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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources: Preprint

Integration of a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problem requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (controllable DERs) including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperformed other benchmark controllers regarding computation time without compromising operational performance.

DER↗
DOE OSTI2022

Scalable Predictive Control and Optimization for Grid Integration of Large-Scale Distributed Energy Resources

Integrating a large number of distributed energy resources (DERs) into the power grid needs a scalable power balancing method. We formulate the power balancing problem as a look-ahead optimization problem to be solved sequentially by a power distribution system aggregator based on a model predictive control (MPC) framework. Solving large-scale look-ahead control problems requires proper configuration of the control steps. In this paper, to solve large-scale control problems, we propose a variable time granularity where control time steps nearby the current control step have finer resolutions. The aggregator objective includes maximization of power production revenue and minimization of power purchasing expense, renewable power curtailment, and mileage costs for energy storage and electric vehicle (EV) charging stations while satisfying system capacity and operational constraints. The control problem is formulated as a mixed-integer linear program (MILP) and solved using the XpressMP solver. We perform simulations considering a copper plate representation of a large distribution network consisting of 2507 devices (controllable DERs), including curtailable photovoltaics (PVs), energy storage batteries, EV charging stations, and buildings with heating, ventilation, and air conditioning units (HVACs). We show the effectiveness of the proposed approach in managing DERs interactively for maximum energy trading profit and local supply-demand power balancing. Finally, we demonstrate that the proposed method outperforms other benchmark controllers regarding computation time without compromising operational performance.

DER↗
DOE OSTI2025

Reticular Structural Diversification of Zirconium Metal–Organic Frameworks Through Angular Ligand Configuration Control

Reticular chemistry offers practical guidelines for enlarging and enriching the arsenal of metal–organic frameworks (MOFs). However, reticular expansion to access mesoporous structures remains challenging due to limitations in achieving precise control over both the size and configuration during building units’ extension. Herein, we combine ligand isomerization and functionalization strategies to regulate the ligand configuration by systematically replacing aryl C–H groups with N atoms, resulting in angular dicarboxylate ligands with various symmetries. The assembly between a 4,4′-(pyridine-2,6-diyl)dibenzoic acid ligand (1N, C 2 symmetry) and 12-connected Zr 6 cluster leads to the formation of a pseudo ftw topology framework (NU-2611), where one pair of nose-to-nose 1N ligands resembles a tetra-topic ligand. When a 6,6′-(1,3-phenylene)dinicotinic acid ligand (2N, C S symmetry) was used, another pseudo ftw network NU-2612 was obtained with a 2-fold framework interpenetration. Interestingly, the planar [2,2′:6′,2″-terpyridine]-5,5″-dicarboxylic acid ligand (3N, C 2V symmetry) yielded an intriguing mesoporous Zr-MOF with kag topology. NU-2613 represents the first example of kag Zr-MOF designed to include large, well-defined mesopores. The diversity of these MOFs was further enhanced through post-synthetic metalation of linkers. Particularly, metalation of the chelating 3N ligand with Fe 3+ in NU-2613 enables efficient catalytic transformation within the functionalized channels. This work contributes insight into the reticular expansion of Zr-MOFs by finely-tuning the ligand planarity, advancing the structure diversification of mesoporous frameworks for specific applications.

Cluster chemistry↗
DOE OSTI2025

A Robust Data-Driven Approach for Mechanical Serial Sectioning

Mechanical serial sectioning (MSS) provides detailed microstructural information across large length scales. By repeatedly removing thin layers of material and imaging the exposed surface, a 3D representation of a specimen’s internal structure can be constructed, enabling failure analysis and feature identification that are otherwise inaccessible via conventional 2D or nondestructive evaluation techniques. Achieving consistent and accurate material removal can be challenging due to system variability, requiring an experienced operator to manually adjust parameters, prolonging data collection times and necessitating post-processing routines to standardize the data. Here, to address these challenges, this paper presents the employment of a one-step model predictive control (MPC) framework tailored to a run-to-run (R2R) controller. The R2R-MPC controller automates the parameter selection process, improving the consistency of material removal through iterative feedback for disturbance rejection and accurate tracking of the target removal rate. Using a data-driven approach, the controller robustly adapts to changing material characteristics. The effectiveness of the R2R-MPC controller is demonstrated through simulation and experimental results and compared to previous data collection procedures.

3D Materials Science↗
DOE OSTI2022

The role of amorphous ZIF in ZIF-8 crystallization kinetics and morphology

Understanding the composition and structure of amorphous precursor phases is fundamental for elucidating two-step crystallization mechanisms and designing shape- and size-controlled nanomaterials. However, that understanding is largely lacking for metal–organic framework compounds despite their growing significance as functional materials. Here, in this study, we report the crystallization of zeolite imidazolate frameworks-8 (ZIF-8, Zn(C 4 H 5 N 2 ) 2 ) via an amorphous ZIF (am-ZIF) solid precursor phase with a rough stoichiometric composition of Zn(C 4 H 5 N 2 ) 1.78 (C 4 H 6 N 2 ) 0.17 (CH 3 COO) 0.22 . The formation of am-ZIF is attributed to the incomplete deprotonation of 2-Methylimidazole (HmIm) and the involvement of the hydrogen bond between CH 3 COO– and –HN, which can further transform into the dense Dia(Zn) structure with a diamondoid crystal topology in pure water. Taking am-ZIF as a precursor, the tunable dissolution and recrystallization kinetics of am-ZIF into ZIF-8, due to the addition of EtOH and CTAB, allows the selective fabrication of dodecahedral, cubic, and hollow ZIF-8. Overall, an in-depth understanding of the differences in composition and structure of am-ZIF from ZIF-8 and the resulting crystallization kinetics suggests a novel approach to designing metal–organic frameworks with controlled crystal morphology.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Framework for assessment of magnetic equilibrium controller performance on the MAST upgrade spherical tokamak

Here, in this work we present the assessment framework for magnetic equilibrium controllers on MAST Upgrade spherical tokamak (MAST-U) spherical tokamak. Such controllers are essential for the MAST-U since exhaust physics and core-edge integration studies require advanced divertor plasma configurations. The developed framework is based on the TokSys suite of plasma control codes, which was adapted and upgraded for MAST-U. However, extra capabilities were added on top of TokSys to support the development of new control algorithms, deployment of controllers to the plasma control system (PCS) and evaluation of their performance. The controller assessment was realized via closed-loop integrated control simulations with the actual MAST-U PCS and different physics-based plasma models. Since all components of the assessment chain were experimentally validated, these simulations provide qualified controllers applicable for direct use in the experiment. This resulted in the successful experimental demonstration of advanced plasma shape control on MAST-U with minimal on-machine development time. A similar methodology would be beneficial to other tokamaks, both existing and future.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Optimizing Layered Control Strategies for Reducing Exposure to SARS-CoV-2

While there is growing understanding of the predominance of the airborne mode of transmission of the SARS-CoV-2 virus, there is a lack of guidance on how to build an effective system of controls to mitigate transmission in enclosed spaces. Such a system integrates multiple hazard-specific control measures to both eliminate or replace a hazard, and safeguard individuals against potential exposure and infection. Controls are defined by the US Occupational Safety and Health Association (OSHA) as the use of engineering methods to reduce the level of hazard inside a confined space. The Hierarchy of Controls provides a framework through which a system of controls can be examined; identifying those which directly remove or replace a hazard as the most effective, and individual behavioral measures (e.g., masking or shielding) as least effective. Use of such a framework to quantify control effectiveness might allow for the promotion of spaces as meeting a certain threshold of safety, likely adding to the confidence of space users resulting in increases in various metrics such as sales, visits, or likes.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Strategy for distributed controller defence: Leveraging controller roles and control support groups to maintain or regain control in cyber-adversarial power systems

Distributed controllers play a prominent role in electric power grid operation. The coordinated failure or malfunction of these controllers is a serious threat, where the resulting mechanisms and consequences are not yet well-known and planned against. If certain controllers are maliciously compromised by an adversary, they can be manipulated to drive the system to an unsafe state. The authors present a strategy for distributed controller defence (SDCD) for improved grid tolerance under conditions of distributed controller compromise. The work of the authors’ first formalises the roles that distributed controllers play and their control support groups using controllability analysis techniques. With these formally defined roles and groups, the authors then present defence strategies for maintaining or regaining system control during such an attack. A general control response framework is presented here for the compromise or failure of distributed controllers using the remaining, operational set. The SDCD approach is successfully demonstrated with a 7-bus system and the IEEE 118-bus system for single and coordinated distributed controller compromise; the results indicate that SDCD is able to significantly reduce system stress and mitigate compromise consequences.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Data-Driven Distribution System Coordinated PV Inverter Control Using Deep Reinforcement Learning

The deployment of distributed solar photovoltaic (PV) systems has increased consistently over the past decades. High penetrations of PVs could cause a series of adverse grid impacts, such as voltage violations. The recent development of smart inverter technologies rises the incentives of developing PV control solutions that regulate the inverter output power and seeking the optimization on system operational objectives. This paper proposes a data-driven control solution based on deep reinforcement learning (DRL) to optimize PV inverters for voltage regulation. The proposed solution can minimize PV real power curtailment while maintaining network voltage at an acceptable range. Comparison results between the proposed DRL control algorithms with deep deterministic policy gradient (DDPG) and volt-var control on a real feeder in west Colorado highlight the advantage of the proposed framework in controlling the system voltage while minimizing the PV real power curtailment.

deep reinforcement learning↗
DOE OSTI2024

Power System Frequency Dynamics Modeling, State Estimation, and Control using Neural Ordinary Differential Equations (NODEs) and Soft Actor-Critic (SAC) Machine Learning Approaches

With the global energy transition of the electric power system, grid control, supervision, and protection is becoming more challenging. With the increasing integration of renewable energy sources (RES), the system dynamics are changing, causing traditional power system dynamic modeling with swing equation-based modeling approaches to fail. Additionally, the converter-dominated power grid is decreasing the system inertia, making the power system more fragile to the frequency swings. This paper first investigates and compares the application of a model-based Kalman filter state estimation approach with (i) a model-free machine learning approach --- neural ordinary differential equations (NODEs) --- and (ii) a data-driven system identification (SysId) approach to model and infer critical state values of the power system frequency dynamics. Then a model predictive control (MPC) framework is compared to a model-free Soft Actor-Critic (SAC) reinforcement learning (RL) control algorithm in providing efficient fast frequency response (FFR) to the power system frequency dynamics. The approaches are compared in terms of their performance goals as well as their per-timestep computational efficiency. Furthermore, the comparative study for state estimation shows that for the model-free requirement, both NODEs and SysId can provide accurate state estimates; however, with increasing model complexity, NODEs can be a better choice for model identification. Similarly, the results from the FFR comparative study show that the SAC RL-based FFR, once trained, outperforms MPC with better control signals and faster computation time, making the SAC RL-based FFR better option for providing FFR to the power system.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

An open-source framework for simulation-based testing of buildings control strategies

Here this paper presents a simulation framework for evaluating building control strategies (BCSs), developed with VOLTTRON, an opensource platform that integrates data, devices, and systems for sensing and control applications, and is based on co-simulation interfaces. It realizes an integrated environment for both testing and deploying BCSs, thereby eliminating the need for having a dedicated implementation of BCS for testing. For the first time, this framework provides critical functionalities, including scalable communication management and time-drive simulation advance, i.e., advancing the simulation based on clock time. We applied this framework to evaluating two BCSs from ASHRAE Guideline 36-2008 and ASHRAE Standard 90.1-2019. The evaluation results show that those BCSs primarily benefit the heating operation by reducing gas usage but yield insignificant savings in electricity consumption. The results also emphasize the importance of tuning the parameters of the BCSs to achieve better performances.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2023

Computationally Efficient Control Co-Design Optimization Framework with Mixed-Fidelity Fluid and Structure Analysis: OpenTurbineCoDe (OTCD) - ARPA-E ATLANTIS Phase I Project (Final Technical Report)

The goal of the Department of Energy (DOE) Advanced Research Projects Agency-Energy (ARPA-E) Aerodynamic Turbines Lighter and Afloat with Nautical Technologies and Integrated Servo-control (ATLANTIS) Program is to develop new technologies for floating offshore wind turbines, or wind farms, using the discipline of control co-design (CCD.) In this context, our goal is to develop a computationally efficient optimization framework for design of floating offshore wind turbines. Our specific aim is to utilize high-fidelity structural, aerodynamic, aero-structural tools, and to derive control-oriented reduced- or low-order models directly from the high-fidelity tools. We proposed a mixed-fidelity modeling approach which means that we are also using low- and mid-fidelity tools when necessary. This research is conducted by a multidisciplinary team consisting of Rutgers University, University of Michigan, Brigham Young University, and the National Renewable Energy Laboratory (NREL). The computational framework, called OpenTurbineCoDe, is designed to integrate, where possible, traditional structural, aerodynamic, aeroelastic models (e.g., OpenFAST) and advanced control algorithms with higher fidelity simulation tools including Reynolds-averaged Navier–Stokes (RANS) solvers, and three-dimensional structural finite element solvers. All the high-fidelity tools used in this research provide numerically exact gradients to facilitate both efficient optimization and local linearization for control implementation.

17 WIND ENERGY↗
DOE OSTI2026

Control of Nonlinear Compton Scattering in a Squeezed Vacuum

Electromagnetic radiation by accelerated charges is a fundamental process in physics. Here, we introduce a quantum-optical framework for controlling the emission of radiation of an electron in an intense laser field via squeezed vacuum states. By engineering the quantum fluctuations of the emission modes, we demonstrate that the probability of nonlinear Compton scattering can be significantly enhanced or suppressed through tunable squeezing amplitude and angle. We show numerically that our predictions are experimentally accessible with current squeezing technologies, establishing a new paradigm for quantum control in high-intensity light-matter interactions.

Light-matter interaction↗
DOE OSTI2023

Aero‐servo‐elastic co‐optimization of large wind turbine blades with distributed aerodynamic control devices

Abstract This work introduces automated wind turbine optimization techniques based on full aero‐servo‐elastic models and investigates the potential of trailing edge flaps to reduce the levelized cost of energy (LCOE) of wind turbines. The Wind Energy with Integrated Servo‐control (WEIS) framework is improved to conduct the presented research. Novel methods for the generic implementation and tuning of trailing edge flap devices and their controller are also introduced. Primary flap and controller parameters are optimized to demonstrate potential maximum blade tip deflection reductions of 21 % . Concurrent design optimization (i.e., co‐design) of a novel segmented wind turbine blade with trailing edge flaps and its controller is then conducted to demonstrate blade cost savings of 5 % . Additionally, rotor diameter co‐design optimization is demonstrated to reduce the LCOE by 1.3 % without significant load increases to the tower. These results demonstrate the efficacy of control co‐design optimization using trailing edge flaps, and the entirety of this work provides a foundation for numerous control co‐design‐oriented studies for distributed aerodynamic control devices.

17 WIND ENERGY↗
DOE OSTI2021

A Multifidelity Ensemble Kalman Filter with Reduced Order Control Variates

This work develops a new multi delity ensemble Kalman lter (MFEnKF) algorithm based on linear control variate framework. The approach allows for rigorous multi delity extensions of the EnKF, where the uncertainty in coarser delities in the hierarchy of models represent control variates for the uncertainty in ner delities. Small ensembles of high delity model runs are com- plemented by larger ensembles of cheaper, lower delity runs, to obtain much improved analyses at only small additional computational costs. We investigate the use of reduced order models as coarse delity control variates in the MFEnKF, and provide analyses to quantify the improvements over the traditional ensemble Kalman lters. We apply these ideas to perform data assimilation with a quasi-geostrophic test problem, using direct numerical simulation and a corresponding POD-Galerkin reduced order model. Numerical results show that the two- delity MFEnKF provides better analyses than existing EnKF algorithms at comparable or reduced computational costs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

A Hardware Platform for Studying Naval Power Electronic Power Distribution Systems

Abstract – Future intelligent ship system designs will likely include electric propulsion, numerous highpower sensors, and directed energy weapons. Supply and control of these large nonlinear loads will require a networked, multi-converter power electronic power distribution system. This work presents a hardware platform to emulate a microgrid power system with multiple power converters and a power data communication network. The platform is reconfigurable and can include both AC and DC power distribution zones, representative of shipboard power systems. It also allows for the study of both power control actuation and power data communication delays. Since the platform is based on electric power hardware, spatial and temporal uncertainties are inherently embedded in the system. Specifically, this work examines the control actuation of multiple pulsed power loads in a single microgrid. Several pulse load levels and operating scenarios have been implemented and measured. A framework for control parameter quantification is presented, and various metrics are explored to capture pulse signal characteristics. The sensitivity of pulse load metric parameters is analyzed. Dynamic shipboard, mission-specific load profiles coupled with pulse loads can also be emulated in the hardware platform.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Toward nonthermal control of excited quantum materials: framework and investigations by ultrafast electron scattering and imaging

Quantum material systems upon applying ultrashort laser pulses provide a rich platform to access excited material phases and their transformations that are not entirely like their equilibrium counterparts. The addressability and potential controls of metastable or long-trapped out-of-equilibrium phases have motivated interests both for the purposes of understanding the nonequilibrium physics and advancing the quantum technologies. Thus far, the dynamical spectroscopic probes eminently focus on microscopic electronic and phonon responses. For characterizing the long-range dynamics, such as order parameter fields and fluctuation effects, the ultrafast scattering probes offer direct sensitivity. Bridging the connections between the microscopic dynamics and macroscopic responses is central toward establishing the nonequilibrium physics behind the light-induced phases. Here, we present a path toward such understanding by cross-examining the structure factors associated with different dynamical states obtained from ultrafast electron scattering, imaging, and modeling. We give the basic theoretical framework on describing the non-equilibrium scattering problems and briefly describe how such framework relates to the out-of-equilibrium phenomena. We give effective models outlining the emergences of nonthermal critical points, hidden phases, and non-equilibrium relaxational responses from vacuum-suspended rare-earth tritellurides, tantalum disulfides thin films, and vanadium dioxide nanocrystalline materials upon light excitations.

79 ASTRONOMY AND ASTROPHYSICS↗