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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

EVs-at-RISC: A Secure and Resilient Interoperable SCM Control System Architecture for Electric Vehicle’s-at-Scale (Final Technical Report)

The EVs-at-RISC project was a five-year research, development, and demonstration initiative to create foundational tools for utility-scale fleet aggregation and Smart Charge Management (SCM) of Electric Vehicles (EV), Electric Vehicle Charging Infrastructure (EVCI), and related Distributed Energy Resources (DER). Rather than seeking to develop and demonstrate highly perfected SCM algorithms and control strategies, this project instead focused on creating foundational software solutions that enable unprecedented digital interoperability across the communications technologies and vendor platforms used to manage EV , EVCI, and DER, as well as existing energy management infrastructure operated by utilities, grid operators, and aggregators. This project then extends these novel interoperability capabilities to develop and deploy powerful middleware abstractions across grid edge networks and EVCI/DER fleet aggregations incorporating modern software tools and best practices, such as CI/CD, to bring the immense capabilities of infrastructure-as-code and policy-as-code to modern grid edge network environments. This addresses the foremost systemic issues preventing realization of any net operational benefits from scaled deployment of behind-the-meter EV, EVCI, and DER assets in electric power grids and markets today. The results of this approach and project unlock massive potential for new SCM capabilities to be easily prototyped, evaluated, and deployed at-scale within the existing grid edge network infrastructure and EVCI/DER technology ecosystem. The EVs-at-RISC project achieves this by extending Open Field Message Bus (OpenFMB), a conceptual model for digital interoperability and distributed intelligence in traditional front-of-meter utility SCADA networks, validating our hypothesis that OpenFMB could be similarly used to solve systemic digital interoperability issues in behind-the-meter environments and unlock real-world utility-scale SCM capabilities without requiring any new proprietary vendor solutions or significant infrastructure reconfiguration.

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NASA NTRS2003

Contributions of the NASA Langley Research Center to the DARPA/AFRL/NASA/ Northrop Grumman Smart Wing Program

An overview of the contributions of the NASA Langley Research Center (LaRC) to the DARPA/AFRL/NASA/ Northrop Grumman Corporation (NGC) Smart Wing program is presented. The overall objective of the Smart Wing program was to develop smart** technologies and demonstrate near-flight-scale actuation systems to improve the aerodynamic performance of military aircraft. NASA LaRC s roles were to provide technical guidance, wind-tunnel testing time and support, and Computational Fluid Dynamics (CFD) analyses. The program was divided into two phases, with each phase having two wind-tunnel entries in the Langley Transonic Dynamics Tunnel (TDT). This paper focuses on the fourth and final wind-tunnel test: Phase 2, Test 2. During this test, a model based on the NGC Unmanned Combat Air Vehicle (UCAV) concept was tested at Mach numbers up to 0.8 and dynamic pressures up to 150 psf to determine the aerodynamic performance benefits that could be achieved using hingeless, smoothly-contoured control surfaces actuated with smart materials technologies. The UCAV-based model was a 30% geometric scale, full-span, sting-mounted model with the smart control surfaces on the starboard wing and conventional, hinged control surfaces on the port wing. Two LaRC-developed instrumentation systems were used during the test to externally measure the shapes of the smart control surface and quantify the effects of aerodynamic loading on the deflections: Videogrammetric Model Deformation (VMD) and Projection Moire Interferometry (PMI). VMD is an optical technique that uses single-camera photogrammetric tracking of discrete targets to determine deflections at specific points. PMI provides spatially continuous measurements of model deformation by computationally analyzing images of a grid projected onto the model surface. Both the VMD and PMI measurements served well to validate the use of on-board (internal) rotary potentiometers to measure the smart control surface deflection angles. Prior to the final entry, NASA LaRC also performed three-dimensional unstructured Navier Stokes CFD analyses in an attempt to predict the potential aerodynamic impact of the smart control surface on overall model forces and moments. Eight different control surface shapes were selected for study at Mach = 0.6, Reynolds number = 3.25 x 10(exp 6), and + 2 deg., 3 deg., 8 deg., and 10 deg.model angles-of-attack. For the baseline, undeflected control surface geometry, the CFD predictions and wind-tunnel results matched well. The agreement was not as good for the more complex aero-loaded control surface shapes, though, because of the inability to accurately predict those shapes. Despite these results, the NASA CFD study served as an important step in studying advanced control effectors.

Florance, Jennifer P.↗
DOE OSTI2024

A Blockchain and PKI-Based Secure Vehicle-to-Vehicle Energy-Trading Protocol

With the increasing awareness for sustainable future and green energy, the demand for electric vehicles (EVs) is growing rapidly, thus placing immense pressure on the energy grid. To alleviate this, local trading between EVs should be encouraged. In this paper, we propose a blockchain and public key infrastructure (PKI)-based secure vehicle-to-vehicle (V2V) energy-trading protocol. A permissioned blockchain utilizing the proof of authority (PoA) consensus and smart contracts is used to securely store data. Encrypted communication is ensured through transport layer security (TLS), with PKI managing the necessary digital certificates and keys. A multi-leader, multi-follower Stackelberg game-based trade algorithm is formulated to determine the optimal energy demands, supplies, and prices. Finally, we propose a detailed communication protocol that ties all the components together, enabling smooth interaction between them. Key findings, such as system behavior and performance, scalability of the trade algorithm and the blockchain, smart contract execution costs, etc., are presented through numerical results by implementing and simulating the protocol in various scenarios. This work not only enhances local energy trading among EVs, encouraging efficient energy usage and reducing burden on the power grid, but also paves a way for future research in sustainable energy management.

Stackelberg game↗
DOE OSTI2026

Reese Housing Power Project (Final Technical Report)

The Reese Housing Power Project is located on Tribal trust land in Colusa, CA and expands existing medium-voltage distribution to seven new households with the addition of medium-voltage cabling, step down transformers, smart meters, and street lighting for the new development. The Tribe utilized their existing Co-Generation power plant and micro grid to supply the new homes with highly reliable power with fewer interruptions and at a reduced rate compared with the local utility. The project gives the Tribe greater independence from traditional power sources and provides jobs for the community. The project reduces electric energy costs, increases Tribe self-reliance, and provides highly reliable electric power to seven tribal members’ homes. Construction of the project also provided jobs for the community.

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NASA NTRS2000

Patch Network for Power Allocation and Distribution in Smart Materials

The power allocation and distribution (PAD) circuitry is capable of allocating and distributing a single or multiple sources of power over multi-elements of a power user grid system. The purpose of this invention is to allocate and distribute power that is collected by individual patch rectennas to a region of specific power-user devices, such as actuators. The patch rectenna converts microwave power into DC power. Then this DC power is used to drive actuator devices. However, the power from patch rectennas is not sufficient to drive actuators unless all the collected power is effectively used to drive another group by allocation and distribution. The power allocation and distribution (PAD) circuitry solves the shortfall of power for devices in a large array. The PAD concept is based on the networked power control in which power collected over the whole array of rectennas is allocated to a sub domain where a group of devices is required to be activated for operation. Then the allocated power is distributed to individual element of power-devices in the sub domain according to a selected run-mode.

Golembiewski, Walter T.↗
NASA NTRS2002

Aerodynamic Database Development for Mars Smart Lander Vehicle Configurations

An aerodynamic database has been generated for the Mars Smart Lander Shelf-All configuration using computational fluid dynamics (CFD) simulations. Three different CFD codes, USM3D and FELISA, based on unstructured grid technology and LAURA, an established and validated structured CFD code, were used. As part of this database development, the results for the Mars continuum were validated with experimental data and comparisons made where applicable. The validation of USM3D and LAURA with the Unitary experimental data, the use of intermediate LAURA check analyses, as well as the validation of FELISA with the Mach 6 CF(sub 4) experimental data provided a higher confidence in the ability for CFD to provide aerodynamic data in order to determine the static trim characteristics for longitudinal stability. The analyses of the noncontinuum regime showed the existence of multiple trim angles of attack that can be unstable or stable trim points. This information is needed to design guidance controller throughout the trajectory.

Bobskill, Glenn J.↗
DOE OSTI2024

Fast Charging Infrastructure for Electrifying Road Trips to and from National Parks in the Western United States

This study investigated the fast-charging infrastructure needed by 2030 to enable seamless electrified road trips to and from national parks and monuments in seven western states: Washington, Oregon, Idaho, Wyoming, Utah, Nevada, and Arizona. It also estimated impacts to the electric grid. The research team investigated how on-route charging infrastructure projections change with different parameters or assumptions, as do related charging loads and grid impacts. NREL conducted the study in partnership with utility service provider PacifiCorp and Utah State University as part of the Western Smart Regional EV Adoption and Infrastructure at Scale project.

ADVANCED PROPULSION SYSTEMS,ENERGY PLANNING, POLIC↗
DOE OSTI2025

Enhancing Grid Resilience with HIVE: Decentralized V2G Coordination for Black Starts

This paper proposes the HIVE (Harmonized Integration of Vehicle Energy for Grid Support) model, a novel game-theoretic framework for decentralized coordination of electrified vehicles to enable black start and load restoration during grid outages. In the absence of a central controller, HIVE employs a cooperative game to model vehicle interactions, allowing autonomous decision-making while admitting to a Nash equilibrium for grid restoration. The framework addresses the heterogeneity of vehicles and their operational constraints, selecting a lead vehicle for grid-forming and coordinating grid-following vehicles to support prioritized loads. Applied to a hospital blackout scenario, HIVE demonstrates robust performance in forming an islanded microgrid and sustaining critical loads under varying vehicle availability, state of charge, and power constraints. Simulation results highlight the model’s effectiveness in ensuring decentralized coordination of energy allocation and prioritizing loads, offering a scalable solution for resilient grid operations.

32 - ENERGY CONSERVATION, CONSUMPTION, AND UTILIZA↗
DOE OSTI2024

Integrating a Microgrid Controller with a Local OpenADR Server

When military microgrids isolate themselves from the main electrical grid, they must locally balance electricity supply and demand. Since local generation may be limited, the current strategy is to shed all but the most critical loads by tripping smart circuit breakers, which must then be reset manually (e.g., ESTCP project EW-201350). This strategy is typically applied at the building level, meaning that entire buildings housing mission critical activities must be excluded from any load management, while those considered non-critical may lose service entirely. The remotely controlled switchgear needed to manage load in this way is very expensive ($\$30,000$-$\$50,000$ per building). While effective at shedding load, this strategy disrupts installation operation and risks damaging equipment during both disconnection and re-energization. With the goals of lowering costs, protecting equipment, and enhancing the agility of DoD microgrids, this report demonstrates the use of cybersecure automated demand response (ADR) technology to manage microgrid loads during grid-independent (a.k.a. "islanded") operation. This automated approach achieves load shedding and shifting through communication signals sent to equipment controllers rather than by cutting off the flow of electricity within the microgrid itself. Because it operates only on the base network, with no connection to external entities, this strategy avoids the main cybersecurity concern raised by past applications of ADR on military bases.

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NASA NTRS2004

Formal Verification of Safety Properties for Aerospace Systems Through Algorithms Based on Exhaustive State-Space Exploration

The Runway Safety Monitor (RSM) designed by Lockheed Martin is part of NASA's effort to reduce aviation accidents. We developed a Petri net model of the RSM protocol and used the model checking functions of our tool SMART to investigate a number of safety properties in RSM. To mitigate the impact of state-space explosion, we built a highly discretized model of the system, obtained by partitioning the monitored runway zone into a grid of smaller volumes and by considering scenarios involving only two aircraft. The model also assumes that there are no communication failures, such as bad input from radar or lack of incoming data, thus it relies on a consistent view of reality by all participants. In spite of these simplifications, we were able to expose potential problems in the RSM conceptual design. Our findings were forwarded to the design engineers, who undertook corrective action. Additionally, the results stress the efficiency attained by the new model checking algorithms implemented in SMART, and demonstrate their applicability to real-world systems. Attempts to verify RSM with NuSMV and SPIN have failed due to excessive memory consumption.

Ciardo, Gianfranco↗
NASA NTRS2006

Formal Verification of the Runway Safety Monitor

The Runway Safety Monitor (RSM) designed by Lockheed Martin is part of NASA's effort to reduce runway accidents. We developed a Petri net model of the RSM protocol and used the model checking functions of our tool SMART to investigate a number of safety properties in RSM. To mitigate the impact of state-space explosion, we built a highly discretized model of the system, obtained by partitioning the monitored runway zone into a grid of smaller volumes and by considering scenarios involving only two aircraft. The model also assumes that there are no communication failures, such as bad input from radar or lack of incoming data, thus it relies on a consistent view of reality by all participants. In spite of these simplifications, we were able to expose potential problems in the RSM conceptual design. Our findings were forwarded to the design engineers, who undertook corrective action. Additionally, the results stress the efficiency attained by the new model checking algorithms implemented in SMART, and demonstrate their applicability to real-world systems.

Siminiceanu, Radu↗
DOE OSTI2026

GridPIQ Reference Data

GridPIQ uses dozens of publicly available datasets to provide context for a user's grid project, as well as defaults for users to choose from. Users can choose to import their own data to better customize their analysis or use GridPIQ-supplied defaults. This allows users to get up and running with an analysis very quickly without having to spend significant time pulling together input data. To run an electric vehicle (EV) smart charging project, a user will need to provide or select from prepopulated values for the regional load profile shape and peak load, region of interest and closest weather station, EV charging profile, number of EVs to add for the analysis, maximum EV charging power, location of chargers relative to grid infrastructure, and allowable charging times (for coordinated charging mode). The outputs of the analysis are changes in air quality, EV energy consumption, EV peak demand, and EV hourly consumption profile—before and after project implementation." For a detailed description of the tool methodology, including all the publicly available datasets used by the tool, see the [GridPIQ documentation](https://gridpiq.pnnl.gov/v2-beta/doc/).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
NASA NTRS1990

Adaptivity and smart algorithms for fluid-structure interaction

This paper reviews new approaches in CFD which have the potential for significantly increasing current capabilities of modeling complex flow phenomena and of treating difficult problems in fluid-structure interaction. These approaches are based on the notions of adaptive methods and smart algorithms, which use instantaneous measures of the quality and other features of the numerical flowfields as a basis for making changes in the structure of the computational grid and of algorithms designed to function on the grid. The application of these new techniques to several problem classes are addressed, including problems with moving boundaries, fluid-structure interaction in high-speed turbine flows, flow in domains with receding boundaries, and related problems.

Oden, J. Tinsley↗
DOE OSTI2025

Demonstration of a Novel Technology to Manage Electricity Demand in Grid-Independent Military Microgrids

This research was conducted by the National Renewable Energy Laboratory (NREL) in collaboration with the S&C Electric Inc. through funding provided by the ESTCP. The project demonstrates use of cybersecure Automated Demand Response (ADR) technology to effectively manage microgrid loads during grid-independent, also known as "islanded," operation. When military microgrids become isolated from the main electrical grid, they are required to balance electricity supply and demand locally. Given that local generation may be constrained, the prevailing strategy involves shedding all but the most critical loads by tripping smart circuit breakers, which then necessitate manual resetting. This approach is generally implemented at the building level, which means that the buildings with mission-critical activities are exempt from load management and remain fully powered, whereas those deemed non-critical can experience a complete loss of service. In this research we developed a method that allows building automation systems to selectively control their assets in response to load shedding request from a microgrid controller, avoiding total loss of service in contrast to the conventional control approach. A commercial OpenADR client server by GridFabric is used for communication between the microgrid controller and the building management system (BMS). The microgrid controller monitors both generation capacity and various assets within the microgrid and issues a demand reduction request when necessary. This request is communicated to the OpenADR server via Modbus. Upon receiving the request, the OpenADR server forwards it to the BMS utilizing the OpenADR protocol. The BMS is pre-configured with various levels of load reduction strategies based on the controllable assets available, allowing for a nuanced approach to demand reduction. Both lab and field tests were performed that considered load shedding needed to achieve closed transition into island mode and to accommodate changing loads and power source availability while islanded. A commercial microgrid controller was used for these tests with normal programming within the expected constraints of the system capabilities. That is, the solution did not require any specialized modification to the code base of the controller. Given the latency of the round-trip communication path between the microgrid controller and the various devices involved with the load shed processes, there are certain scenarios for which the demonstrated solution are appropriate and some which are not. The methods described in this report can be used for load shedding/restoration during transitions between islanded and grid-tied modes of operation, as well as accommodating normal variations in load and the need to remove a power source from operation for maintenance. These methods should not be used for scenarios that require load shedding within a second or two such as sudden and unanticipated significant load increases or loss of power sources through equipment faults.

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DOE OSTI2025

Benefits of Dual Fuel Heat Pump Grid-responsive Control: A Model-based Control Optimization Approach Using Building and Equipment Co-simulation

Conventional dual fuel heat pumps lack the intelligent control mechanisms to efficiently manage the switch between heat pump and furnace, leading to sub-optimal energy usage and, in some cases, increased operating costs. To resolve this gap, this study applies optimized control on hybrid heat pumps. With a focus on equipment control strategies, we compare the performances of five spacing heating equipment, including a conventional heat pump (HP), a conventional furnace, a dual fuel heat pump (DFHP) with conventional control, a dual fuel heat pump with smart control, and a novel seamlessly fuel flexible heat pump (SFFHP). While DFHP runs on either gas or electricity at any given moment, SFFHP concurrently consumes gas and electricity by continuously optimizing the proportion of each. In this research, a co-simulation framework is developed by integrating a building envelope model with a physics-based heat pump simulation model to analyze the benefits of grid-responsive controls of DFHP and SFFHP. The model-based optimal controls adjust the operation of the heat pump and gas furnace based on utility price signals and marginal grid emission to minimize utility cost and CO 2 emissions for multiple climate zones, different utility tariffs, and marginal grid emission scenarios. Case studies in Chicago and Los Angeles demonstrate that SFFHP and DFHP, with model-based optimal control, can deliver significant reductions in peak demand, utility cost, and CO 2 emission. In Chicago, SFFHP and smart controlled DFHP yield up to 64.7% and 61.7% utility cost reduction and up to 15.7% and 8.5% CO 2 emission reduction compared to the gas furnace. In Los Angeles, SFFHP and smart controlled DFHP achieve up to 43.6% and 40.1% utility cost reduction and up to 13.8% and 14.1% CO2 emission reduction compared to conventional heat pumps. In conclusion, by leveraging the fuel flexibility nature of dual fuel heat pumps, the model-based control optimization approach makes dual fuel heat pump an attractive option for demand response programs.

Control↗
DOE OSTI2024

Brick Schema Standardized Plug Load Control Strategies for Load Reduction: Preprint

Plug loads comprise a significant percentage of commercial building energy consumption. Applying intelligent controls to turn off plug loads when unused can provide dynamic load reduction and flexibility, which are key traits of grid-interactive efficient buildings. This capability is important for equitable decarbonization as it can enable disadvantaged communities to electrify buildings without costly upgrades to electrical infrastructure. In this work, we present the effectiveness of various control strategies along with the operational lessons that informed their design. During a three-year period, we operated over 600 smart outlets in 12 university office buildings. The attached plug loads consisted primarily of printers, TVs, water dispensers, and copiers. After recording baseline power measurements for one year, we designed plug load control (PLC) strategies for each plug load type, use, and for different risk tolerance levels because PLC can potentially be disruptive to daily work. We used the Brick Schema to facilitate the management of plug load locations and other metadata. For advanced controls, we integrated the smart plugs with heating, ventilation, and air conditioning (HVAC) systems through the campus building automation system. We found static schedules to be the least disruptive and most predictable for occupants, resulting in 38% and 66% energy savings in two studies. For printers, print server-triggered PLC produced 86% savings, the highest of all strategies with minimal occupant impact. Scheduling of water dispensers and digital signage TVs produced 49% and 70% savings respectively with opportunities to improve performance with the use of HVAC occupancy data.

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗
DOE OSTI2024

Experimentation in Exploring Photovoltaic Inverter Dynamics Under Different Irradiance Levels Through a Data-Driven Approach

As conventional direct connections of synchronous generators are being phased out, inverter-based resources (IBRs) with grid support functions are increasingly being integrated into power systems. This transition requires the development of accurate dynamic models for IBRs to predict how power systems will adapt to varying levels of IBRs penetration, establish grid code requirements, and ensure compliance. Here, this study introduces an active probing signal-based data-driven modeling technique to accurately derive the dynamics model of a smart photovoltaic inverter operating in Volt-Watt and Freq-Watt modes, in compliance with the IEEE 1547–2018 standard. The paper focuses on investigating how the dynamics of the PV inverter model respond to fluctuations in solar irradiance, utilizing real-time digital simulator experimentation. The experimental analysis demonstrates that the amplitude of dynamics fluctuates with changes in irradiance across both operational modes and confirms the active power’s dependence on irradiance levels. Furthermore, the nature of inverter dynamics varies distinctly between the different modes of activation. Critically, our findings indicate that dynamic models require DC-gain adjustments to accommodate contrasting irradiance levels, highlighting a negative gradient linear relationship between the DC-gain of each model and the irradiance.

14 SOLAR ENERGY↗
DOE OSTI2025

DistOPF: Advanced Solutions for Distribution Optimal Power Flow Analysis - DistOPF v0.2 Documentation

To achieve an affordable and reliable energy system, research on power distribution system is often focused on integration of distributed generators, energy storage solution, EV charging, smart meters, and other advanced assets that may benefit from or require more advanced control and optimization techniques. Despite this focus on advanced distribution system topics, early researchers and grid scientists often start from scratch when developing optimization programs for power distribution systems. This report introduces DistOPF, a Python package that consolidates years of research into a versatile and modular tool. DistOPF provides researchers with essential capabilities to solve distribution system Optimal Power Flow (OPF) problems using standard network models. Additionally, it offers a platform to benchmark both new and existing algorithms against established test systems.

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