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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 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

A Low Voltage DC Power Electronic Hub to Support Buildings

This paper presents the communication, control, and architecture, for a low voltage (nominal 480V) hybrid AC/DC microgrid for supporting small commercial buildings with critical data center loads. The proposed system is based on a dc-power electronic hub (PEH) that seamlessly integrates renewable energy resources, energy storage, and back-up generation to support commercial building economical energy management and reliability. This PEH concept provides a parallelization of critical power to the commercial and industrial buildings leading to increased efficiency and reliability compared to traditional uninterruptable power supplies. The demonstration of the proposed PEH architecture and controls is conducted through a controller hardware in the loop validation.

Starke, Michael↗
DOE OSTI2021

DYFLOW: A flexible framework for orchestrating scientific workflows on supercomputers

Modern scientific workflows are increasing in complexity with growth in computation power, incorporation of non-traditional computation methods, and advances in technologies enabling data streaming to support on-the-fly computation. These workflows have unpredictable runtime behaviors, and a fixed, predetermined resource assignment on supercomputers can be inefficient for overall performance and throughput. Inability to change resource assignments further limits the scientists to avail of science-driven opportunities or respond to failures.We introduce DYFLOW, a flexible framework that orchestrates scientific workflows on supercomputers based on user-designed policies. DYFLOW compartmentalizes orchestration stages into simplified constructs, and end-users can program and reuse them according to their workflow requirements through an easy-to-use interface. These constructs hide the intricacies involved in runtime management from end-users, for instance, procurement of information to understand the workflow state, assessment, and supervision of the runtime changes. DYFLOW is designed to work alongside existing workflow management systems and reuse the available (static) support for workflow management. We have integrated DYFLOW with an existing workflow management tool as a demonstration. With experiments performed on use cases from three types of scientific workflows and two different parallel architectures, we show that DYFLOW achieves the desired orchestration incurring a small cost to carry out the runtime changes.

Singhal, Swati↗
DOE OSTI2021

Integrating Advanced Modeling and Accelerated Testing for a Modernized Fuel Qualification Paradigm

With the increasing interest in sodium fast reactor technology, as seen by applications to the U.S. Nuclear Regulatory Commission for the OKLO Aurora plant, fuel testing for the TerraPower Traveling Wave Reactor, and the impending construction and startup of the versatile test reactor (VTR), a modernized, accelerated approach to fuel qualification is needed. To guide this effort, a Phenomena Identification Ranking Table–styled analysis was performed for a U-Pu-Zr sodium-free annular fuel system. This analysis evaluated a series of fuel design properties and parameters against their contributions to key fuel performance phenomena. The resulting priority parameters were then reviewed against existing modeling and experimental capabilities to support investigation of the highest-priority parameters. A pathway for qualification was then established using highthroughput, high-volume experiments from MiniFuel and FAST in parallel with advanced physics-based model development. This effort outlines how the first stages of qualification can be reduced from the typical 20+-year development cycle to 5 to 7 years by deploying accelerated irradiation testing platforms. As with any accelerated test, these methods are prototypic in some aspects and less so in others; however, by coupling with advanced fuel performance modeling and simulation capabilities, the larger space of irradiation parameters and material response provided offers advantages for the validation of physics-based models supporting the deployment of novel fuel designs. As a test case, this paper utilizes a proposed Mark II fuel system for the upcoming VTR. Thus, an accelerated qualification method can be tested for the development of MARK II driver fuel so that by the time of VTR startup, lead test assemblies for a Mark II fuel can be initiated.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

OpenACC unified programming environment for GPU and FPGA multi-hybrid acceleration

Attached accelerators have been frequently used in recent High Per- formance Computing (HPC) systems because of their high performance/power ratio. In particular, the Graphics Processing Unit (GPU) is the most popu- lar accelerator owing to its high peak FLOPS performance and high memory bandwidth supported by HBM2, etc. However, the performance of GPU depends highly on a large degree of SIMD parallelism and has difficulty sustaining a high performance on programs with frequent branch operations or a partially low degree of parallelism.By contrast, a Field Programmable Gate Array (FPGA) has received attention as a different type of accelerator than GPU as a fully reconfigurable processor fitting the target applications. The high performance of FPGA is mainly provided by a pipelined operation and optimized circuit suitable for any operation even with frequent conditional branches. We have been focusing on the flexibility of FPGA to compensate for the weakness of GPU. We believe that the coupling of GPU with FPGA can result in one of the most powerful accelerating platforms available.However, the program coding of GPU and FPGA coupling can be quite difficult for application users. Traditionally, CUDA by NVIDIA has been the most popular programming language with the largest share of GPUs used in HPC, whereas a hardware description language such as Verilog HDL has been used in FPGA programming. OpenCL coding has recently become available even on high-end FPGAs. Moreover, several recent studies have also enabled the OpenACC coding for use in FPGA. In this study, we provide a unified programming system based on OpenACC for a platform equipped with both GPU and FPGA aiming at the next-generation accelerated supercomputer framework. Our programming environment is called Multi-Hybrid OpenACC Translator (MHOAT), and in this paper, we describe the basic concept and prototype system of MHOAT based on an evaluation on the amount of coding required and the performance of a hybrid multi-device accelerated system.

Tsunashima, Ryuta↗
DOE OSTI2021

Progress on Optimizing Wind Farms and Rotor Designs Using Adjoints

Modern wind plants are increasingly tasked with multiple performance objectives. In addition to designing plants that maximize power output and minimize the levelized cost of energy (LCOE), the design and operation of wind plants is increasingly influenced by challenges regarding grid integration of variable generation renewables. This places a growing emphasis on making wind plants more controllable and predictable. WindSE is a Reynolds-averaged Navier-Stokes (RANS) model designed around analytical gradient and adjoint methods, with the ability to capture terrain-induced effects, as shown in Figure 1. The recent addition of an unsteady solver with an actuator line method (ALM) and ongoing work to enable massively parallel optimizations gives it a unique niche to explore coupled plant-level controls and design problems. This code is an open source python package built on the FEniCS framework that utilizes fast, parallel PETSc solvers to model fluid flow throughout wind-farm scale domains. Two recent studies performed using WindSE demonstrate the capability to optimize under a wide variety of flow conditions and objective functions. In the first, we present an optimization focused on modifying the layout of a wind farm with a fixed number of turbines for maximum total power output [1]. This study highlights the ability to quickly perform simulations using the steady Navier-Stokes solver combined with rotors represented as actuator disks while also stressing the importance of capturing terrain-induced effects. Gradient-based optimization using the RANS equations is viable due to the inclusion of efficiently computed adjoint derivatives. We interpret the physical results of the optimal layout and also discuss the computational cost of scaling to larger problems. In the second study, we present the capabilities of the unsteady Navier-Stokes solver, where rotor-blade profiles represented by actuator lines are optimized to enhance wake steering effects and overall power production [2]. We quantify the wind plant performance gains obtained from this type of simultaneous control co-design optimization as compared to optimizing the blade design and yaw independently. Figure 2 shows the differences between a baseline two-turbine system and an optimized system where we fine-tune the blade chord profile. Results and challenges from each study are quickly summarized and used to motivate the current development efforts within WindSE. Current and future work is focused on enabling higher-resolution studies with more degrees of freedom through parallelization of both the simulation and optimization algorithms. We present benchmarking results to show that WindSE performs well in both weak- and strong-scaling tests and further demonstrate that the optimizer obtains the same convergence rates in both shared- and distributed-memory environments. Using larger wind farms, we can study deep-array effects within an optimization context, allowing the use of objective functions that have been previously unstudied. As an example, we present ongoing work on a blockage metric which characterizes the loss of available kinetic energy due to wake effects from multiple upstream turbines.

adjoint optimization↗
DOE OSTI2026

The sweeper spectrometer for neutron invariant-mass spectroscopy at FRIB

Neutron invariant-mass spectroscopy (NIMS) is a key technique for studying unbound and weakly bound nuclei at the limits of stability. At the Facility for Rare Isotope Beams (FRIB), such measurements are performed using the Sweeper spectrometer, a large-gap, high-rigidity dipole system coupled to the MoNA-LISA neutron detector arrays. To meet the demands imposed by higher beam energies (>130 MeV/u) and the broad cocktail-beam selection available at FRIB, the spectrometer has recently been upgraded to improve particle-identification and detection performance. Upstream of the reaction target, a plastic scintillator with Silicon photomultiplier (SiPM) readout provides the global trigger and time reference, two parallel plate avalanche counters (PPACs) track the trajectories of incoming beam particles, and a silicon PIN detector measures the energy loss, ΔE, for charge (Z) identification. After the Sweeper magnet, the trajectories of the reaction products are tracked by two micro-pattern drift chambers (MPDCs), their charge (Z) is identified by a Frisch-grid ionization chamber (FG-IC), and their mass-to-charge ratio (A/Q) is deduced by time-of-flight measurement using a fast plastic scintillator read out by an array of photomultiplier tubes (PMTs). The detection system also incorporates the Modular Neutron Array (MoNA) for neutron detection and the CAESium-iodide scintillator ARray (CAESAR) for high-efficiency γ-ray measurements to enable full kinematic reconstruction. Performance was evaluated using a cocktail beam around 37 Al accelerated at E ≈ 130 MeV/u during the first FRIB campaign, demonstrating the readiness of the upgraded system for future studies of nuclei at and beyond the neutron drip line.

Particle identification methods↗
DOE OSTI2021

Reaction Mechanism Generator v3.0: Advances in Automatic Mechanism Generation

In chemical kinetics research, kinetic models containing hundreds of species and tens of thousands of elementary reactions are commonly used to understand and predict the behavior of reactive chemical systems. Reaction Mechanism Generator (RMG) is a software suite developed to automatically generate such models by incorporating and extrapolating from a database of known thermochemical and kinetic parameters. Here, we present the recent version 3 release of RMG and highlight improvements since the previously published description of RMG v1.0. Most notably, RMG can now generate heterogeneous catalysis models in addition to the previously available gas- and liquid-phase capabilities. For model analysis, new methods for local and global uncertainty analysis have been implemented to supplement first-order sensitivity analysis. The RMG database of thermochemical and kinetic parameters has been significantly expanded to cover more types of chemistry. The present release includes parallelization for faster model generation and a new molecule isomorphism approach to improve computational performance. RMG has also been updated to use Python 3, ensuring compatibility with the latest cheminformatics and machine learning packages. Overall, RMG v3.0 includes many changes which improve the accuracy of the generated chemical mechanisms and allow for exploration of a wider range of chemical systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Efficient solvers for hybridized three-field mixed finite element coupled poromechanics

We consider a mixed hybrid finite element formulation for coupled poromechanics. A stabilization strategy based on a macro-element approach is advanced to eliminate the spurious pressure modes appearing in undrained/incompressible conditions. The efficient solution of the stabilized mixed hybrid block system is addressed by developing a class of block triangular preconditioners based on a Schur-complement approximation strategy. Robustness, computational efficiency and scalability of the proposed approach are theoretically discussed and tested using challenging benchmark problems on massively parallel architectures.

42 ENGINEERING↗
DOE OSTI2024

Sustainable aviation fuels from biomass and biowaste via bio- and chemo-catalytic conversion: Catalysis, process challenges, and opportunities

Sustainable aviation fuel (SAF) production from biomass and biowaste streams is an attractive option for decarbonizing the aviation sector, one of the most-difficult-to-electrify transportation sectors. Despite ongoing commercialization efforts using ASTM-certified pathways (e.g., lipid conversion, Fischer-Tropsch synthesis), production capacities are still inadequate due to limited feedstock supply and high production costs. New conversion technologies that utilize lignocellulosic feedstocks are needed to meet these challenges and satisfy the rapidly growing market. Combining bio- and chemo-catalytic approaches can leverage advantages from both methods, i.e., high product selectivity via biological conversion, and the capability to build C-C chains more efficiently via chemical catalysis. Herein, conversion routes, catalysis, and processes for such pathways are discussed, while key challenges and meaningful R&D opportunities are identified to guide future research activities in the space. Bio and chemo-catalytic conversion primarily utilize the carbohydrate fraction of lignocellulose, leaving lignin as a waste product. This makes lignin conversion to SAF critical in order to utilize whole biomass, thereby lowering overall production costs while maximizing carbon efficiencies. Thus, lignin valorization strategies are also reviewed herein with vital research areas identified, such as facile lignin depolymerization approaches, highly integrated conversion systems, novel process configurations, and catalysts for the selective cleavage of aryl C–O bonds. The potential efficiency improvements available via integrated conversion steps, such as combined biological and chemo-catalytic routes, along with the use of different parallel pathways, are identified as key to producing all components of a cost-effective, 100% SAF.

09 BIOMASS FUELS↗
DOE OSTI2021

Multi-objective optimization with an integrated electromagnetics and beam dynamics workflow

In particle accelerators, RF cavities are used to accelerate charged particle beams to designed high energy for physical applications. In a typical accelerator design, the optimization of RF cavities and the optimization of beam dynamics are carried out in separate studies. For a more general and unrestricted accelerator design, a coupled optimization of the RF cavities and the beam parameters is required. For this coupled optimization problem, we have developed an integrated electromagnetics and beam dynamics workflow management system. Within this system, the geometries for a set of cavity components are first adjusted; the field modes are then computed with an electromagnetics program, and imported into a beam dynamics program for beam dynamics simulation. This workflow is encapsulated into a parallel multi-objective optimizer to achieve the integrated accelerator design optimization. A multi fidelity strategy is developed to improve the speed of the optimizer. Furthermore, this integrated global optimization capability is illustrated using a photoinjector design example and yields an improved design.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2024

Bifurcation of equilibrium positions for ellipsoidal particles in inertial shear flows between two walls

We conducted a systematic numerical investigation of spherical, prolate and oblate particles in an inertial shear flow between two parallel walls, using smoothed particle hydrodynamics (SPH). It was previously shown that above a critical Reynolds number, spherical particles experience a supercritical pitchfork bifurcation of the equilibrium position in shear flow between two parallel walls, namely that the central equilibrium position becomes unstable, leading to the emergence of two new off-centre stable positions (Foxet al.,J. Fluid Mech., vol. 915, 2021). This phenomenon was unexpected given the symmetry of the system. In addition to confirming this finding, we found, surprisingly, that ellipsoidal particles can also return to the centre position from the off-centre positions when the particle Reynolds number is further increased, while spherical particles become unstable under this increased Reynolds number. By utilizing both SPH and the finite element method for flow visualization, we explained the underlining mechanism of this reverse of bifurcation by altered streamwise vorticity and symmetry breaking of pressure. Furthermore, we expanded our investigation to include asymmetric particles, a novel aspect that had not been previously modelled, and we observed similar trends in particle dynamics for both symmetric and asymmetric ellipsoidal particles. While further validation through laboratory experiments is necessary, our research paves the road for development of new focusing and separation methods for shaped particles.

Mechanics↗
DOE OSTI2021

Exascale models of stellar explosions: Quintessential multi-physics simulation

The ExaStar project aims to deliver an efficient, versatile, and portable software ecosystem for multi-physics astrophysics simulations run on exascale machines. The code suite is a component-based multi-physics toolkit, built on the capabilities of current simulation codes (in particular Flash-X and Castro), and based on the massively parallel adaptive mesh refinement framework AMReX. It includes modules for hydrodynamics, advanced radiation transport, thermonuclear kinetics, and nuclear microphysics. The code will reach exascale efficiency by building upon current multi- and many-core packages integrated into an orchestration system that uses a combination of configuration tools, code translators, and a domain-specific asynchronous runtime to manage performance across a range of platform architectures. The target science includes multi-physics simulations of astrophysical explosions (such as supernovae and neutron star mergers) to understand the cosmic origin of the elements and the fundamental physics of matter and neutrinos under extreme conditions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Improvements to MOOSE user workflow through polyhedral elements, automation, and concise physics syntax

The MOOSE framework is a foundational capability used by the NEAMS program to create over 15 different simulation tools for advanced nuclear reactors. Due to MOOSE's broad use, improvements to the framework in support of modeling and simulation goals are critical to the program. Such improvements can take many forms, including optimization, improved user experience, streamlined application programming interfaces (APIs), parallelism, and new capabilities. The work described in this report was conducted in direct support of NEAMS tools and includes: addition of support for polyhedral elements, incorporation of mesh smoothers for mesh repair, integration of the Physics and ActionComponents systems, expansion of the Convergence system, and exploration of automated input file generation. These five areas of development are fundamental capabilities that will be leveraged by many NEAMS applications.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Turbulent mixing by microscopic self-assembled spinners

A system for mixing particles that includes a liquid comprising inert particles and defining a liquid and air interface; magnetic microparticles suspended at the liquid and air interface; and a magnetic source configured to apply a uniaxial alternating magnetic field parallel to the liquid and air interface, wherein the uniaxial alternating magnetic field promotes a turbulent motion of the magnetic microparticles, which in turn promotes a diffusive motion of the inert particles.

Snezhko, Oleksiy↗
DOE OSTI2022

Electromagnetic propulsion system

An electromagnetic propulsion system comprises a plurality of stator coils wound about a first axis, a plurality of support structures, a coupler that surrounds a portion of the stator coils, and a plurality of rotor coils wound about an axis that is parallel to the first axis. The stator coils are configured to receive electric current to induce a first magnetic field. The support structures support the stator coils. The coupler includes a notch oriented so that one of the support structures can pass through the notch when the coupler moves along the stator coils. The rotor coils are attached to the coupler and are configured to receive electric current to induce a magnetic field that interacts with the first magnetic field so that a magnetic force is applied to the rotor coils, thereby propelling the coupler and the rotor coils along the stator coils.

Hartman, Seth↗
DOE OSTI2020

Distributed fiber sensing systems for 3D combustion temperature field monitoring in coal-fired boilers using optically generated acoustic waves (Final Report)

In this project, we have developed and tested three kinds of fiber optic sensing systems for real time monitoring of temperature variations within an industrial scale boiler furnace. The fiber optic sensing systems target spatial and temporal distributions of high temperature profiles in a boiler furnace in fossil power plants. The reconstructed temperature profile will provide critical input for the control mechanisms to optimize the combustion process. This temperature profile will address the essential problem for fossil power plants in achieving higher efficiency and fewer pollutant emissions. Acoustic pyrometer systems have been used to reconstruct temperature field of power plant boilers based on measuring TOF (times-of-flight) of sound waves along some straight paths in a 2D cross-section of the boiler. In this project, optically generated acoustic signals from a fiber optic sensing system have replaced the acoustic signals generated from an electrical transducer. A 3D reconstruction algorithm replaced the previous 2D model. In this project, three kinds of fiber optic sensing systems have been developed and tested. They are fiber optic sensing system I, fiber optic sensing system II (Distributed Sensing System I) and fiber optic sensing system III (Distributed Sensing System II). For fiber optic sensing system I, the fiber optic ultrasound generator acts as a signal generator. A microphone, hydrophone or other electronic devices serve as a signal receiver. In this system, there are one generator and one receiver. Distance test, water temperature test, air temperature test, air temperature reconstruction, and GE ISBF pilot test were performed by Fiber optic sensing system I. The fiber optic sensing system I successfully detected temperature in all these tests. We got 2D temperature reconstruction results by using the fiber optic sensing system I and it matched the reference data. The fiber optic sensing system I successfully survived in GE ISBF boiler environment (480 °F). For fiber optic sensing system II (Distributed Sensing System I), it is an all optical ultrasound system. The fiber optic ultrasound generator acts as a signal generator. Fiber Bragg Grating (FBG) and Fabry-Perot (FP) sensor act as a signal receiver. In this system, there is one generator and one receiver. Aluminum plate temperature test, furnace high temperature test, and GE ISBF pilot test were performed by the fiber optic sensing system II. Fiber optic sensing system II successfully detected the temperature in all these tests. The fiber optic sensing system II successfully survived at up to 700 °C furnace environment and 320 °C GE ISBF boiler environment. For fiber optic sensing system III (Distributed Sensing System II), it is also an all optical ultrasound system. The fiber optic ultrasound generator acts as a signal generator. Multiple FP fiber sensors act as signal receivers. In this system, there is one generator and three receivers. Three GE ISBF pilot tests were performed by fiber optic sensing system III. The fiber optic sensing system III survived in the cold flow tests in GE’s ISBF pilot test facility. However, we didn’t get high temperature data by using this system since the nanosecond laser issues. During the period of the project, test trials, data simulation and algorithm optimization was performed successfully. For real time temperature field construction, the sampling rate must be fast enough to capture the field variations. The technology of Code-division multiple access (CDMA) is well studied which could allow parallel multiplexing, even if signals overlap in time or frequencies. Moreover, it has been known that extending the length of signal significantly improves SNR. For acoustic signals, these multiplexing techniques have also been widely used, mainly for sonar and acoustic communications. The CDMA modulation technique has been proposed and studied to guarantee high network throughput, low channel access delay and low energy consumption. We have studied the temperature field reconstruction using Gaussian Radial Basis Functions (GRBF)-based approximation approach. Reconstruction of 3D temperature field using Neural Networks with measured TOF and known propagation paths is feasible. 2D and 3D temperature field reconstruction simulation results are achieved. The milestone status is shown in Table 1. We finished milestone 1-8 and milestone 10. For milestone 9, we did three pilot tests by using the fiber optic sensing system III (Distributed Sensing System II) at GE Power. However, due to the failure of the ns laser, we did not get the temperature results. We conducted some additional tasks that were not originally proposed: 1) We fabricated a fiber optic sensing system I and did a pilot test based on this system. 2) In the proposal, we proposed two pilot tests at GE Power. In reality, we finished at least seven pilot tests at GE Power. GE Power has made a lot of efforts for supporting the pilot tests. 3) We got a simulation results based on CDMA. In summary, most of the tasks have been accomplished. The outcome of this project removed a few barriers that hinder the achievement of the final product of the distributed sensing systems. With the successful accomplishment of this project, a prototype of the fiber optic sensing system can be fabricated to attract more interests from companies and other funding agencies.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Bayesian model updating with finite element vs surrogate models: Application to a miter gate structural system

Bayesian finite element (FE) model updating using direct model evaluations of large-scale high-fidelity FE models is extremely computationally expensive. Surrogate models can be used as fast emulators of FE models to accelerate the model calibration process. The physics/mechanics-based FE models are still the underpinning behind the surrogate models. Here, this paper evaluates the loss in accuracy and the gain in computational time while performing Bayesian model updating by using surrogate model evaluations compared to using direct FE model evaluations. This evaluation is crucial before entirely relying on surrogate models in model updating for structural health monitoring (SHM) and damage prognosis (DP) purposes. This paper also demonstrates Bayesian updating and surrogate model construction of large-scale high-fidelity FE models of infrastructure systems. In this regard, the miter gate structural system is considered as the testbed structure. Three predominant damage modes (loss of contact between gate and wall, loss of thickness due to corrosion, and loss of tension in the diagonal rods) are considered for model updating purposes. Bayesian model updating is performed using direct FE evaluations by leveraging parallel computing. Two types of surrogates, namely polynomial chaos expansion (PCE) and Gaussian process regression (GPR), are developed for the miter gate. Model updating is performed again using the trained surrogate models, and the updating results are compared with their counterparts obtained using the direct FE evaluation results. The posterior distribution of the FE model parameters obtained using the trained surrogates are sufficiently accurate with respect to the posterior obtained utilizing the direct FE evaluations. In addition, an approximate 4-fold decrease in the computational time was observed when using surrogate model evaluations instead of direct FE evaluations for model updating.

42 ENGINEERING↗
DOE OSTI2022

End-to-end Analytics for Grid Arch Design & All-hazard Assessment

Resiliency, reliability, and security of the next-generation smart grid depend upon leveraging advanced communication and computing technologies, integrating them with physical power systems, and developing real-time, fast, data-based applications to help in wide-area monitoring and control of the grid. Using a high sampling data rate from phasor measurement units (PMUs) to develop applications has opened the door to achieving the next-generation grid requirements. The North American Synchrophasor Initiative Network (NASPlnet) was developed in 2007-09 to create a standard and guide for PMU data exchanges. With the advancement in both networking and grid requirements, it is necessary to evaluate the performance of different NASPInet versions and their impact on applications. Therefore, we need a cyber-power cosimulation framework that supports very large-scale co-simulation capable of running in parallel, high-performance computing platforms and capturing real-life network behavior. This work presents a cyber-physical co-simulation testbed using NS3 to model the communication network, GridPACK to model the power grid, and HELICS as a co-simulation engine. Comparative analysis of latency in synchrophasor networks and a performance evaluation of a power system stabilizer application based on PMU data in an Institute of Electrical and Electronics Engineers 39-bus test system is presented using this co-simulation testbed.

24 POWER TRANSMISSION AND DISTRIBUTION↗