Time domain modeling of constant power loads for electromagnetic transient simulations
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Alboaouh, Kamel↗
SEARCH · Engineering Papers
Results for “Transient Modeling”
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Adaptive Interface-PINNs (AdaI-PINNs) for transient diffusion: Applications to forward and inverse problems in heterogeneous media
We model transient diffusion in heterogeneous materials using a novel physics-informed neural networks framework (PINNs) termed Adaptive interface physics-informed neural networks or AdaI-PINNs (Roy et al. arXiv preprint arXiv:2406.04626, 2024). AdaI-PINNs utilize different activation functions with trainable slopes tailored to each material region within the computational domain, allowing for a fully automated and adaptive PINNs approach to model interface problems with strongly and weakly discontinuous solutions. To enhance its performance in highly heterogeneous transient diffusion systems, we prescribe a suite of robust practices, including appropriate non-dimensionalization of equations, a biased sampling method, Glorot initialization, and the hard enforcement of boundary and initial conditions. Here we evaluate the efficacy of the proposed method on several benchmark forward and inverse problems. Comparative studies on one-dimensional and two-dimensional benchmark problems reveal that the modified AdaI-PINNs outperform its unmodified counterpart, achieving root-mean-square errors that are at least two orders of magnitude better in forward problems. For inverse problems, the maximum errors in the approximated diffusion coefficients by modified AdaI-PINNs are four orders of magnitude better than those of the unmodified version. Additionally, modified AdaI-PINNs demonstrate improved stability in problems with large material mismatches.
42 ENGINEERING↗
Deep Learning-enhanced Block-Diagram Modeling of Solar Power Systems
Data-driven models of power system inverter-based resources are desired to run simulations faster than with detailed electromagnetic transient models, to hide proprietary design details, to support control system design applications, and to aggregate the effects of distributed energy resources. This paper applies a customized Hammerstein Wiener framework to train block diagram models from thousands of electromagnetic transient simulations or experimental test records. The block diagram models integrate with larger grid simulations as voltagecontrolled current sources or current-controlled voltage sources for several simulators. Guidelines for block architecture and training are presented. Three-phase balanced, three-phase unbalanced, and single-phase examples all achieve an acceptable root mean square error of no more than 0.05 per-unit.
Mcdermott, Thomas E. [Private consulting company]↗
Design and performance assessment of a dual-mode latent thermal storage integrated heat pump across multiple climate zones
The electrification of space cooling and heating systems risks overloading the existing electrical grid during peak hours. Heat pumps integrated with thermal energy storage (HP-TES) offer a promising solution by shifting peak loads to off-peak hours, reducing grid strains. This work presents the design and assessment of a dual-mode HP-TES that uses a single 22°C phase-change material (PCM) as a heat source or sink in heating and cooling modes, respectively. Performance assessment was conducted using Modelica-based transient models, and full-year simulations were conducted across eight US climate zones using typical weather data. Two HP-TES performance metrics: peak energy reduction and recharge energy increases, were defined by comparing HP-TES energy consumption with base HP peak consumptions. Annual heating demand reductions (40–65%) exceeded cooling demand reductions (15–20%) due to the elimination of peak-hour backup heating. Cooling mode recharge energy requirements (0–10%) were reduced in locations with lower summer nighttime temperatures, while heating recharge requirements were lower than the high base-peak energy demand from backup heating. Simplified rapid methods that were 10 7 times faster than annual simulations were developed to predict seasonal cooling and heating energy reductions, and recharge energy requirements, with maximum deviations of ±2.5% and ±3.5% points. These methods enabled rapid parametric studies that identified optimal location-specific PCM temperatures between 22°C and 27°C, highlighting the need to consider both discharge and recharge energy requirements to achieve sustainable, energy-efficient peak load shifting across various climate zones.
25 ENERGY STORAGE↗
Dual Purpose – Heating & Cooling – Thermal Battery for Flexible and Energy-Efficient Heat Pump Systems
The integration of heat pumps with thermal energy storage (HP-TES) systems is gaining attention as a viable solution for managing peak building demand driven by immense cooling and heating loads. With growing reliance on renewable energy sources, thermal energy storage offers an excellent opportunity to mitigate mismatches in thermal load between energy supply and demand. The use of phase-change material (PCM) TES is especially promising, as PCMs offer significant latent energy storage capacity with smaller temperature glides in smaller volumes compared to other TES technologies. However, challenges arise because current HP-TES architectures can load-shift only cooling or heating, not both, requiring two systems and thus doubling cost, weight, and footprint. Furthermore, current research efforts lack specific tools and techniques to advance integrated systems from concept design to end-user application, focusing on only discharge performance. To address these challenges, this research proposes a dual-mode (heating and cooling) integrated HP-TES system that uses room-temperature PCM-TES as a high-temperature heat source in heating mode and a low-temperature heat sink in cooling mode, thereby reducing temperature lifts and compressor power. Design criteria for PCM-TES heat exchangers were developed, balancing thermal-hydraulic performance with practical constraints such as available building space and weight requirements along with PCM selection considerations such as shipping conditions, moisture exposure, and number of available cycles. A detailed transient model for HP-TES systems was developed to enable rapid annual performance assessments in any US climate zone.
42 ENGINEERING↗
SSR APPLIED – Automated Power Plants: Intelligent, Efficient and Digitised (V.2)
This report describes work undertaken during the SSR APPLIED project. The focus of the project has been on the development of digital twins to de-risk licensing of improved operating and maintenance practices. The operation of a bespoke flowing separate effects molten salt loop at ANL, with realistic temperature gradients, will provide invaluable data for computer codes validation. Three digital twins of aspects of the SSR-W have been successfully developed using ANL expertise and software. These digital twins have demonstrated optimization of the fuel cycle, the ability to model transients using an integrated coupled neutronic – thermal-hydraulic model with a model of the fuel expansion feedback so important to the inherent safety of the SSR-W. Advanced machine learning techniques have been developed and demonstrated for optimization of heat exchanger operation and maintenance.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Reduced-dimension Bayesian optimization for model calibration of transient vapor compression cycles
Development and calibration of first-principles dynamic models of vapor compression cycles (VCCs) is of critical importance for applications that include control design and fault detection and diagnostics. Nevertheless, the inherent complexity of models that are represented by large systems of differential–algebraic equations leads to significant challenges for model calibration processes that utilize classical gradient-based methods. Bayesian optimization (BO) is a sample-efficient and gradient-free approach using a probabilistic surrogate model and optimal search over a feasible parameter space. Despite the benefits of BO in reducing computational costs, challenges remain in dealing with a high-dimensional calibration task resulting from a large set of parameters that have significant impacts on system behavior and need to be calibrated simultaneously. This paper presents a reduced-dimension BO framework for calibrating transient VCCs models where the calibration space is projected to a low-dimensional subspace for accelerating convergence of the solution algorithm and consequently reducing the number of transient simulations. The proposed approach was demonstrated via two case studies associated with different VCC applications where 10 parameters were calibrated in each case using laboratory measurements. The reduced-dimension BO framework only required 1 / 8 th of the iterations associated with a standard BO method that deals with high-dimensional calibration parameters for converged solutions and yielded comparable accuracy. Furthermore, both calibrated models revealed significant accuracy improvements compared to uncalibrated models.
Ma, Jiacheng↗
Integrated Optimization and Control of a Hybrid Gas Turbine/sCO 2 Power System
During phase-I, the project team led by Echogen Power Systems (EPS) had two primary objectives based on investigating the application of gas turbines with supercritical carbon dioxide (sCO 2 ) power cycles. The first objective was to improve the overall efficiency and performance of a hybrid gas turbine/sCO 2 power system through a joint optimization of the two subsystems (gas turbine and sCO 2 power cycle) using non-linear optimization techniques that simultaneously evaluate thermal performance of the combined cycle. The hybrid power system included several points of interaction, including (but not limited to) gas turbine exhaust, fuel heating, inlet chilling and turbine cooling. The second objective was to establish a baseline transient response model of the hybrid power system and a notional microgrid and begin steps to integrate the control systems of the three major elements (gas turbine, sCO 2 cycle and grid controller). The project team established a baseline performance for a combined cycle power plant using a production gas turbine and scaled sCO 2 power cycle only utilizing exhaust heat recovery. Echogen’s non-linear techno-economic optimization code was extended by adding gas turbine component models derived from a in-house developed gas turbine design code. With the two cycles coupled by the gas turbine exhaust, design parameters of both cycles were allowed to vary simultaneously to determine performance opportunity versus isolated designs. Returning to the baseline gas turbine/sCO 2 power cycle transient models: Echogen had in-house developed sCO 2 cycle transient model in GT-Suite system simulation software, and had partnered with Siemens Finspång for gas turbine transient model, and Siemens PTI group to provide micro-grid load profile as well as hybrid power cycle generated load (power and frequency) analysis. The transient model for the SGT-750 Siemens gas turbine was a “black-box” functional mock-up interface (FMI) model developed by Siemens Industrial Turbomachinery in Finspång, Sweden. The SGT-750 is a twin-shaft gas turbine that produces 40 MW electricity with an efficiency of about 40% at ISO conditions. At 100% gas turbine throttle (load), the SGT-750 has average exhaust conditions of 114.6 kg/s and 469.8°C. The transient model for sCO 2 power cycle was developed by Echogen in GT-SUITE 1D system simulation software platform. The basic CO 2 flow circuit has single-shaft turbomachinery with net 11.5 MW electrical power output at design conditions. The power turbine has a double-ended shaft with one end connected to synchronous generator through a fixed-ratio gearbox. The other end of power turbine is connected to the compressor through a continuously variable transmission. The major components of the sCO 2 power cycle modeled include air cooled condenser/cooler, CO 2 compressor, recuperator, two waste heat exchanger coils, power turbine, continuous variable transmission, gearbox and generator. Integration of SGT-750 transient model and sCO 2 power cycle transient model was done in Matlab Simulink. In the integrated model, the gas turbine and sCO 2 power cycle interacted at two points, first one being the gas turbine exhaust gas flow rate and temperature, which were inputs to sCO 2 power cycle model. The second point was the distribution of micro-grid load demand signal between the SGT-750 generator and sCO 2 cycle generator. For a given combined-cycle load demand, the gas turbine load demand was equal to the total demand minus the sCO 2 cycle power generated. In the present study the integrated model was simulated for two cases of grid load demand: (i) for a step change, both positive-step and negative-step, in grid load demand (ii) for a micro-grid load demand curve provided by Siemens PTI group. Finally, the time series plots representing load demand versus integrated system response were presented including the sCO 2 power cycle control system performance plots. The actual generated power and frequency of both the generators, gas turbine and sCO 2 power cycle, was supplied to Siemens PTI group for dynamic grid assessment, results of which are provided in appendices.
03 NATURAL GAS↗
Estimation of Participation Factors Using the Synchrosqueezed Wavelet Transform
This paper proposes a data-driven approach for estimating participation factors for a power system using only simulation results on selected disturbances. The approach is purely response-based and does not need a linearized system model for eigen-analysis, which makes it applicable to systems whose detailed, complete mathematical models are not available. Considering the unavoidable nonlinearity as exhibited in the transient period of a system response, the Synchrosqueezed Wavelet Transform is applied to simulated responses for modal analysis to obtain participation factors. Based on simulations of Kundur's two-area system using both the electromagnetic transient model and phasor model, the participation factors estimated by the proposed approach are compared with two other signal processing tools, the Prony analysis and continuous wavelet transform, and are also benchmarked with conventional model-based participation factors.
participation factor↗
A Forward Feedback Control Scheme for a Solar Thermochemical Moving Bed Counter-Current Flow Reactor
Abstract Pelletized thermochemical energy storage media has a potential for long-duration energy storage. Production of solid-state energy storage media can be done within a cavity chemical reactor that captures concentrated solar radiation from a solar thermal field. The temperature stability of a solar reactor is directly influenced by the solar flux intercepted. This paper presents a low-order physical model to simulate the dynamic response of temperature inside a tubular plug-flow reactor prototype. Solid granular particles are fed to the reactor from the top whereas a counter-current flowing gas enters the reactor from the bottom. An in-house code was developed to model transient heat transfer of the reactor wall, gas, and moving particles. The model was preliminarily validated with packed beds for different temperature ranges and two gas flowrates. Dynamic response of the reactor temperature is simulated for different input power and gas/particle flowrates. The results show that the system response can be controlled efficiently by utilizing input power (solar flux) as a control parameter. A conventional proportional integral (PI) controller is designed to control the temperature inside the reactor and to maintain it during the solar flux intermittency. The controller parameters are tuned using the Ziegler–Nichols method to ensure optimal system response. The results show that the feedback control model is successful in tracking different reference reactor temperatures within a reasonable settling time of 30 min and eliminated overshoot. This study can be extended to include a hybrid reactor with a multi-input, multi-output variable system.
Energy & Fuels↗
Initial Demonstration of New Griffin Technologies for Simulating the Running-In Phase of Pebble Bed Reactors
Griffin is a reactor multiphysics modeling application based on MOOSE (Multiphysics Object-Oriented Simulation Environment) and specifically targeting transient modeling of advanced reactors. Griffin has been used recently to model pebble-bed reactors for the Nuclear Regulatory Commission (NRC) Office of Nuclear Regulatory Research and the Advanced Reactor Technology program. This modeling work has focused thus far on the direct calculation of equilibrium cores. This report documents an initial demonstration of a new running-in simulation capability. The new running-in capability is verified using the existing direct equilibrium core calculation capability. A simplified pebble-bed reactor model is then used to demonstrate the running-in simulation capability. This demonstration shows that Griffin is able to simulate years of operation during the running-in phase efficiently with each depletion step taking only several seconds. Two new technologies are also presented in this report which have been developed in Griffin that will be essential for improved accuracy both of the direct equilibrium core computation and the new running-in simulation capability. The first technology is an online cross section generation capability specifically targeted for pebble-bed reactors. This will improve the accuracy of the depletion calculation as the cross sections are generated at the exact core status. This also avoids the difficult step of pre-generating a separate standalone multigroup cross section set. Secondly, a newly implemented discretization for discontinuous finite element method (DFEM) SN transport in cylindrical (RZ) coordinates, which can be solved efficiently using the existing SN sweep solver, is discussed and some results are shown demonstrating the usefulness of the additional accuracy transport provides over a diffusion approximation.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
EXERGETIC: De-Risking Next-Generation Resilient Geothermal Hybrids via At-Scale Evaluation Using Virtual Emulation Digital Twin Environment for Efficient Operation
The DOE-GTO-funded project, award number 5.1.2.12, entitled "EXERGETIC - De-risking Next Generation Resilient Geothermal Hybrids via at-Scale Evaluation Using a Virtual Emulation Digital Twin Environment for Efficient Operation," advances the solution to these challenges by developing and validating a geothermal co-emulation environment implemented at the National Laboratory of the Rockies (NLR)'s Advanced Research on Integrated Energy Systems (ARIES) platform. This framework enables the de-risking of next-generation geothermal and geothermal hybrid systems through high-fidelity modeling, real-time digital emulation, advanced control strategies, and techno-economic assessment. The project focused on geothermal hybrid configurations that integrate geothermal power plants with concentrated solar power and underground thermal energy storage, enabling enhanced efficiency, flexibility, and grid support capabilities. The main goal of this project was the development of a geothermal digital co-emulation environment to demonstrate the technical and economic value of geothermal hybrid systems and their contribution to grid stability and flexibility. The EXERGETIC framework combined physics-based models, controls, and real assets at ARIES, including digital real-time simulators (DRTS), a 20-MW-scale controllable grid interface (CGI), and a 2-MW conventional generator. Detailed transient models were developed for the key subsystems of a hybrid geothermal plant, including parabolic trough solar collectors, reservoir thermal energy storage (RTES), and a binary Organic Rankine Cycle (ORC) power plant. The ORC model explicitly captured thermal inertia and off-design operation and integrated control strategies to dynamically respond to electric load profiles. The models were validated against published experimental and numerical studies, demonstrating strong agreement and confirming the accuracy and robustness of the modeling approach. The resulting digital twin represents geothermal-solar-storage systems at multiple scales (1 MW to 100 MW) and enables realistic emulation of grid-connected operation. The control architecture allows the geothermal resource to provide stable baseload generation, while solar and stored thermal energy supply flexible, dispatchable support during periods of high demand or variable grid conditions. A key contribution of the EXERGETIC project is the demonstration that geothermal hybrid systems can be designed to be active grid assets rather than passive baseload generators. Using the ARIES platform, the digital twin was evaluated under multiple grid scenarios, including load following, voltage support at the distribution level, and frequency response at the transmission level. Results show that hybrid geothermal systems can respond effectively to dynamic grid conditions, providing inertia-like behavior, primary frequency support, and voltage regulation through coordinated control. In addition to the performance and grid services capability analysis of geothermal and hybrid geothermal systems, the EXERGETIC project also focused on scalability and techno-economic analysis of geothermal hybrid plants. In particular, for the scalability analysis, machine-learning (ML)-based surrogate models were trained using data generated from the geothermal digital twin under different grid-connected scenarios and plant capacities. These ML models demonstrated strong interpolation and extrapolation capabilities across plant sizes, accurately reproducing both steady-state and transient responses with very low errors. Regarding the techno-economic analysis, plant performance results were integrated with cost models for hybrid geothermal systems, and the levelized cost of electricity (LCOE) was used as the main economic metric to evaluate system performance across a range of system capacities, solar shares, solar multiples, and storage durations. Results indicate that economies of scale significantly reduce geothermal LCOE as plant capacity increases, with large-scale systems (25-100 MW) achieving substantially lower costs than small plants. Hybridization with solar thermal energy and storage further improves economic performance by increasing capacity utilization and enabling flexible dispatch. In addition, thermal storage plays a critical role in reducing LCOE by maximizing geothermal, solar, and stored energy resources. In summary, the results from this project demonstrate that geothermal hybrid systems represent a promising alternative for increasing the energy conversion efficiency of geothermal technologies, contributing to the preservation of geothermal resources, and supporting the transition of geothermal plants from traditional baseload resources into flexible, resilient, and cost-competitive energy conversion technologies.
15 GEOTHERMAL ENERGY↗
Design tool for estimating metal hydride storage system characteristics for light-duty hydrogen fuel cell vehicles
The U.S. Department of Energy (DOE) has developed the Framework model to simulate fuel cell-based light-duty vehicle operation for various hydrogen storage systems. This transient model simulates the performance of the storage system, fuel cell, and vehicle for comparison to DOE's Technical Targets using four drive cycles. Metal hydride hydrogen storage models have been developed for the Framework model. Despite the utility of this model, it requires that material researchers input system design specifications that cannot be easily estimated. To confront this challenge, a design tool has been developed that allows researchers to directly enter physical and thermodynamic metal hydride properties into a simple sizing module that then estimates the systems parameters required to run the storage system model. This design tool can also be used as a standalone MS Excel model to estimate the storage system mass and volume outside of Framework and compare it to the DOE Technical Targets. This model will be explained and exercised with existing hydrogen storage materials.
33 ADVANCED PROPULSION SYSTEMS↗
Unified Model of Current-Limiting Grid-Forming Inverters for Large-Signal Analysis
Grid-forming (GFM) inverters can hardly withstand any overloading. As such, GFM inverters need a current limiter in their control system to avoid hardware damage during overloading or grid disturbances. When the current limiter is engaged for inverter protection, however, it dynamically changes the inverter output impedance, which can significantly affect the system behavior against large disturbances. For example, when the current limiter curtails the output power, the primary controller of the GFM inverter-which generates the voltage and angle reference-is prone to losing synchronization with the grid. This can cause large-signal instability in the network. This paper presents a unified GFM current-limiter model to gain a deeper understanding of the impact of the GFM inverter current limiting on large-signal instability and other system behaviors. The unified model captures several well-known current limiters for GFM inverters, and it reveals their large-signal equivalence characterized by the limiter angle. We use the unified model to present in-depth insights into the driving forces that cause large-signal instability in GFM inverter-driven grids. Further, this paper illustrates that the unified model can be used as a tool for assessing the system-level impacts of various GFM current-limiter designs during grid disturbances. Using numerical, analytical, electromagnetic transient models, and a hardware setup, the validity of the unified model is evaluated.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Transient Analysis of a Micro-reactor using the DireWolf Code Suite
Transient analyses of heat pipe micro-reactors are necessary to ensure that hypothetical accident scenarios do not comprise reactor safety. Due to its small size and reliance on heat-pipes for cooling, the micro-reactor design introduced in this paper is a tightly coupled system which requires multi-physics tools to accurately model transient events. Idaho National Laboratory’s DireWolf code suite based on the MOOSE framework is tailor-built to model heat-pipe reactors. This paper demonstrates DireWolf’s ability to simulate the coupled thermal-neutronics transient behavior of a heat-pipe micro-reactor. The transient events presented here include an inadvertent rotation of all control drums simultaneously and a sudden complete ejection of a single control drum. A detailed description of each event is provided along with simulation results, including time dependent power and temperature distributions, and discussion. This is a Westinghouse Electric Company (WEC) led publication.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Transient analysis of a micro-reactor using the DireWolf code suite
Transient analyses of heat pipe micro-reactors are necessary to ensure that hypothetical accident scenarios do not comprise reactor safety. Due to its small size and reliance on heat-pipes for cooling, the micro-reactor design introduced in this paper is a tightly coupled system which requires multi-physics tools to accurately model transient events. Idaho National Laboratory's DireWolf code suite based on the MOOSE framework is tailor-built to model heat-pipe reactors. This paper demonstrates DireWolf's ability to simulate the coupled thermal-neutronics transient behavior of a heat-pipe micro-reactor. The transient events presented here include an inadvertent rotation of all control drums simultaneously and a sudden complete rotation of a single control drum. A detailed description of each event is provided along with simulation results, including time dependent power and temperature distributions, and discussion. (authors)
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
SAM Code Enhancement, Validation, and Reference Model Development for Fluoride-salt-cooled High-temperature Reactors
The System Analysis Module (SAM) is under development at Argonne National Laboratory as a modern system-level modeling and simulation tool for advanced non-light water reactor safety analyses. It utilizes the object-oriented application framework MOOSE to leverage the modern software environment and advanced numerical methods. The capabilities of SAM are being extended to enable the transient modeling, analysis, and design of various advanced nuclear reactor systems. This report summarizes recent progress under DOE-NE’s Nuclear Energy Advanced Modeling and Simulation program in SAM code development, demonstration, and validation to support transient safety analysis of Fluoride-salt-cooled High-temperature Reactors.
22 GENERAL STUDIES OF NUCLEAR REACTORS↗
Aggregate data‐driven dynamic modeling of active distribution networks with DERs for voltage stability studies
Abstract Electric distribution networks increasingly host distributed energy resources based on power electronic converter (PEC) toward active distribution networks (ADN). Despite advances in computational capabilities, electromagnetic transient models are limited in scalability because of their reliance on exact data about the distribution system and each of its components. Similarly, the use of the DER_A model, which is intended to examine the combined dynamic behavior of many DERs, is limited by the difficulty in parameterization. There is a need for improved dynamic models of DERs for use in large power system simulations for stability analysis. This paper proposes an aggregate model‐free, data‐driven approach for deriving a dynamic partitioned model (DPM) of ADNs. Detailed residential distribution feeders were first developed, including PEC‐based DERs and composite load models (CMLDs), from which the aggregated DPM was derived. The performance was evaluated through various case studies and validated against the detailed ADN model and state‐of‐the‐art DER_A model with CMLD. The data‐driven DPM achieved a of over 90%, accurately representing the aggregated dynamic behavior of ADNs. Furthermore, the DPM significantly accelerated the simulation process with a computational speedup of 68 times compared to the detailed ADN and a 3.5 times speedup compared to the DER_A CMLD model.
42 ENGINEERING↗