Resilient Adaptive Parallel sImulator for griD (RAPID): An Open Source Power System Simulation Toolbox
Not Available
42 ENGINEERING↗
SEARCH · Search NASA
Results for “power system simulation”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
A Participation Factor-Based Approach for Defining the EMT Model Boundary for Power System Simulations with Inverter-Based Resources
The increasing penetration of inverter-based resources (IBRs) introduces new challenges to power system simulations, particularly with the emergence of fast electromagnetic transient (EMT) dynamics and sub-synchronous oscillations (SSO) that require time-consuming EMT simulations. To reduce the time cost for simulating a large-scale power grid with IBRs, this paper proposes a novel participation factor-based approach for defining a critical zone for detailed EMT modeling and simulations, which includes the IBRs, synchronous generators, and the network components participating significantly in simulated contingencies. Both model-based and response-based methods are introduced for the estimation of participation factors (PFs). The case study on the 240-bus Western Electricity Coordinating Council (WECC) system demonstrates that the EMT zone determined by the proposed approach can effectively capture power system dynamics involving IBRs.
EMT simulation↗
Numerical Propulsion System Simulation (NPSS) Power Systems Library
This presentation covers the Numerical Propulsion System Simulation (NPSS) Power Systems Library being developed by NASA. This library is a set of components, models, and interfaces for the NPSS language to enable building electric power system models for electrified propulsion systems. The presentation is to be given at the 3rd annual RVLT Toolchain Workshop, where attendees from across the eVTOL industry will be informed of NASA’s tools for eVTOL conceptual design from the vehicle level down through subsystems including propulsion, noise, electrical power, and others. It covers where the NPSS Power System Library fits into NASA’s RVLT toolchain and RVLT work in general, and will inform the audience of how the tool can be useful in their own work.
Electric vertical takeoff and landing↗
Parallel-in-Time Power System Simulation Using a Differential Transformation Based Adaptive Parareal Method
Not Available
42 ENGINEERING↗
Examination of Semi-Analytical Solution Methods in the Coarse Operator of Parareal Algorithm for Power System Simulation
With continuing advances in high-performance parallel computing platforms, parallel algorithms have become powerful tools for development of faster than real-time power system dynamic simulations. In particular, it has been demonstrated in recent years that parallel-in-time (Parareal) algorithms have the potential to achieve such an ambitious goal. Here, the selection of a fast and reasonably accurate coarse operator of the Parareal algorithm is crucial for its effective utilization and performance. This paper examines semi-analytical solution (SAS) methods as the coarse operators of the Parareal algorithm and explores performance of the SAS methods to the standard numerical time integration methods. Two promising time-power series-based SAS methods were considered; Adomian decomposition method and Homotopy analysis method with a windowing approach for improving the convergence. Numerical performance case studies on 10-generator 39-bus system and 327-generator 2383-bus system were performed for these coarse operators over different disturbances, evaluating the number of Parareal iterations, computational time, and stability of convergence. All the coarse operators tested with different scenarios have converged to the same corresponding true solution (if they are convergent) and the SAS methods provide comparable computational speed, while having more stable convergence to the true solution in many cases.
97 MATHEMATICS AND COMPUTING↗
Hubble Space Telescope electrical power system simulation breadboard
The components and operation of the Hubble Space Telescope (HST) electrical power system (EPS) breadboard are described. The HST EPS breadboard consists of: (1) the power distribution breadboard, (2) the batteries, (3) the solar array simulators, (4) the load banks, (5) the charge current control hardware, and (6) a control computer; the functions of each of these elements are discussed. The HST EPS has been used to simulate changes in charge level, charge control schemes, and beta angle, failed cells, batteries, solar panel assemblies (SPAs), beginning of life SPAs, and end of life SPAs, and temperature differences. The test data reveal that the HST EPS is capable of operating over a wide range of conditions.
Bush, John R., Jr.↗
Dynamic solar cell power system simulator
Simulation of solar array characteristics to evaluate systems designed to operate from solar cell power source by utilization of silicon diodes
DIODE↗
Applying Quantum Computing to Simulate Power System Dynamics
Power system dynamics are generally modeled by high dimensional nonlinear differential-algebraic equations due to a large number of generators, loads, and transmission lines. Thus, its computational complexity grows exponentially with the system size. This paper demonstrates the potential use of quantum computing algorithms to model the power system dynamics. Leveraging a symbolic programming framework, we equivalently convert the power system dynamics’ differential algebraic equations (DAEs) into ordinary differential equations (ODEs), where the data of the state vector can be encoded into quantum computers via amplitude encoding. The system's nonlinearity is captured by Taylor polynomial expansion, the quantum state tensor, and Hamiltonian simulation, whereas state variables can be updated by a quantum linear equation solver. Our results show that quantum computing can simulate the dynamics of the power system with high accuracy, whereas its complexity is polynomial in the logarithm of the system dimension. Our work also illustrates the use of scientific machine learning tools for implementing scientific computing concepts, e.g., Taylor expansion, DAEs/ODEs transform, and quantum computing solver, in the field of power engineering.
Tran, Huynh↗
Electric-Power System Simulator
Shows different combinations of generation, storage, and load components: display, video monitor with keyboard input to microprocessor, and video monitor for display of load curves and power generation. Planning tool for electric utilities, regulatory agencies, and laymen in understanding basics of electric-power systems operation.
Caldwell, R. W.↗
Open-Source PSCAD Grid-Following and Grid-Forming Inverters and a Benchmark for Zero-Inertia Power System Simulations: Preprint
This paper presents open-source, flexible, and easily-scalable models of grid following and grid forming inverters for the PSCAD software platform. The models are intended for system integration studies, particularly stability analyses of power systems with high penetration of inverter-based generation. To verify the model functionality, they are implemented in a IEEE9-bus system in a zero-inertia operational scenario of 100% inverter-based generation. The models have been made available open source at the PyPSCAD NREL GitHub page.
41 EE - Solar Energy Technologies Office (EE-4S)↗
CNN-Based Phase Fault Classification in Real and Simulated Power Systems Data
This study proposes a convolutional neural network (CNN)–based two-step phase fault detection and identification method to classify anomalies in the power grid signal. Specifically, the first step checks the fault’s existence and determines the need for the second step. Subsequently, in the case of anomalies in the power grid signal, the second step identifies the type of fault, including line-to-line, single-line-to-ground, double-line-to-ground, and triple-line. Accordingly, the CNN architecture is both designed for the classification layers and trained with simulated data. To provide maximum prediction accuracy with minimum processing time, this study investigates the combinations of various feature extraction (FE) techniques, such as fast Fourier transform (FFT), amplitude and phase (AP), auto-correlation function, power spectral density, and wavelet transform (WT). Consequently, simulated and real-world results demonstrate that the proposed two-step method outperforms conventional one-step techniques, with the best performance obtained by using the combination of AP-AP, AP-WT, FFT-AP, and FFT-WT–based FE methods.
Alaca, Ozgur↗
Testing of an Integrated Reactor Core Simulator and Power Conversion System with Simulated Reactivity Feedback
A Direct Drive Gas-Cooled (DDG) reactor core simulator has been coupled to a Brayton Power Conversion Unit (BPCU) for integrated system testing at NASA Glenn Research Center (GRC) in Cleveland, Ohio. This is a closed-cycle system that incorporates an electrically heated reactor core module, turboalternator, recuperator, and gas cooler. Nuclear fuel elements in the gas-cooled reactor design are replaced with electric resistance heaters to simulate the heat from nuclear fuel in the corresponding fast spectrum nuclear reactor. The thermodynamic transient behavior of the integrated system was the focus of this test series. In order to better mimic the integrated response of the nuclear-fueled system, a simulated reactivity feedback control loop was implemented. Core power was controlled by a point kinetics model in which the reactivity feedback was based on core temperature measurements; the neutron generation time and the temperature feedback coefficient are provided as model inputs. These dynamic system response tests demonstrate the overall capability of a non-nuclear test facility in assessing system integration issues and characterizing integrated system response times and response characteristics.
Bragg-Sitton, Shannon M.↗
Testing of an Integrated Reactor Core Simulator and Power Conversion System with Simulated Reactivity Feedback
A Direct Drive Gas-Cooled (DDG) reactor core simulator has been coupled to a Brayton Power Conversion Unit (BPCU) for integrated system testing at NASA Glenn Research Center (GRC) in Cleveland, OH. This is a closed-cycle system that incorporates an electrically heated reactor core module, turbo alternator, recuperator, and gas cooler. Nuclear fuel elements in the gas-cooled reactor design are replaced with electric resistance heaters to simulate the heat from nuclear fuel in the corresponding fast spectrum nuclear reactor. The thermodynamic transient behavior of the integrated system was the focus of this test series. In order to better mimic the integrated response of the nuclear-fueled system, a simulated reactivity feedback control loop was implemented. Core power was controlled by a point kinetics model in which the reactivity feedback was based on core temperature measurements; the neutron generation time and the temperature feedback coefficient are provided as model inputs. These dynamic system response tests demonstrate the overall capability of a non-nuclear test facility in assessing system integration issues and characterizing integrated system response times and response characteristics.
Bragg-Sitton, Shannon M.↗
Efficient and Robust Dynamic Simulation of Power Systems With Holomorphic Embedding
Dynamic simulation is vitally important in power system analysis, but traditional approaches based on numerical integration over small time steps are time-consuming. Also, the Newton-Raphson method suffers from difficulty in convergence when solving nonlinear algebraic equations. In this paper, we propose a novel dynamic simulation approach based on holomorphic embedding. By obtaining a high-order approximation of system dynamics, it achieves a much larger time step and thus enhances the computational efficiency significantly. In addition, the new approach avoids non-convergence issues in solving algebraic equations, which improves robustness. The approach includes flexible modeling of synchronous generators and controllers, and we propose a method for modeling generator coordinate transformations. The approach is tested on the IEEE 39-bus, 10-generator system and a Polish 2383-bus, 327-generator system. The results demonstrate promising computational efficiency and satisfactory numerical robustness for the analysis of large-scale power systems.
42 ENGINEERING↗
Performance and Feature Improvements in Parareal-based Power System Dynamic Simulation
In recent years, a novel Parareal-based approach has been developed for fast transient simulations of large power system interconnections. Parareal belongs to the class of Parallel-in-time algorithms for solution of systems of differential-algebraic equations in parallel over an interval of time. The selection of a reasonably fast and accurate coarse solution is crucial to improve the performance of Parareal algorithm. Semi-analytical solution methods are one promising approach to achieve this goal. They have been investigated, and some preliminary results are presented here. In addition, Parareal-based simulator has been expanded to enable co-simulation with OpenDSS, a widely used open-source distribution system simulator. Preserving the parallel nature of the Parareal approach and taking advantage of the parallel capabilities of the latest versions of OpenDSS, each distribution system can be solved in their entirety on different processors in parallel within the main Parareal simulator. This paper also presents the structure of the transmission and distribution co-simulation and some results with different dynamic models of inverter-based resources in the distribution systems.
Park, Byungkwon↗
Common Electric Power Transmission System Model JSON Schema Specification
The Common Electric Power Transmission System Model (CTM) is an intuitive, extensible, language-agnostic, and error-resistant specification of electric power network components parameter names and units, and relation between components, intended for use by the research community developing new computational methods for power systems operations and simulation. Power system datasets following the CTM specification can be read as dictionaries and manipulated in that form in most programming languages (e.g., Python, Julia, C++). This standard data structure in CTM makes it easy to work in multiple power systems domains (e.g., economic operation, reliability assessment, electricity markets, stability assessment, etc.) without requiring conversions between use-case-specific file formats with information loss in the process. This repository specifies CTM as a JSON Schema, provides documentation, derivate (code-generated) implementations of CTM, and example data and usage of the schema for important use cases.
Aravena Solis, Ignacio↗
Acceleration of Power System Dynamic Simulations Using a Deep Equilibrium Layer and Neural ODE Surrogate
The dominant paradigm for power system dynamic simulation is to build system-level simulations by combining physics-based models of individual components. The sheer size of the system along with the rapid integration of inverter-based resources exacerbates the computational burden of running time domain simulations. Here, in this paper, we propose a data-driven surrogate model based on implicit machine learningspecifically deep equilibrium layers and neural ordinary differential equationsto learn a reduced order model of a portion of the full underlying system. The data-driven surrogate achieves similar accuracy and reduction in simulation time compared to a physics-based surrogate, without the constraint of requiring detailed knowledge of the underlying dynamic models. This work also establishes key requirements needed to integrate the surrogate into existing simulation workflows; the proposed surrogate is initialized to a steady state operating point that matches the power flow solution by design.
Neural ordinary differential equations↗