on securing the buildings from the network perspective. This research proposes a maximum-impact adversary design framework so that the adversary can provide the most adversarial impact on the controlled system while remaining stealthy. The proposed framework is numerically demonstrated on a network-based building energy and control system. The building energy system is built in a Modelica-based simulation environment and controlled by the state-of-the-art ASHRAE Guideline 36 control sequences. The control commands at the supervisory level, generated from the Guideline 36 controller, are assumed to be sent to local devices through communication networks using the BACnet protocol. Simulation results show that the proposed maximum-impact adversary on such a system can stealthily affect the building system's performance to its maximum extent. It is anticipated that results can be used by researchers and practitioners in the building automation industry to design efficient and robust cyber-attack detection algorithms, especially for stealthy attacks.

Chu, Mengyuan↗
DOE OSTI2022

Evaluation of Optimal Net Load Management in Microgrids Using Hardware-in-the-Loop Simulation: Preprint

This paper presents the performance evaluation of a net load management (NLM) engine that balances load and generation in an isolated community to power a critical facility after a grid interruption event (e.g., lost a large generation unit). The NLM engine is a central dispatch control system that provides high-speed cost-optimal coordination of a set of net loads (combination of generation and deferrable loads) connected to the same electrical network. The NLM algorithm cost-optimally dispatches the grid-following inverters and deferrable loads based on the demanded power and load priorities, and the grid-forming inverters use droop control to form system voltages and share active and reactive power. A controller-hardware-in-the-loop platform is developed to evaluate the control performance of the NLM algorithm. The experimental results indicate that the NLM engine can achieve the targeted system voltage and frequency and balance load and generation to serve the critical facility.

droop control↗
DOE OSTI2022

Peer-to-Peer Communication Trade-Offs for Smart Grid Applications: Preprint

Peer-to-peer energy management systems for smart grids require developers to consider the trade-offs between the amount of communication traffic generated and the quality and speed of convergence of the control algorithms that are deployed. Employing a fully connected communication causes messages to scale exponentially with the number of nodes, while using a sparse connectivity causes less information dissemination leading to degradation of the algorithm performance. The best communication topology for a particular application lies somewhere in between and often requires empirical evaluation by application designers. Existing methods do not put focus on the needs for smart grid applications, which is information dissemination throughout the network and they do not provide a flexible solution for application developers to prototype and deploy different topologies without modifying the application code. This paper introduces a configurable virtual communication topology framework TopLinkMgr, allowing users to specify any chosen communication topology and deploy peer-to-peer applications using it. It also introduces a self-adaptive, fault-tolerant topology management algorithm, Bounded Path Dissemination that can ensure the dissemination of information to all peers within a specified threshold for a sparsely connected topology. Experiments show that the algorithm improves on convergence speed and accuracy over state-of-the-art methods and is also robust against node failures. The results indicate the possibility of achieving a close-to optimal convergence without overloading the network allowing the realization of peer-to-peer control platforms covering larger and more complex power systems.

Bounded Path Dissemination↗
DOE OSTI2020

Smart technologies enable homes to be efficient and interactive with the grid

Oak Ridge National Laboratory researchers compare two different approaches to test how advanced, energy-efficient building technologies such as smart thermostats, heat pump water heaters, and advanced heat pump HVAC (heating, ventilation and air conditioning) can be optimized within a home and connected at a neighborhood-scale load to a community microgrid in the Alabama Power Smart Neighborhood located in Hoover. Working with Southern Company and Alabama Power, ORNL researchers are pioneering that future where smart homes and smart neighborhoods can benefit both homeowners and utilities, by reducing energy consumption by 44% and peak demand by 34%.This project is one of two neighborhoods in the U.S Department of Energy’s (DOE’s) Connected Neighborhood project, supported by Building Technologies Office , where ORNL researchers leverages DOE investment in micro-grids and responsive, flexible building loads research to improve grid reliability – a goal of DOE’s Grid-interactive Efficient Buildings (GEB) Initiative. Researchers control the neighborhood and microgrid to enable utilities achieve their desired load and cost profiles while ensuring the comfort of homeowners in the Smart Neighborhood. This transactive control approach maximizes the utilization of technical resources of the microgrid and controllable loads, while reducing costs for both the homeowners and Alabama Power. These tests partially seek to determine a more precise range of tolerance with respect to occupant comfort as researchers work to facilitate customer acceptance and perception of new building technologies that enable energy savings.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Reducing impacts of artificial ponding in modeling salt marshes using a conductivity-formulated subgrid model

The landforms of salt marsh systems are rather complex, with meandering channel networks cutting through low-lying, extensive marsh platforms. Some small-scale topographic details are critical to flooding and draining processes but cannot be reflected in the Digital Elevation Model (DEM) due to limited measurement resolution and vegetation bias. Numerical models need a grid with high enough resolution to capture the small-scale connectivity to correctly model the small-scale flow processes, making the model computationally unaffordable. Here, in this study, we derived a subgrid model, which couples two flow components, one is the regular subgrid model for simulating the subgrid-resolved flows, and the other is a conductivity-formulated porous flow model for modeling small-scale gut flows unresolved at the subgrid level. The model validation was performed using an idealized case with a narrow slot that was unresolved in the coupled flow model. Model results were compared with a slot-resolved regular subgrid model where only surface flows are solved and suggested that, with a proper model parameterization, the coupled flow model is capable of reproducing flooding and draining processes similar to the slot-resolved subgrid model of surface flow. The model was applied to simulating flooding and draining processes in a meso-tidal salt marsh. The model results demonstrate that the coupled subgrid model can be used to reduce the impacts of artificial ponding that usually occur in numerical simulations of salt marshes with numerous narrow gullies and creeks.

54 ENVIRONMENTAL SCIENCES↗