Real-Time Power Management for Microgrids With Dynamic Boundaries and Multiple Source Locations
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42 ENGINEERING↗
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Results for “Power System Dynamics”
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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A transfer learning approach to energy-efficient control of small and medium-sized commercial buildings
Model-free reinforcement learning (RL) provides a data-driven and adaptive approach to optimize building energy use while satisfying occupant comfort. This powerful tool does not need any prior knowledge about the environment and system it is optimizing and can adapt its policy based on the changes in captures. Like any other data-driven tool, it faces high training costs due to the extensive agent-environment interactions required to capture long-term building dynamics and user comfort. Transfer learning, particularly policy distillation, offers a promising way to accelerate training by leveraging pretrained RL agents in different building and system types. Here, this study investigates online student distillation, in which the student model updates its neural network weights using outputs from teacher models. The work introduces a student distillation strategy designed for efficient knowledge transfer, along with a teacher selection method that ensures high-quality guidance. The approach is validated using a highly calibrated whole building energy model for a small/medium commercial building test facility. Results show substantial reductions in training time and data requirements while surpassing the performance of ASHRAE Guideline 36, an advanced rule-based control strategy. The distilled RL model required 45% less data and achieved 20% higher cumulative rewards than a state-of-the-art RL model, with faster convergence and lower energy consumption. These outcomes demonstrate that effective transfer learning enables a scalable and data-efficient energy management solution for commercial buildings.
ASHRAE guideline 36↗
In Situ UV–vis Quantification of Chlorobasicity in Binary Molten Chlorides
Optical basicity measurements provide a basis for determining the relative chlorobasicity of a given molten salt composition. This study uses Bi3+ as a spectroscopic probe to investigate optical basicity across three binary molten chloride systems (LiCl-KCl, MgCl2–KCl, and ZnCl2–KCl) through in situ UV–vis spectroscopy measurements of the 1S0→3P1 transition. LiCl-KCl systems exhibit the highest optical basicity with minimal compositional dependence, while both divalent systems show stronger, yet nonlinear, dependence that is reminiscent of acid–base titration curves. The influence of cation electronegativity and polarizing power (Li+ < Mg2+ < Zn2+) directly reflects the basicity curves, with ZnCl2–KCl displaying the steepest gradients and lowest basicity values. Nonlinear dependencies in divalent systems indicate formation of chloride-bridged network structures with coordination states dictated by the amount of KCl in a salt composition, which was further investigated and validated by molecular dynamics simulations of polymeric structures formed in ZnCl2 and MgCl2-based salts using machine learning force fields. The temperature dependence of chlorobasicity in terms of optical basicity was investigated, and a loose, positive correlation between the two was revealed. These findings establish Bi3+ as a sensitive probe for understanding electronic environments in molten chloride systems and provide insights for predicting the chemical behavior of molten salts for use in high-temperature environments.
Buttice, Kailee [Department of Nuclear Engineering↗
Integration of Multiple Real-time Simulation Platforms with AIO for Scalability
This paper introduces a practical and scalable approach to extend interoperability of Controller Hardware in the Loop (CHIL) validations for large scale microgrids, networked microgrids, and power electronics-based feeders. The work focuses on integrating multiple real-time simulators using Analog Input/Output (AIO) interface techniques in heterogeneous CHIL environment. It explores interfacing methods, highlighting key challenges related to dynamic accuracy and maintaining bidirectional power balance. A comparative evaluation of the Ideal Transformer Method is presented, assessing its effectiveness in multi-CHIL integration scenarios. The feasibility of this setup is demonstrated through a real-time use case involving multiple Typhoon HIL and Opal-RT platforms, showcasing its applicability for distributed system studies.
Khalid, Mohammad [ORNL] (ORCID:0000000179208805)↗
A Novel Grid-forming Voltage Control Strategy for Supplying Unbalanced Microgrid Loads Using Inverter-based Resources
This paper presents a novel grid-forming voltage control strategy for a battery energy storage system to maintain balanced three-phase output voltages when serving unbalanced loads. A stationary reference frame (αβ) based control scheme is proposed to regulate positive-sequence and negative-sequence voltages. Compared with the conventional rotating reference frame (dq) based control scheme, the proposed scheme shows better dynamic performance. Then, we analyze the system zero-sequence network and propose adding a grounding transformer to the Y/Yg connected output transformer to further reduce the voltage unbalance at the point of common coupling. The simulation results demonstrate the effective performance of the proposed voltage control scheme. Based on the results, the power-voltage unbalance curve is derived for different output transformer configurations to establish the relationship between the power unbalance limit and the voltage unbalance limit for microgrid power scheduling.
Xu, Bei↗
Tethys: A Spatiotemporal Downscaling Model for Global Water Demand
Humans use water for many important tasks, such as drinking, growing food, and cooling power plants. Since future water demands depend on complex global interactions between economic sectors (e.g., demand for wheat in one country causing demand for water to grow that wheat in another country), it is often modeled at coarse spatial and temporal scales as part of models that account for complex, multi-sector system dynamics. However, models that project future water availability typically simulate physical processes at much finer scales. Tethys enables integration between these kinds of models by downscaling region-scale water demand projections using sector-specific proxies and formulas.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Near-field-driven radiative thermal dynamics in aperiodic photonic nanostructures
Harnessing structural correlations in near-field plasmonic and polaritonic systems hold untapped potential for controlling light–matter interactions at the nanoscale. By tuning these correlations, one can reshape mode localization, coupling, and spectral distribution which are properties central to manipulating energy transport and field enhancement in nanophotonic platforms. We exploit Vogel spirals, an aperiodic geometry where a single parameter dictates spatial correlations, to show how correlation strength reshapes the modal spectrum and transient dynamics of near-field coupling. As a proof of concept, we demonstrate that aperiodic configurations outperform both uncorrelated (random) and periodic arrays in controlling near-field radiative heat-transfer dynamics. These results establish deterministic aperiodic order as a powerful platform for tailoring correlated electromagnetic responses in next-generation nanophotonic devices.
36 MATERIALS SCIENCE↗
Insights into water extraction and aggregation mechanisms of malonamide-alkane mixtures
Structure at the nanoscale in the organic phase of liquid–liquid extraction systems is often tied to separation performance. However, the weak interactions that drive extractant assembly lead to poorly defined structures that are challenging to identify. Here, in this work, we investigate the mechanism of water extraction for a malonamide extractant commonly applied to f-element separations. We measure extractant concentration fluctuations in the organic phase with small angle X-ray scattering (SAXS) before and after contact with water at fine increments of extractant concentration, finding no qualitative changes upon water uptake that might suggest significant nanoscopic reorganization of the solution. The critical composition for maximum fluctuation intensity is consistent with small water–extractant adducts. The extractant concentration dependence of water extraction is consistent with a power law close to unity in the low concentration regime, suggesting the formation of 1 : 1 water–extractant adducts as the primary extraction mechanism at low concentration. At higher extractant concentrations, the power law slope increases slightly, which we find is consistent with activity effects modeled using Flory–Huggins theory without introduction of additional extractant–water species. Molecular dynamics simulations are consistent with these findings. The decrease in interfacial tension with increasing extractant concentration shows a narrow plateau region, but it is not correlated with any change in fluctuation or water extraction trends, further suggesting no supramolecular organization such as reverse micellization. This study suggests that water extraction in this system is particularly simple: it relies on a single mechanism at all extractant concentrations, and only slightly enhances the concentration fluctuations characteristic of the dry binary extractant/diluent mixture.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Structure and Shape of Surface-Mediated Assembly of Surfactants
Achieving controls on the self-assembly of cationic and block copolymer micelles has significant implications for advancing novel material systems for energy, environmental, and biological applications and for tuning fluid flow behavior in subsurface geologic environments. While it is known that the aggregation of micelles is influenced by the composition of the surrounding fluid, the influence of a solid interface has been less explored. In this study, we probe the organization of cetyltrimethylammonium bromide (CTAB) micelles in the absence and presence of the Pluronic P123 block copolymer and quartz substrate using transmission and grazing-incidence small-angle X-ray scattering measurements and classical molecular dynamics (MD) simulations. In the absence of the quartz interface, CTAB with and without P123 molecules assemble as ellipsoid core–shell micelles. Densification of the core on adding P123 is noted from the decrease in the core radius from 15.9 to 14.6 Å. Here, the presence of a quartz substrate causes the micelles to elongate, which is noted by the emergence of a power-law slope in the low q region (<0.02 Å –1 ). Moreover, in the presence of both P123 and the quartz substrate, the micelle shape changes from ellipsoid core–shell to cylindrical core–shell, and a significantly higher number of aggregates are formed. The higher number of aggregates, and faster aggregation kinetics are linked to the organization of the solvent structures as noted from the MD simulations. These findings demonstrate the effects of adding a block copolymer and including a quartz substrate on the self-assembly of cationic (CTAB) micelles, which can be used to inform the design of functional material systems that harness surfactant chemistries.
42 ENGINEERING↗
Using extended MHD to explore lasers as a trigger for x-pinches
X-pinches have been shown to be a source of extremely intense x-ray emissions useful for diagnosing plasma dynamics and imaging biological objects. The most striking feature of an x-pinch is the hotspot, the point source from where all the x rays come from. Unfortunately, the exact timing and location of the hotspot are still unpredictable. Since an x-pinch hotspot forms from instabilities (like an m = 0 mode), we will computationally explore whether we can use a high-power laser to control the timing and location of these instabilities. Our goal is to reduce the temporal and spatial jitter associated with the x-ray burst. Using an extended MHD (XMHD) code, we explore the non-relativistic instability generation using a current profile of a 250 kA linear transformer driver system and laser characteristics of SLAC's Matter in Extreme Conditions laboratory. Our results include both laser-penetration results using a boundary-defined electromagnetic (EM) wave and instability results from a power-deposition method.
71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
Joint Resource Modeling and Assessment for Hybrid Distributed Solar and Wind Systems
The inherent variability and uncertainty in distributed energy resources can presents myriad challenges to the planning and operations of power systems. These risks are poised to become larger as the penetration of renewable energy sources rises in the power generation mix. Hybrid solar-wind energy systems are able to mitigate some of these risks by their complementary resource availability. Surface solar and wind fields are coupled and correlated in both space and time. Appropriately estimating the hybrid solar wind energy system requires simulating the spatio-temporal structure of these fields that can be produced for each time horizon. We introduce a novel joint spatio-temporal stochastic differential equation (SPDE) approach that captures the spatio-temporal dynamics of solar and wind fields and their joint dependency over a domain for each time step. In the case study on Colorado, we consider nonstationary three-level hierarchical spatio temporal models for both hourly solar irradiance data and wind speed data in Colorado. Dependence between the solar irradiance data and wind speed data is captured by a shared spatio-temporal random effect. Our approach performs well in terms of the prediction score criterion.
joint modeling↗
Coarse-grained resource allocation modeling for decoding and rewiring microbial metabolism
Microbial metabolism is a complex, emergent system driven by the coordinated interplay of intricate and dynamic molecular processes. To elucidate cellular behavior and enable biotechnological applications, quantitative models that address the inherent complexity of metabolism have been developed from a resource allocation perspective. Here, we synthesize recent advances in coarse-grained resource allocation frameworks and their applications in understanding microbial physiology and guiding gene circuit design. Here, these frameworks reveal global regulatory constraints and predict cellular adaptation to nutrient and environmental changes. In addition, they enable the quantification of metabolic costs, the dissection of circuit–host interactions, and the development of strategies for burden mitigation. Collectively, these modeling frameworks provide a powerful platform for uncovering quantitative principles of microbial growth and engineering robust synthetic biological systems.
coarse-grained modeling↗
Development of MOSCATO: A CFD-Level Electrochemistry and Corrosion Simulator for Molten Salt Systems
For both coolant and fueled variants of molten salt reactors (MSRs), the corrosion of structural materials is a significant challenge. The corrosion stems from chemical and electrochemical reactions initiated by fissile material, fission products, and impurities in the salt. Lower-fidelity models rely on empirical correlations for mass transfer, simplified lumped temperature profiles, and similar assumptions. They do not capture detailed spatial variations in complex geometries, creating the need for high-fidelity modeling to bridge this gap.As we approach the demonstration and possible deployment of MSRs in this decade, the development of a high-fidelity, high-performance simulator becomes imperative. To simulate the complex electrochemical environment and corrosion within molten salt systems, we have developed the Molten Salt Chemistry And TranspOrt (MOSCATO) code. This endeavor is comprised of three essential components. First, mass transfer equations are coupled with the Navier-Stokes equations in order to account for the transport of species in the salt. Second, the diffusion of alloy constituents, such as Cr, Fe, Ni, etc. is simulated within the structural metals. Third, the alloy and salt domains are coupled to account for the heterogeneous chemical and electrochemical reactions that occur at the salt-alloy interface.MOSCATO manages all three components within the framework of the highly scalable, open-source spectral element method computational fluid dynamics code Nek5000/NekRS. This integration enables MOSCATO to harness the immense computational power of modern high-performance computing resources, ensuring both high fidelity and computational speed.In addition to code development, we have initiated a comprehensive verification and validation campaign, utilizing data from diverse sources. First, MOSCATO's electrochemical solver was verified with reference numerical data. Then validation occurred against experiments: one of a thermal galvanic cell and the other for corrosion in flowing molten salt of FLiNaK (LiF-NaF-KF). This campaign verified and validated MOSCATO as a reliable tool for simulating electrochemical environments and corrosion in molten salt systems.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Distinct Mechanisms of Triplet Pair Decay in Amorphous and Crystalline Heteroacene Thin Films
Triplet pairs (TT) in crystalline molecular semiconductors have unique spin properties of interest for quantum information or enhancing solar photoconversion. The population and diffusion dynamics of TT have been the subject of recent studies, both in covalent dimers and in crystalline systems. Here, in this study, we monitor the triplet population in neat polycrystalline and amorphous films of a heteroacene with known TT spectral properties and tunable spin polarization depending on the intermolecular geometry. Transient measurements reveal an anomalous power dependence in polycrystalline films that we attribute to the fast diffusion and interaction of dissociated triplet pairs confined to one-dimensional stacks of strongly coupled molecules. The nongeminate triplet interaction after dephasing facilitates conversion to the triplet 3 TT and eventually T 1 +S 0 . Amorphous films have no power dependence and proceed directly from 1 TT to 3 TT and subsequently T 1 +S 0 via state mixing facilitated by nonparallel geometries and weak exchange coupling.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Feedback Control Approaches for Restoration of Power Grids from Blackouts
The automated restoration of power systems with variable energy resources is a timely problem to tackle. Automated restoration advice can support operators in deciding on strategic actions to restore power grids from a blackout with a mix of conventional and renewable generation resources. To this end, this paper frames the restoration process of power grids with solar resources as a nonlinear dynamic model with algebraic constraints in discrete time which is steered by feedback control loops. We discuss two feedback-control strategies based on greedy and reinforcement learning algorithms, and contrast their performance with restoration plans generated by a mixed-integer linear program. We found that the reinforcement learning algorithm infers restoration actions faster than the greedy one. However, the tuning process of the reinforcement learning parameters is slower than for the greedy one.
machine learning↗
Co-optimization of repairs and dynamic network reconfiguration for improved distribution system resilience
In this work, a post-disaster distribution system repair and restoration (DSRR) strategy is proposed to improve distribution system resilience. The DSRR strategy is formulated as a two-stage optimization. The first stage is a comprehensive co-optimization of repair crew scheduling, dynamic network reconfiguration, and distributed energy resource (DER) dispatch based on the forecast load profile. The goal is to minimize the accumulative operating cost caused by the load reduction payment as well as DER operating cost. In particular, since the number of available repair crews is usually smaller than the number of faulted lines after a disaster event, the DSRR strategy determines the optimal scheduling for repairing faulted lines. The second stage is a re-dispatch of the DER power output and load shedding based on the real-time load demand of each bus. The proposed algorithm is validated by case studies of the IEEE 33-bus and 123-bus test systems. We consider those scenarios in which faults occur in multiple heavy-loaded feeders. The simulation results demonstrate that the DSRR strategy effectively coordinate the repair scheduling, network reconfiguration and load shedding to minimize the operating cost.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Cell dynamics simulations of coupled charge and magnetic phase transformation in correlated oxides
In this work, we present a comprehensive numerical study on the kinetics of phase transition that is characterized by two nonconserved scalar order parameters coupled by a special linear-quadratic interaction. This particular Ginzburg-Landau theory has been proposed to describe the coupled charge and magnetic transition in nickelates and the collinear stripe phase in cuprates. The inhomogeneous state of such systems at low temperatures consists of magnetic domains separated by quasimetallic domain walls where the charge order is reduced. By performing large-scale cell dynamics simulations, we find a two-stage phase-ordering process in which a short period of independent evolution of the two order parameters is followed by a correlated coarsening process. The long-time growth and coarsening of magnetic domains is shown to follow the Allen-Cahn power law. We further show that the nucleation-and-growth dynamics during phase transformation to the ordered states is well described by the Kolmogorov-Johnson-Mehl-Avrami theory in two dimensions. On the other hand, the presence of quasimetallic magnetic domain walls in the ordered states gives rise to a very different kinetics for transformation to the high-temperature paramagnetic phase. In this scenario, the phase transformation is initiated by the decay of magnetic domain walls into two insulator-metal boundaries, which subsequently move away from each other. Implications of our findings to recent nano-imaging experiments on nickelates are also discussed.
75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
Life-Cycle Assessment Integration into Scalable Open-Source Numerical Models (LiAISON) for Prospective Impact Analysis of Novel Technologies
Decarbonizing the industrial sector is a significant challenge in achieving a net-zero greenhouse gas (GHG) emissions economy by 2050 and the Paris Agreement, i.e., a global climate change mitigation target of achieving a maximum average temperature change potential of 1.5 Degrees Celsius or less by 2100 with respect to pre-industrial levels. In the United States (US), the industrial sector accounts for 23% of total GHG emissions and is home to a number of hard-to-electrify activities. The chemicals subsector has the single largest subsector emissions profile after direct emissions from fossil fuel combustion and leakage from fossil fuel distribution systems. Within the chemicals subsector, many processes depend on hydrogen or ammonia precursors. Decarbonizing these two commodities would contribute significantly to decarbonizing the industrial sector as hydrogen could also be used for low carbon steel production (e.g., hydrogen-based direct reduction of iron) and other industrial applications. Emerging technologies require the application of prospective life cycle assessment (LCA), which can account for technology (foreground) scaling and process improvements via learning-by-doing, among others. In many cases, the future system context (background) in which the technologies are assumed to operate in is equally relevant. Background scenarios generated by integrated assessment models (IAM) can coherently incorporate potential future dynamics of the energy-climate-human-land system. Further, IAM scenarios are harmonized across socioeconomic and climate change mitigation pathways, which facilitates the comparability of prospective LCAs using different IAMs. We introduce an open source prospective LCA framework, the Life-cycle Assessment Integration into Scalable Open-source Numerical models (LiAISON), to analyze the non-linear relationships between technology foreground and the future energy system background across a series of midpoint and resource use metrics. The integration of LCA and IAM data is achieved using prospective environmental Impact assessment (PREMISE). We showcase it by assessing two Power-to-Hydrogen (PtH2) processes, namely Solid Oxide Electrolysis (SOE) and Polymer Electrolyte Membrane Electrolysis (PEME). We compare the technologies to a baseline of hydrogen production via natural gas-based Steam Methane Reforming (SMR) in a US context of multiple energy system and climate change mitigation futures. Besides providing an analysis that specifies the LCA results ranges with temporal and geospatial explicitness across the two technologies, metrics, and impact assessment methods, this research also aims to establish a base framework that can be expanded to use other IAM generated scenarios and US open-source life cycle inventory (LCI) databases. We find that the temporal environmental performance of either technology or their difference to SMR is directly influenced by the underlying background dynamics. Additionally we compare our results by linking two other prospective models with LiAISON - GCAM (Global Change Assessment Model) and ReEDS (Regional Energy Deployment System) to analyze the effect of changing background scenarios using varying predictions in life cycle analysis.
decarbonizing↗