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DOE OSTI2020

GridOPTICS/GridPACK

GridPACK is a software framework consisting of a set of modules designed to simplify the development of programs that model the power grid and run on parallel, high performance computing platforms. It also contains several fully developed applications, including powerflow, dynamic simulation, state estimation, Kalman filter analysis (dynamic state estimation), contingency analysis and real time path rating. These applications can be used either standalone or as components in more complicated workflows that combine several different types of application together. The framework modules are available as a combination of libraries and software templates and consist of components for setting up and distributing power grid networks, support for modeling the behavior of individual buses and branches in the network, converting the network models to the corresponding algebraic equations, and parallel routines for manipulating and solving large algebraic systems. The framework also contains a module for distributing tasks evenly amongst computing resources, even if individual tasks vary widely in their execution times. Additional modules support input and output, basic statistical analysis of contingency based calculations, distributed data structures, as well as basic profiling and error management.

Palmer, Bruce↗

DOE OSTI2022

Resolution requirements for energy conservation in kinetic plasma simulations

The kinetic codes used to model the coupled dynamics of electromagnetic fields and charged particle transport have requirements for spatial, temporal, and charge resolution. These requirements may vary by the solution technique and scope of the problem. In this report, we investigate the resolution limits in the energy-conserving implicit particle-in-cell code CHICAGO. This report has the narrow aim of determining the maximum acceptable grid spacing for the dense plasmas generated in models of z-pinch target gases and power-flow electrode plasmas. In the 2D sample problem, the plasma drifts without external forces with velocity of 10 cm/µs. Simulations are scaled by plasma density to maintain uniform strides across the plasma and from the plasma to the boundaries. Additionally, the cloud-in-cell technique is used with 400 particles per cell and Δ t = 0.85× the Courant limit. For the linear cloud distribution, the criterion for conserving energy is Δ E/E tot < 0.01 for 50,000 time steps. The grid resolution is determined to crudely be Δx ≲ 3 l s , where l s is the electron collisionless skin depth. For the second-order cloud distribution the criterion is Δ E/E tot < 0.005 yielding Δx ≤ 15 l s . These scalings are functions of the chosen v d , Δ t , particles-per-cell, and number of steps.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

From Simple Labels to Time-Use Integrations: Supporting the Spectrum of Qualitative Travel Behavior Data

In transportation research, applications of travel behavior data collection are context-specific and require different types of qualitative inputs. These inputs can be viewed as spanning a spectrum of user burden and data quality, from simple trip labels to complex time-use surveys. However, each currently active smartphone-based travel diary platform appears to only support one type of qualitative input, and the effort required for customization is unclear. In this paper, we characterize the spectrum by defining four canonical use cases: (i) trip labels, (ii) trip questionnaire, (iii) counterfactual trips, and (iv) time-use surveys. We then outline a mechanism for supporting configurable user inputs on the same underlying smartphone-based sensing mechanism and demonstrate that it can support all the use cases without any code changes. We further demonstrate that the flexible data model that underpins this mechanism can enable real-time monitoring and analysis. Finally, we evaluate per-user data collection and engagement metrics for large-scale deployments of three canonical use cases, spanning 10 programs, 435 users, and 251,041 trips, and a maximum duration of 800 days. Future efforts may support additional use cases through an expanded configuration and provide greater insight into user engagement. We hope that these insights enable the research community to look at qualitative inputs through a new lens and experiment with novel use cases to fill in the spectrum.

ADVANCED PROPULSION SYSTEMS,POWER TRANSMISSION AND↗

DOE OSTI2024

Trends and meteorological drivers of extreme daily reservoir evaporation events in the western United States

Extreme daily evaporation from reservoir surfaces can lead to significant short-term water losses, affecting water quality, water supply, and reservoir operation strategies. Historical trends in daily reservoir evaporation events have eluded the scientific and operational communities, largely due to a lack of long-term, consistent data record. This study quantifies trends in extreme daily reservoir evaporation events at 165 major reservoirs located in the western U.S. Here, we use the place-based energy balance and aerodynamic Daily Lake Evaporation Model (DLEM) driven by multiple meteorological data products (RTMA, gridMET, Daymet) to estimate daily evaporation rates at these reservoirs from 1981 to 2022. The results—while are based on different meteorological forcing datasets—consistently indicate that the California, Lower Colorado, and Rio Grande hydrologic regions are more prone to higher daily evaporation extremes. Compared to the rest of western U.S, these three regions also experience a more pronounced increasing trend in the annual maximum daily evaporation rate, at about 0.3 mm day -1 decade -1 during 1981-2022. The results show that heat and dryness are the main drivers to the increasing trend of extreme evaporation, while extreme wind speed is the primary contributor to exceptionally high daily evaporation events across all regions. This phenomenon is particularly prominent in the arid Lower Colorado region, but less significant in the cold and humid Pacific Northwest region. We also find that the correlation between extreme wind speed and extreme evaporation degrades as the time scale increases from daily, to monthly and seasonal. Our findings have strong implications for the pattern and distribution of extreme evaporation events at the western U.S. reservoirs, and illustrate how various drivers influence extreme evaporation across different time scales.

13 HYDRO ENERGY↗

DOE OSTI2023

The Influence of Carbon Fiber Composite Specimen Design Parameters on Artificial Lightning Strike Current Dissipation and Material Thermal Damage

Previous artificial lightning strike direct effect research has examined a broad range of specimen design parameters. No works have studied how such specimen design parameters and electrical boundary conditions impact the dissipation of electric current flow through individual plies. This article assesses the influence of carbon fiber composite specimen design parameters (design parameters = specimen size, shape, and stacking sequence) and electrical boundary conditions on the dissipation of current and the spread of damage resulting from Joule heating. Thermal-electric finite element (FE) modelling is used and laboratory scale (<1 m long) and aircraft scale (>1 m long) models are generated in which laminated ply current dissipation is predicted, considering a fixed artificial lightning current waveform. The simulation results establish a positive correlation between the current exiting the specimen from a given ply and the amount of thermal damage in that ply. The results also establish that the distance to ground, from the strike location to the zero potential boundary conditions (ground), is the controlling factor which dictates the electric current dissipation in each ply. Significantly, this distance to ground is dependent on each of the specimen shape, dimensions, stacking sequence, and location of ground boundary conditions. Therefore, it is not possible to decouple current dissipation and damage from specimen design and boundary condition setup. However, it is possible to define a specimen size for a given specimen shape, stacking sequence, and waveform which limit the influence of specimen dimensions on the resulting current distribution and damage. For a rectangular specimen design which appears in literature multiple times, as 100 × 150 mm and with a stacking sequence of [45/0/-45/90] 4s , a specimen design of greater than 300 × 200 mm is required to limit the influence of specimen dimensions on current distribution and damage.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Peer-to-peer communication control for resilient operations of networked cyberphysical systems

This report includes two main accomplishments of the peer-to-peer communication control for resilient operation of networked microgrids project in FY24, which include a scheme for cyberattack-aware coordination of networked microgrids for supporting voltages of bulk power systems and a scheme for price signal-based operations of EV-rich networked microgrids with mixed ownership. First, the cyberattack-aware scheme enables networked microgrids to distributedly determine the amount of reactive power injection to support the voltage of bulk power system (BPS) in a fair manner. In this scheme, a risk-informed algorithm is presented to generate the peer-to- peer (P2P) communication graph with minimal risk of attack on communication links. To deal with cyberattacks on MG controllers, the resilient consensus algorithm (CA) is utilized for MG controllers to robustly estimate the total reactive power headroom, from which the MGs can accurately provide the needed amount of reactive power injection for supporting the voltage of BPS. The CA implementation and performance within the P2P communication framework are demonstrated on the IEEE 39-bus system with 6 microgrids contained in the distribution feeder under different cyberattack scenarios. Second, the price-based scheme enables the usage of the real-time price signal for the operations of electric vehicle (EV)-rich networked-microgrids with mixed ownership, in which not all the microgrids can communicate with the distribution system operator (DSO). In this scheme, a max consensus is introduced to enable the real-time price signal to be propagated from the DSO to all the microgrids, from which each microgrid controller will manage the DERs to balance the load demand and the power injection from the EV charging stations within its microgrid. Numerical results over one day with 288 slots of 5-minute intervals on the modified 123-node test feeder including 3 microgrids with high penetration of EV are presented to evaluate how the price signal affects the operations of networked microgrids under different charging strategies of the EV charging stations. The result indicates that our proposed EVCS (dis)charging strategy, which leverages the flexibility of EVs to support the grid through discharging during peak demand, proves to be a cost-effective solution that reduces operational costs while improving the social welfare of EV charging.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Quantitative phase imaging around water vapor microbubbles under pulsed laser illumination

We measured water temperature around a self-oscillating water vapor-rich bubble using diffraction phase microscopy equipped with a pulsed laser. The water vapor-rich bubble, which causes a strong water flow around it, was generated by locally heating degassed water through the photothermal conversion properties of an FeSi2 thin film. The generation of the flow is related to the self-oscillation of the bubble at sub-MHz frequencies and the temperature distribution around it. Here, the refractive index of the surrounding water was measured using a pulsed laser with a 3.5-ns pulse duration, which guarantees a time resolution of less than 1/200 of the oscillation cycle of the bubble. The temperature distribution around the bubble was calculated from the measured refractive index.

Narihira, Kyoshiro [Kyoto University, Japan]↗

DOE OSTI2024

Space-Time Structured Plasma Waves

Electrostatic waves play a critical role in nearly every branch of plasma physics from fusion to advanced accelerators, to astro, solar, and ionospheric physics. The properties of planar electrostatic waves are fully determined by the plasma conditions, such as density, temperature, ionization state, or details of the distribution functions. Furthermore we demonstrate that electrostatic wave packets structured with space-time correlations can have properties that are independent of the plasma conditions. For instance, an appropriately structured electrostatic wave packet can travel at any group velocity, even backward with respect to its phase fronts, while maintaining a localized energy density. These linear, propagation-invariant wave packets can be constructed with or without orbital angular momentum by superposing natural modes of the plasma and can be ponderomotively excited by space-time structured laser pulses like the flying focus.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2020

Looking at the bigger picture: Identifying the photoproducts of pyruvic acid at 193 nm

Here, photodissociation of pyruvic acid (PA) was studied in the gas-phase at 193 nm using two complementary techniques. The time-sliced velocity map imaging arrangement was used to determine kinetic energy release distributions of fragments and estimate dissociation timescales. The multiplexed photoionization mass spectrometer setup was used to identify and quantify photoproducts, including isomers and free radicals, by their mass-to-charge ratios, photoionization spectra, and kinetic time profiles. Using these two techniques, it is possible to observe the major dissociation products of PA photodissociation: CO 2 , CO, H, OH, HCO, CH 2 CO, CH 3 CO, and CH 3 . Acetaldehyde and vinyl alcohol are minor primary photoproducts at 193 nm, but products that are known to arise from their unimolecular dissociation, such as HCO, H 2 CO, and CH 4 , are identified and quantified. A multivariate analysis that takes into account the yields of the observed products and assumes a set of feasible primary dissociation reactions provides a reasonable description of the photoinitiated chemistry of PA despite the necessary simplifications caused by the complexity of the dissociation. These experiments offer the first comprehensive description of the dissociation pathways of PA initiated on the S 3 excited state. Most of the observed products and yields are rationalized on the basis of three reaction mechanisms: (i) decarboxylation terminating in CO 2 + other primary products (~50%); (ii) Norrish type I dissociation typical of carbonyls (~30%); and (iii) O—H and C—H bond fission reactions generating the H atom (~10%). The analysis shows that most of the dissociation reactions create more than two products. This observation is not surprising considering the high excitation energy (~51 800 cm –1 ) and fairly low energy required for dissociation of PA. We find that two-body fragmentation processes yielding CO 2 are minor, and the expected, unstable primary co-fragment, methylhydroxycarbene, is not observed because it probably undergoes fast secondary dissociation and/or isomerization. Norrish type I dissociation pathways generate OH and only small yields of CH 3 CO and HOCO, which have low dissociation energies and further decompose via three-body fragmentation processes. Experiments with d 1 -PA (CH 3 COCOOD) support the interpretations. The dissociation on S 3 is fast, as indicated by the products’ recoil angular anisotropy, but the roles of internal conversion and intersystem crossing to lower states are yet to be determined.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Real-Time Testbed for Transmission Line Protection

Hardware in the loop (HIL) testing is crucial for designing and managing electric power grids. These grids are becoming larger and more complex. The importance for students to have safe and intuitive ways to interact with the devices associated with the power grids has never been more crucial. Since most of these tests involve high voltages, this can be a deterrent for instructors and students in undergraduate programs. HIL testing is a solution to these common issues. This method has become one of the most popular methods for testing these power systems. With the use of Western Michigan University’s (WMU) Real-Time Digital Simulator (RTDS) and SEL-421-7 protection relay, a HIL testbed has been created. These devices were interconnected using the communication protocol known as Generic Object-Oriented Substation Event (GOOSE). A simulated transmission line system was modeled in an RTDS software RSCAD as the basis for this testbed. This model simulated different types of faults that could occur in a transmission line while in operation. The SEL-421-7 relay is connected to the RSCAD simulation via GOOSE to protect our simulated transmission line. This testbed was set up to give students a clear understanding of how distance protection works as well as how the SEL-421-7 will react to various kinds of faults, in addition to how useful the RTDS can be when testing different power systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Filamentary velocity scaling validation and spin dynamics in the DIII-D tokamak

Measured filament velocities in the DIII-D tokamak are compared against theoretical scalings, finding that the latter often represents an upper limit on experimental velocity distributions with most filaments possessing lower velocity. Filament spin from internal E × B drift is experimentally demonstrated to alter filament radial velocity. A critical spin velocity, where filament radial velocity peaks, is observed and corresponds to approximately 5 km/s. This transition is corroborated using a less direct measure of filament spin in the form of a temperature ratio. These techniques are combined to find that the critical spin velocity closely aligns with transport times along and across filaments becoming comparable. The normalized filament size distribution is consistent with the most stable size as dictated by Kelvin–Helmholtz and curvature-driven instabilities. Overall, the findings suggest filament stability and spin alter filamentary transport that may threaten the integrity of first walls in fusion devices.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Controller Hardware-in-the-Loop Modeling and Operation of a High-Power DC Charging Hub

High-power charging (HPC) concept will be a critical enabler for the wide-scale adoption and integration of electric vehicles (EVs). HPC hubs will have a significant impact on achieving this goal, particularly when considering the charging requirements of next-generation medium and heavy-duty vehicles (MD/HD) used in various vocational scenarios. This emphasizes the significance of evaluating and confirming the technical planning and multi-level operation of HPC hubs through modeling, protocol implementation, and simulation before hardware demonstration. The focus of this study is to develop the architecture, modeling, communication, and real-time controller hardware-in-the-loop (C-HIL) simulation of HPC hubs using the DC distribution system approach. Specifically, this work demonstrates the practical implementation of a custom Smart Energy Management System (SEMS) for a real-time C-HIL HPC hub simulation using the Open Charge Point Protocol (OCPP) for communication. OCPP is implemented on the Node-Red framework and the custom controller is executed in Python. We developed a rule-based controller to demonstrate the proposed approach.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2026

Tachyon: Intelligent Multi-Scale Modeling of Distributed Resilient Infrastructure and Workflows for Data Intensive HEP Analyses

The DOE High Energy Physics (HEP) program in Neutrino and Collider science drives data-intensive science and simulation on extreme-scale platforms. Modeling and optimizing the complex distributed components from experimental to leadership computing facilities are essential for HEP workflows to achieve required response times and resilience under various conditions. Tachyon proposes a framework for scalable modeling, simulation, and validation of key performance characteristics for the distributed infrastructure between FNAL and ALCF, along with associated HEP workflows.

Carothers, Chris [Rensselaer Poly.]↗

DOE OSTI2026

Tachyon: Intelligent Multi-Scale Modeling of Distributed Resilient Infrastructure and Workflows for Data Intensive HEP Analyses

Carothers, Chris [Rensselaer Poly.]↗

DOE OSTI2020

A Hybrid-Learning Algorithm for Online Dynamic State Estimation in Multimachine Power Systems

With the increasing penetration of distributed generators in the smart grids, having knowledge of rapid real-time electromechanical dynamic states has become crucial to system stability control. Conventional Supervisory Control and Data Acquisition (SCADA)-based dynamic state estimation (DSE) techniques are limited by the slow sampling rates, while the emerging phasor measurement units (PMUs) technology enables rapid real-time measurements at network nodes. Using generator bus terminal voltages, we propose a hybrid-learning DSE (HL-DSE) algorithm to estimate the synchronous machine rotor angle and speed in real time. The HL-DSE takes the power system model into account and trains neuroestimators with real-time data in an online manner. Compared with traditional DSE methods, the HL-DSE overcomes limitations by using a data-driven approach in conjunction with the physical power system model. The time efficiency, accuracy, convergence, and robustness of the proposed algorithm are tested under noises and fault conditions in both small- and large-scale test systems. Simulation results show that the proposed HL-DSE is much more computationally efficient than widely used Kalman filter (KF)-based methods while maintaining comparable accuracy and robustness. In particular, HL-DSE is over 100 times faster than square-root unscented KF (SR-UKF) and 80 times faster than extended KF (EKF). The advantages and challenges of the HL-DSE are also discussed.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

Electric Vehicles Charging Time Constrained Deliverable Provision of Secondary Frequency Regulation

Aggregation of electric vehicles (EVs) is a promising technique for providing secondary frequency regulation (SFR) in highly renewable energy-penetrated power systems. Equipped with energy storage devices, EV aggregation can provide reliable SFR. However, the main challenge is to guarantee reliable intra-interval SFR capacities and inter-interval delivery following the automatic generation control (AGC) signal. Furthermore, aggregated EV SFR provision will be further complicated by the EV charging time anxiety because SFR provision might extend EV's charging time. This paper proposes a deliverable EV SFR provision with a charging-time-constrained control strategy. First, a charging-time-constrained EV aggregation is proposed to address the uncertainty of EV capacity based on the state-space model considering the charging-time restriction of EV owners. Second, a real-time economic dispatch and time domain simulation (RTED-TDS) cosimulation framework is proposed to verify financial results and the dynamic performance of the EV SFR provision. Last, the proposed charging time-constrained EV aggregation is validated on the IEEE 39-bus system. In conclusion, the results demonstrate that with charging time-constrained EV aggregation, the dynamic performance of the system can be improved with a marginal increase in total cost. More importantly, the charging time constraint can be respected in the proposed SFR provision of the EV aggregation.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Machine Learning-Assisted Distribution System Network Reconfiguration Problem

High penetration from volatile renewable energy resources in the grid and the varying nature of loads raise the need for frequent line switching to ensure the efficient operation of electrical distribution networks. Operators must ensure maximum load delivery, reduced losses, and the operation between voltage limits. However, computations to decide the optimal feeder configuration are often computationally expensive and intractable, making it unfavorable for real-time operations. This is mainly due to the existence of binary variables in the network reconfiguration optimization problem. To tackle this issue, we have devised an approach that leverages machine learning techniques to reshape distribution networks featuring multiple substations. This involves predicting the substation responsible for serving each part of the network. Hence, it leaves simple and more tractable Optimal Power Flow problems to be solved. This method can produce accurate results in a significantly faster time, as demonstrated using the IEEE 37-bus distribution feeder. Compared to the traditional optimization-based approaches, a feasible solution is achieved approximately ten times faster for all the tested scenarios.

deep neural networks↗

DOE OSTI2019

A Forward Time Stepping Heat Conduction Model for Spot Melt Additive Manufacturing

Solidification dynamics are crucial for determining microstructure development in additively manufactured parts. Multiphysics models based on finite element or finite volume methods may help gain insight for complicated phenomena such as fluid flow, keyholing, and porosity but are too computationally expensive to use for simulating actual builds. Recent analytic and semi-analytic solutions for moving heat sources in a semi-infinite three-dimensional space provide a way to accurately estimate the solidification conditions for entire builds. The downside to these methods is that, unlike finite element or finite volume methods, they cannot use the temperature distribution of the previous timesteps to march the solution forward in time. This paper provides the mathematical formulation and implementation of a forward time stepping (FTS) approach to an existing semi-analytic solution. The speed and accuracy of the two methods are then compared for various scan patterns. The result is that, for spot melts, the forward time-stepping model provides improvements in both speed and accuracy. This is especially true for longer simulations, where the simulation can be orders of magnitude faster. Finally, the longest simulation analyzed in this paper was roughly 30× faster when using the forward time-stepping model versus the straightforward implementation of the semi-analytic solution.

36 MATERIALS SCIENCE↗