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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Multiple Environmental Influences on the Lightning of Cold-Based Continental Convection. Part II: Sensitivity Tests for Its Charge Structure and Land–Ocean Contrast

In Part I, an electrification scheme was described and a simulation of an observed cold-based storm from the U.S. Great Plains was validated with electrical observations. Most charge in the storm was separated by rebounding collisions of secondary ice originating from prior graupel–snow collisions. In this Part II, sensitivity tests are performed with the control simulation (Part I) and influences from environmental factors (aerosols, temperature, moisture, and shear) on lightning are elucidated. Environmental factors [e.g., convective available potential energy (CAPE)] controlling updraft speed are salient. When ascent is reduced by 30% and 70%, flashes become 70% fewer and disappear, respectively; faster ascent promotes positive cloud-to-ground (+CGs) flashes. Since cloud base is too cold (1°C) for coalescence, cloud condensation nucleus aerosol concentrations do not influence the lightning appreciably. The electrical response to varying concentrations of active ice nuclei is limited by most ice particles being secondary and less sensitive—a natural “buffer.” Imposing a maritime sounding suggests that the land–sea contrast in lightning for such storms is due to the vertical structure of environmental temperature and humidity. Weak CAPE, and both entrainment and condensate weight from a low cloud base, suppress ascent and charging. Maritime thermodynamic conditions reduce simulated flash rates by two orders of magnitude. Reducing aerosol loadings from continental to maritime only slightly reinforces this suppression. Last, a conceptual model is provided for how any simulated storm is either normal because graupel/hail is mostly positively charged or else is inverted/anomalous because graupel/hail is mostly negatively charged, with environmental factors controlling the charging. Impacts from microphysical processes, including three processes of secondary ice production, on lightning are analyzed.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Scalable, Physical Effects Measureable Microgridfor Cyber Resilience Analysis

SPEMMCRA provides a low-cost simulated method to provide for testing of control theory and cybersecurity approaches to microgrid implementations. Specifically, this physics-based approach provides realistic responses to compare control strategies in simulation, but also to demonstrate actions that can or cannot be taken in taking cybersecurity actions . As communications interfaces or other actions are taken that affect the flow of data, SPEMMCRA can show whether the microgrid operation is adversely affected by what is intended to mitigate a cybersecurity event.

Rieger, CraigG↗
DOE OSTI2025

Hardware-Based Demonstration of Temperature Control Functions for Reactor Systems

Establishing autonomy in reactor control systems has become essential for the expansion of nuclear technologies. Thermal regulation in particular remains crucial for maintaining stable operation and ensuring the integrity of fuel. To alleviate public skepticism of the safety of nuclear reactors, demonstrating control over this key factor is pivotal. Utilizing electric heat pads to simulate the heat released in a reactor core, thermocouples for temperature monitoring, and an Arduino micro programmable logic controller (PLC) for control, a hardware-based demonstration of a reactor heating system validates the efficacy of reactor control over this key parameter. To improve precision, a proportional-integral-derivative (PID) algorithm was implemented in the heating control loop to ensure meticulous control of reactor functions. In addition, the integration of this physical system with a digital simulator tool such as RELAP5-3D establishes a foundation for a comprehensive testing environment. This allows for a refinement of temperature control under various simulated reactor conditions, bringing another layer of reliability to the operation of the system. By facilitating a physical demonstration of reactor thermal management and control strategies, this project provides a foundation for expanded testing and educational outreach. Ultimately, this system advances the broader goal of demonstrating the safety and viability of autonomous reactor operations, contributing to public trust and future reactor deployment.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Energy performance evaluation of the ASHRAE Guideline 36 control and reinforcement learning–based control using field measurements

This study evaluates the energy performance of ASHRAE Guideline 36–compliant control (ASHRAE 36 control) and reinforcement learning (RL)–based control through experimental field tests and a simulation study. Three field tests were conducted at Oak Ridge National Laboratory’s commercial building test facility in Oak Ridge, Tennessee: a baseline with a baseline conventional control, a test with ASHRAE 36 control, and a test with RL-based control. The selected ASHRAE 36 controls were trim and respond control, as well as variable air volume (VAV) box control. We compared the measured supply air temperature of the rooftop unit, VAV box supply air temperature, and VAV box supply airflow rate across the three test cases. The field data indicated that ASHRAE 36 controls operated as specified by ASHRAE Guideline 36. Based on these data, ASHRAE 36 control achieved a 45 % reduction in hourly averaged HVAC energy consumption compared with the baseline, and RL-based control achieved a 66 % reduction. These potential annual energy savings were confirmed using a calibrated whole-building energy model. Compared with the baseline, ASHRAE 36 control reduced HVAC energy consumption by 42 %, and RL-based control achieved a 54 % reduction. Furthermore, RL-based control reduced total HVAC energy consumption by 21 % more than ASHRAE 36 control.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Model-based predictive control of multi-stage air-source heat pumps integrated with phase change material-embedded ceilings

This paper presents a model-based predictive control strategy to optimize the operations of phase change material (PCM) ceiling panels coupled with a multi-stage air-source heat pump. A three-stage prototype heat pump unit has been built and tested in the laboratory, with the low and medium stages designed for space heating/cooling and the high compression stage dedicated to charging of the PCM energy storage. To facilitate optimal control of the integrated heat pump system, a mixed-integer linear programming formulation is derived through linearization of the heat pump model and a mixed-integer reformulation of the PCM dynamic governing equations. A predictive control strategy is synthesized based on the resultant control formulation and implemented in a receding horizon scheme that optimizes the PCM charging and the zone temperature schedules simultaneously to leverage both the passive (associated with building construction materials) and active (PCM) storage capacities of a building. The control strategy has been tested along with three benchmarking control scenarios using a co-simulation platform for a prototypical detached house in Atlanta, GA. In this study, test results showed that application of the proposed control strategy to the PCM-integrated heat pump could provide 27.1% electricity cost savings while a fine tuned rule-based control strategy could achieve cost savings of 20.4%, compared to a baseline case without PCM storage, under a time-of-use rate tariff.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Hardware Demonstration of Weak Grid Oscillations in Grid-Following Converters

The increasing penetration of inverter-based resources (IBRs) introduces some unexpected dynamic issues, including low-frequency oscillations. In this paper, a laboratory-scale grid-following voltage-source converter (VSC) system is implemented to demonstrate weak grid oscillations. Grid-following control is applied in VSC to provide active power, reactive power or ac voltage control. The test bed is also replicated in electromagnetic transient (EMT) simulation environment (MAT-LAB/SimPowerSystems) for benchmark purpose. Case studies are carried out to demonstrate low-frequency oscillations under real power/ac voltage or real power/reactive power control. The excellent agreement between the simulation and experimental results ensures that the two test beds are exchangeable and can be used for testing oscillation mitigation strategies in future research.

Bao, Li↗
DOE OSTI2023

SiC Based Modular Transformer-less MW-Scale Power Conditioning System and Control for Flexible CHP System

This project aims at developing a SiC-based, modular, transformer-less (60-Hz-transformers-free), MW-scale, four-wire DC/AC power conditioning system (PCS) converter, and a corresponding control system for flexible-CHP (F-CHP) systems. With the help of an F-CHP controller and power electronics converters, different CHP sources, renewable sources, and batteries can be assembled to the DC grid, which is then connected to the medium voltage (MV) AC grid through the PCS converter. To meet grid support and performance requirements, the F-CHP controller design and PCS converter design follow IEEE 1547 and IEEE 2030.7 standards. Five main tasks, including PCS converter design, F-CHP controller development, PCS converter prototype building and testing, F-CHP controller testing, and PCS paralleling, have been carried out. In this project, the F-CHP controller testing has been completed in simulation, HIL and HTB, and the PCS converter prototypes have been successfully built and tested.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Resilient Control of Networked Microgrids Using Vertical Federated Reinforcement Learning: Designs and Real-Time Test-Bed Validations

Improving system-level resiliency of networked microgrids against adversarial cyber-attacks is an important aspect in the current regime of increased inverter-based resources (IBRs). To achieve that, this paper contributes in designing a hierarchical control layer, in conjunction with the existing control layers, resilient to adversarial attack signals. Considering model complexities, unknown dynamical behaviors of IBRs, and privacy issues regarding data sharing in multi-party-owned microgrids, designing such a control layer is non-trivial. Here, to tackle these issues, a novel federated reinforcement learning (Fed-RL) method is proposed. To grasp the interconnected dynamics of networked microgrids, the paper develops Federated Soft Actor-Critic (FedSAC) algorithm following the vertical structure of implementing Fed-RL. Next, utilizing the OpenAI Gym interface, we built a custom set-up in GridLAB-D/HELICS co-simulation platform, named Resilient RL Co-simulation (ResRLCoSIM), to train the RL agents with IEEE 123-bus benchmark comprising 3 interconnected microgrids. Finally, the learned policies in the simulation are transferred to the real-time hardware-in-the-loop (HIL) test-bed developed using the high-fidelity Hypersim platform. Finally, experiments show that the simulator-trained RL controllers achieve desirable performance with the test-bed platform, validating the minimization of the sim-to-real gap.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Incentive-Based Control and Coordination of Distributed Energy Resources. Final Report

The rapid growth of low-inertia renewable energy resources represents an immense opportunity for the U.S. to minimize its carbon footprint, while presenting a challenge for system operators as traditional “spinning” generation resources are displaced. This transformation requires solutions to robustly and cost-effectively manage dynamic changes on the grid while ensuring quality of service. There is growing recognition that distributed energy resources (DERs – loads, distributed generation, storage, electric vehicles, etc.) represent a great potential to perform this function. This report details a scalable hierarchical control strategy for coordinating thousands of heterogeneous DERs in order to provide three ancillary gird services: 1) frequency response, a rapid (within 2 seconds) service used to maintain the grid at 60 Hz; 2) regulation response, a larger response used to balance on-going differences in supply and demand on the grid; and, 3) ramping reserve, used to bring on capacity to replace lost generation. The developed control architecture consists of 1) a Distribution Reliability Coordinator (DRC), 2) aggregator controllers, and finally, 3) DER controllers. The DRC coordinates all the flexible loads and distributed energy resources on the distribution system and bids the aggregate flexibility into the wholesale market. The DRC also performs resource allocation (deciding how the flexible devices on the distribution system will be dispatched) to meet the requirements for each of the three ancillary services. The aggregators control a collection of devices that are geographically co-located and provide a platform to aggregate their flexibility and mitigate uncertainty associated with a single flexible load by managing a large aggregation of similar loads (so that any stochastic effects average out). Finally, DER controllers (for example, thermostats for air conditioners, chargers for electric vehicles) adjust the power consumption of individual devices to ensure accurate and reliable delivery of the requested grid services. Evaluation and validation of this approach was conducted with a mixture of simulation and hardware testing for a range of DERs in residential (air conditioners and water heaters), commercial HVAC (ventilation fans and central chiller plants), and micro-grids (battery energy storage, solar PV etc.). This culminated in DER hardware and simulation models operating in conjunction with grid simulations as part of a large scale federated test-bed demonstration. Simulations of over 10,000 controllable residential devices (a combination of air conditioners, water heaters, batteries, and electric vehicles) demonstrated that this advanced control approach could simultaneously meet all three grid services. Furthermore, hardware-in-the-loop testing was performed with operational micro-grid and commercial building HVAC equipment. The micro-grid equipment (representing PV, battery storage, and back-up generators) demonstrated the ability to meet all frequency response requirements (except ramping time). The commercial building HVAC ventilation equipment successfully provided the regulating response service. An Industry Advisory Board (IAB) was formed and engaged throughout the project to get feed-back on project risks and potential commercialization barriers. Their input was invaluable in identify key risks stemming from regulatory and market access challenges, financial risks from under-performance, and competitive threats from utility-scale solutions such as integrated storage. A phased commercialization plan was developed that addresses continued risk reduction (value proposition refinement and performance uncertainty assessments), piloting through field demonstrations with key stakeholders, and finally, deployment as an emerging standard for DER control.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Battery Electric Vehicle Eco-Cooperative Adaptive Cruise Control in the Vicinity of Signalized Intersections

This study develops a connected eco-driving controller for battery electric vehicles (BEVs), the BEV Eco-Cooperative Adaptive Cruise Control at Intersections (Eco-CACC-I). The developed controller can assist BEVs while traversing signalized intersections with minimal energy consumption. The calculation of the optimal vehicle trajectory is formulated as an optimization problem under the constraints of (1) vehicle acceleration/deceleration behavior, defined by a vehicle dynamics model; (2) vehicle energy consumption behavior, defined by a BEV energy consumption model; and (3) the relationship between vehicle speed, location, and signal timing, defined by vehicle characteristics and signal phase and timing (SPaT) data shared under a connected vehicle environment. The optimal speed trajectory is computed in real-time by the proposed BEV eco-CACC-I controller, so that a BEV can follow the optimal speed while negotiating a signalized intersection. The proposed BEV controller was tested in a case study to investigate its performance under various speed limits, roadway grades, and signal timings. In addition, a comparison of the optimal speed trajectories for BEVs and internal combustion engine vehicles (ICEVs) was conducted to investigate the impact of vehicle engine types on eco-driving solutions. Lastly, the proposed controller was implemented in microscopic traffic simulation software to test its networkwide performance. The test results from an arterial corridor with three signalized intersections demonstrate that the proposed controller can effectively reduce stop-and-go traffic in the vicinity of signalized intersections and that the BEV Eco-CACC-I controller produces average savings of 9.3% in energy consumption and 3.9% in vehicle delays.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Current profile and normalized beta control via feedback linearization and Lyapunov techniques

Abstract Simultaneous control of the current profile and normalized plasma beta is an essential control problem in the development of advanced tokamak scenarios. However, this control problem is especially challenging due to the nonlinear nature of the current, heat, and particle transport dynamics, as well as the difficulty to understand and accurately model such processes. In this work, a nonlinear, robust, model-based controller for the simultaneous regulation of the current profile and normalized beta has been designed using feedback linearization and Lyapunov redesign techniques. Feedback linearization avoids approximate linearization of the plasma dynamics, retaining the original physics content of the model. Moreover, the use of Lyapunov redesign techniques makes the controller robust against the uncertainties arising during the modeling process. The controller’s performance in the presence of unknown dynamics is tested in nonlinear, one-dimensional simulations using the Control Oriented Transport SIMulator (COTSIM) code, which employs plasma models that are significantly more complex than those employed for control synthesis.

Physics↗
DOE OSTI2021

Time-Disciplined Non-PLL Active Synchronization for Grid-Forming Inverters: Preprint

Grid Forming Inverters (GFMIs) are a critical component of the future Grid. One major challenge with GFMIs is synchronization. Currently, most research in GFMI synchronization is focused around specific transition types but this is only a subcategory of the possible events facing GFMIs. In this paper, we propose categorizing all possible synchronization events into four categories: (1) Initial Grid Synchronization, (2) Ride-Through, (3) Blackstart Coordination, (4) Grid Reconnection Coordination. By categorizing events, we can better compare and integrate different control strategies under specific test conditions as demonstrated in simulation. This paper’s framework helps guide GFMI primary-level control design to further research towards the 100% inverter-dominant Grid.

blackstart↗
DOE OSTI2021

Time Disciplined Non-PLL Active Synchronization for Grid Forming Inverters

Grid forming inverters (GFMIs) are a critical component of the future grid. One major challenge with GFMIs is synchronization. Currently, most research in GFMI synchronization is focused around specific transition types but this is only a subcategory of the possible events facing GFMIs. In this paper, we propose categorizing all possible synchronization events into four categories: (1) initial grid synchronization, (2) ride-through, (3) blackstart coordination, (4) grid reconnection coordination. By categorizing events, we can better compare and integrate different control strategies under specific test conditions as demonstrated in simulation. This paper's framework helps guide GFMI primary-level control design to further research towards the 100% inverter-dominant grid.

blackstart↗
DOE OSTI2021

Ensuring statistical reproducibility of ocean model simulations in the age of hybrid computing

Novel high performance computing systems that feature hybrid architectures require large scale code refactoring to unravel underlying exploitable parallelism. Such redesign can often be accompanied with machine-precision changes as the order of computation cannot always be maintained. For chaotic systems like climate models, these round-off level differences can grow rapidly. Systematic errors may also manifest initially as machine-precision differences. Isolating genuine round off level differences from such errors remains a challenge. Here, we apply two-sample equality of distribution tests to evaluate statistical reproducibility of the ocean model component of US Department of Energy's Energy Exascale Earth System Model (E3SM). A 2-year control simulation ensemble is compared to a modified ensemble as a test case - after a known non-bit-for-bit change in a model component is introduced - to evaluate the null hypothesis that the two ensembles are statistically indistinguishable. To quantify the false negative rates of these tests, we conduct a formal power analysis using a targeted suite of short simulation ensembles. The ensemble suite contains several perturbed ensembles, each with a progressively different climate than the baseline ensemble - obtained by perturbing the magnitude of a single model tuning parameter, the Gent and McWilliams κ, in a controlled manner. The null hypothesis is evaluated for each of perturbed ensembles using these tests. The power analysis informs on the detection limits of the tests for given ensemble size allowing model developers to evaluate the impact of an introduced non-bit-for-bit change to the model.

Mahajan, Salil↗
DOE OSTI2025

Deep reinforcement learning control for co-optimizing energy consumption, thermal comfort, and indoor air quality in an office building

With the recent demand for decarbonization and energy efficiency, advanced HVAC control using Deep Reinforcement Learning (DRL) becomes a promising solution. Due to its flexible structures, DRL has been successful in energy reduction for many HVAC systems. However, only a few researches applied DRL agents to manage the entire central HVAC system and control multiple components in both the water loop and the air loop, owing to its complex system structures. Moreover, those researches have not extended their applications by incorporating the indoor air quality, especially both CO2 and PM2.5concentrations, on top of energy saving and thermal comfort, as achieving those objectives simultaneously can cause multiple control conflicts. What's more, DRL agents are usually trained on the simulation environment before deployment, so another challenge is to develop an accurate but relatively simple simulator. Therefore, we propose a DRL algorithm for a central HVAC system to co-optimize energy consumption, thermal comfort, indoor CO2 level, and indoor PM2.5 level in an office building. To train the controller, we also developed a hybrid simulator that decoupled the complex system into multiple simulation models, which are calibrated separately using laboratory test data. The hybrid simulator combined the dynamics of the HVAC system, the building envelope, as well as moisture, CO2, and particulate matter transfer. Three control algorithms (rule-based, MPC, and DRL) are developed, and their performances are evaluated on the hybrid simulator environment with a realistic scenario (i.e., with stochastic noises). The test results showed that, the DRL controller can save 21.4 % of energy compared to a rule-based controller, and has improved thermal comfort, reduced indoor CO2 concentration. The MPC controller showed an 18.6 % energy saving compared to the DRL controller, mainly due to savings from comfort and indoor air quality boundary violations caused by unmeasured disturbances, and it also highlights computational challenges in real-time control due to non-linear optimization. Finally, we provide the practical considerations for designing and implementing the DRL and MPC controllers based on their respective pros and cons.

Guo, Fangzhou↗
DOE OSTI2018

An agent-based hardware-in-the-loop simulation framework for building controls

In general, a hardware-in-the-loop (HIL) building simulation has lower cost and fewer practical limitations (e.g., scheduling issues) than field tests in occupied buildings, while also overcoming limitations of simulations alone by capturing the full behavior of some physical systems, equipment, and components. However, the implementation of an HIL can be difficult due to the scarcity of appropriate tools. Here, this paper presents an agent-based framework for HIL simulation. It can be used for investigation of controller performance via controller-in-the-loop simulations and also HIL for system synthesis. In the latter case, both controllers and major equipment participate in tests to ensure that dynamics of equipment operation are correctly captured in addition to controller performance. The HIL simulation framework presented allows such actual physical parts to be included in the framework while representing others for which behaviors are better known and modeled in simulation models. The mechanism implemented in the framework to synchronize simulations in software with real-time operation of physical equipment is described. Lastly, as an example, use of the HIL simulation framework is illustrated through a brief study of speed control of the supply fan in the air handling unit of a variable-air-volume building heating, ventilating and air-conditioning system.

42 ENGINEERING↗
DOE OSTI2022

Tundra SGS – Critical Importance of Site-Specific Injectivity Testing for Carbon Dioxide Injection Well Simulation Calibration

Paper presented at 16th International Conference on Greenhouse Gas Control Technologies (GHGT-16), October 23–27, 2022, Lyon, France. Brine injectivity tests were conducted on both the Broom Creek (BC) and Deadwood (DW) storage formations in one of the cored stratigraphic test wells prior to finalized simulations. The injectivity tests entailed injection of brine into the formations, followed by shutting in the wells. The shut-in duration represents the fall-off period which was used to carry out pressure transient analyses of the tests. The analysis of injectivity tests indicated that core-indicated and modeled permeability distributions should be conservatively multiplied by 2.5× and 5× in the BC and DW geologic models, respectively, prior to numerical simulations of CO 2 injection using Computer Modelling Group’s (CMG’s) GEM equation-of-state reservoir simulator. The scaler permeability multipliers allowed the fluid flow simulations to fully represent well test-measured injection well rates in the respective formations.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2025

Fermilab's controls development with virtual accelerator

Control Systems development is often the last thing considered when designing and building new equipment, e.g. a new detector or superconducting RF LINAC; however when the new equipment is installed, it is the first thing desired to be operational for testing. Due to frequent delays in building new equipment and project deadlines, control system development and testing is often curtailed. A way to alleviate this problem is to simulate the control system, though this will be challenging for complex systems.The Fermilab PIP-II (proton improvement plan - II) project is being constructed at Fermilab to deliver $800\,MeV$ protons of $>1\,MW$ beam power to replace the present LINAC for the remainder of the existing accelerator complex. The new LINAC consists of a warm front end (WFE), 23 superconducting RF cryomodules (of 5 types), and a beam transfer line (BTL) to the existing complex.The accelerator physics group has a parallel project to create a digital twin (DT) of the PIP-II accelerator. We have coupled the EPICS controls to this DT and are developing both the DT and EPICS software in parallel. This will allow us to develop the EPICS software framework, the HMIs, sequences, high level physics applications, and other services for use in a fully functional control system.This presentation will detail the work that we have performed to date and show demonstrations of controlling and monitoring the status of the accelerator, as well as future plans for this work.

Hanlet, Pierrick [Fermilab]↗