Pressure Transient Analysis to Determine Anisotropic Fault Leakage Characteristics
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Engineering↗
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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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Space Nuclear Power Autonomous Control Algorithm and Control Element Test Bed
Nuclear thermal rockets are currently NASA’s preferred option for use in a manned mission to Mars in the 2040s. The communication delay between an Earth ground station and a spacecraft heading toward Mars can be up to 20 min. Therefore, controlling the nuclear rocket engine would require either a full-time reactor operator on the mission or an autonomous control system for the reactor. The latter idea of making space nuclear reactors fully autonomous has drawn more interest from stakeholders, but such an autonomous control system must be rigorously tested and validated before it is certified for human use. The cost of a full ground test for a space nuclear reactor is tremendous, so a nonnuclear mock reactor test bed was created to test and validate control elements and control algorithms for space nuclear reactors. The test bed consists of control element hardware that inputs physical measurement data into a reactor emulator to produce the reactor’s performance under steady-state, transient, and fault conditions. The control element hardware consists of six full-sized control drums equipped with servo drives and motors and is instrumented with optical encoders, resolvers, and torque sensors for drum movement characterization. In addition to the drums, a two-phase flow loop was designed and built to mimic the valves and turbomachinery associated with the propellant flow through a nuclear thermal rocket engine; components such as pressure sensors, flow meters, thermocouples, and tachometers are instrumented throughout the loop to characterize the fluid flow, valve, and turbomachinery behavior of the system. The data from the physical hardware (e.g., drum position, propellant flow rates) are input to a nuclear reactor simulator to determine the actual nuclear reactor parameters, and the data are sent back to a control algorithm to complete the control loop. The ability to conduct numerous tests of the control systems and autonomous algorithms can help validate the instrumentation and control aspects for a space nuclear reactor for every possible fault situation.
Wilson, Brandon↗
Gearbox Reliability Collaborative 1.5 (GRC1.5) Project: Joint Industry Megawatt Scale Gearbox Field Tests: Cooperative Research and Development (Final Report) CRADA Number CRD-16-00608
A new DOE/NREL industry collaboration called the Gearbox Reliability Collaborative 1.5 (GRC1.5) will undertake field testing on a commercial multi-megawatt wind turbine gearbox to collect loading data as installed in the turbine to thoroughly characterize gearbox loads and responses during actual in-field conditions. A chief outcome is to provide publicly available operational loading data to the industry. This will provide a greater understanding of steady-state, transient, and fault response for both the input and output of the gearbox; thus, facilitating improvements in the gearbox components, lubrication system, power converter or turbine controller.
17 WIND ENERGY↗
Drivetrain Reliability Collaborative 1.5 (DRC1.5) Project: Joint Industry Megawatt Scale Gearbox Field Tests: Cooperative Research and Development (Final Report) CRADA Number CRD-17-00702
A new Department of Energy (DOE)/NREL industry collaboration called the Drivetrain Reliability Collaborative 1.5 (DRC1.5) will undertake field testing on a commercial multi-megawatt wind turbine drivetrain to collect loading data as installed in the turbine to thoroughly characterize drivetrain loads and responses during actual in-field conditions. A chief outcome is to provide publicly available operational loading data to the industry. This will provide a greater understanding of steady-state, transient, and fault response for both the input and output of the drivetrain; thus, facilitating improvements in the drivetrain components, lubrication system, power converter or turbine controller.
17 WIND ENERGY↗
GRC1.5 Project: Joint Industry Megawatt Scale Gearbox Field Tests (Final Report)
A new DOE/NREL industry collaboration called the Gearbox Reliability Collaborative (GRC) 1.5 will undertake field testing on current commercial multi-megawatt wind turbine gearboxes to collect loading data from installed turbines to thoroughly characterize gearbox input loads and responses during actual in-field conditions. A chief outcome is to provide operational loading data relative to the most common failure modes. This will provide a greater understanding of steady-state, transient, and fault response for both the input and output of the gearbox, thus facilitating improvements in the gearbox, power converter or turbine controller.
17 WIND ENERGY↗
Passive Islanding Detection of Inverter-Based Resources in a Noisy Environment
Islanding occurs when a load is energized solely by local generators and can result in frequency and voltage instability, changes in current, and poor power quality. Poor power quality can interrupt industrial operations, damage sensitive electrical equipment, and induce outages upon the resynchronization of the island with the grid. This study proposes an islanding detection method employing a Duffing oscillator to analyze voltage fluctuations at the point of common coupling (PCC) under a high-noise environment. Unlike existing methods, which overlook the noise effect, this paper mitigates noise impact on islanding detection. Power system noise in PCC measurements arises from switching transients, harmonics, grounding issues, voltage sags and swells, electromagnetic interference, and power quality issues that affect islanding detection. Transient events like lightning-induced traveling waves to the PCC can also introduce noise levels exceeding the voltage amplitude by more than seven times, thus disturbing conventional detection techniques. The noise interferes with measurements and increases the nondetection zone (NDZ), causing failed or delayed islanding detection. The Duffing oscillator nonlinear dynamics enable detection capabilities at a high noise level. The proposed method is designed to detect the PCC voltage fluctuations based on the IEEE standard 1547 through the Duffing oscillator. For the voltages beyond the threshold, the Duffing oscillator phase trajectory changes from periodic to chaotic mode and sends an islanded operation command to the inverter. The proposed islanding detection method distinguishes switching transients and faults from an islanded operation. Experimental validation of the method is conducted using a 3.6 kW PV setup.
Energy & Fuels↗
A Current Limiting Control Strategy for Single-Loop Droop-Controlled Grid-Forming Inverters Under Balanced and Unbalanced Faults
Existing studies reporting current limiting control strategies for grid-forming inverters primarily focus on grid-forming inverters that use a multi-loop control structure. This study reports a current limiting control for grid-forming inverters that uses a single-loop control structure. The proposed current limiting control was implemented at the pulse width modulation (PWM) control layer to guarantee a rapid response. Once an overcurrent caused by severe faults is detected, the proposed control strategy immediately blocks relevant insulated-gate bipolar transistors (IGBTs) using a hysteresis loop, ensuring that the overcurrent is limited within a few PWM cycles. After the fault is cleared, the inverter seamlessly transfers back to droop control mode to maintain stability. The current limiting control has been tested in a microgrid environment operating in the OPAL-RT platform. Study results show that the control strategy can effectively limit the overcurrent under both balanced and unbalanced faults and can maintain system transient stability after the fault is cleared.
Du, Wei↗
Transient evolution of permeability and friction in a slowly slipping fault activated by fluid pressurization
The mechanisms of permeability and friction evolution in a natural fault are investigated in situ. During three fluid injection experiments at different places in a fault zone, we measured simultaneously the fluid pressure, fault displacements and seismic activity. Changes in fault permeability and friction are then estimated concurrently. Results show that fault permeability increases up to 1.58 order of magnitude as a result of reducing effective normal stress and cumulative dilatant slip, and 19-to-60.8% of the enhancement occurs without seismic emissions. When modeling the fault displacement, we found that a rate-and-state friction and a permeability dependent on both slip and slip velocity together reasonably fit the fault-parallel and fault-normal displacements. This leads to the conclusion that the transient evolution of fault permeability and friction caused by a pressure perturbation exerts a potentially dominant control on fault stability during fluid flow.
58 GEOSCIENCES↗
Bridging Power System Protection Gaps with Data-driven Approaches
Protection is a critical function in power systems to avoid equipment damage, maintain personnel safety, and support system reliability. However, current protective relay technology cannot adequately protect equipment and personnel from effects of some events; these deficiencies are termed protection gaps. In this research, a data-driven approach is proposed to complement traditional protection technology and distinguish fault conditions from transients caused by normal operations. A convolutional neural network (CNN) based fault detection approach is implemented to achieve data translation invariance of the time-series input data. As a result, the data-driven method can accurately detect system faults despite variation and noise in the input data. In addition, using the CNN–based method avoids the complicated manual feature extraction procedure required by many traditional data-driven methods. The effectiveness of the proposed approach is tested on four kinds of protection gaps: high impedance faults, transformer/generator inter-turn faults, distribution system PV circuit faults, and the mis-operation situations of Zone 3 line protection relays operating under system stress. Finally, a transfer learning method is also proposed to address the common issue of data-driven methods for which real-world training data are scarce. Extensive study results demonstrate that the proposed approach can accurately bridge power system protection gaps.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Reduced-Order Parameterized Short-Circuit Current Model of Inverter-Interfaced Distributed Generators
The short-circuit response of inverter-interfaced distributed generators (IIDGs) is not adequately represented in many conventional protection studies. This paper presents an in-depth analysis of IIDG behavior during grid faults and proposes a more accurate reduced-order parameterized short-circuit current (RPSC) model of inverters. Typical inverter components are thoroughly investigated to identify those that play dominant roles during faults. The paper shows that the current limiter is the dominant factor for the steady-state fault-current of inverter; while the inverter filter along with the severity of the voltage disturbance largely determine the initial transient spike of inverter fault current. The proposed model is low-order and can be used in large scale simulations. The parameters of the proposed RPSC model can be extracted from laboratory experiments without requiring proprietary manufacturer information. The proposed fault-current model is analogous to the well-known synchronous machine model that segregates the inverter fault current into subtransient, transient, and steady-state fault currents. Finally, experimental and simulation tests are presented to validate the model.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Positive-Sequence Phasor Modeling of Droop-Controlled, Grid-Forming Inverters with Fault Current Limiting Function
Traditional positive-sequence phasor models of droop-controlled, grid-forming inverters do not have the fault current limiting function. During a short-circuit fault the model generates unrealistic high fault current making the simulation results less practical. This paper develops a fault current limiting function for the positive-sequence phasor model of droop-controlled, grid-forming inverters, which can effectively limit the inverter output current at the predefined maximum during faults. A user-written model has been developed for the commercially-available software Siemens/PTI PSS/E. Fault studies on a modified IEEE 39-bus system with all grid-forming inverters verify the effectiveness of the developed fault current limiting function. The proposed model can be used to evaluate how the limited fault currents of droop-controlled, grid-forming inverters impact the bulk power system transient stability under fault conditions.
Du, Wei↗
Using Electromagnetic Transient Program (EMTP) for accurate prediction of faults location.
Abstract not provided.
Carr, Christopher↗
Fault-tolerant grid frequency measurement algorithm during transients
A system determines the frequency of grid signals corresponding to an electrical grid in real time. The system includes a transient detector that monitors a grid signal from a voltage meter or a current meter connected to the electrical grid. The system produces, in real time and at a sampling rate, a deviation signal indicative of a periodicity of the monitored grid signal. The system determines, over one or more cycles of the monitored grid signal, a measurement signal corresponding to the deviation signal. The system determines a frequency signal that corresponds a frequency estimation of the monitored signal by applying a frequency estimation when values of the measurement signal are less than a deviation threshold and maintaining the frequency signal at a constant value when values of the measured signal equal or exceeds the deviation threshold.
Zhan, Lingwei↗
New data-driven approach to bridging power system protection gaps with deep learning
Protection is a critical function in power systems to avoid equipment damage, maintain personnel safety, and support system reliability. However, current protective relay technology cannot adequately protect equipment and personnel from effects of some events; these deficiencies are termed protection gaps. In this paper, a data-driven approach is proposed to complement traditional protection technology and distinguish fault conditions from transients caused by normal operations. A combined convolutional neural network and long short-term memory (CNN-LSTM) network is implemented to achieve data translation invariance and capture the temporal correlation of the time-series input data. As a result, the data-driven method can accurately detect system faults despite variation and noise in the input data. In addition, using the CNN-LSTM--based method avoids the complicated, manual feature extraction procedure required by many traditional data-driven methods. The effectiveness of the proposed approach is tested on two kinds of protection gaps: high-impedance faults and transformer inter-turn faults. Lastly, a transfer learning method is also proposed to address the common issue of data-driven methods for which real-world training data are scarce. Extensive study results demonstrate that the proposed approach can accurately bridge power system protection gaps.
42 ENGINEERING↗
A Parametric Reduced-Order Model for Inverter Short-Circuit Response in Protection Studies
This paper presents a reduced-order model (ROM) for grid-following (GFL) inverters that reproduces inverter fault current trajectories, including sub transients, transient, and steady-state phases, across a range of fault types, locations, and pre-fault operating points. . The proposed model is developed by: Constructing the positive- and negative-sequence current with parameterization fitted by large data training and fitting Validating using EMT simulation against EMT full model and demonstrating the ROM's capability to capture fault current magnitude, phase angle, and oscillatory transients. Building a standard EMT simulation platform library component for easy configuration and application.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Medium-Voltage Testbed for Comparing Advanced Power Line Sensors vs. Measurement Transformers with Electrical Grid Events
Electrical utilities have relied upon potential transformers (PTs) and current transformers (CTs) for very accurate metering and to provide reliable signals for protective relays. Less expensive alternative sensing technologies offer the possibility of wider deployment, particularly in grids that employ distributed energy resources. In this work, the performance of an advanced medi-um-voltage sensor is compared with a reference PT and CT and experimentally evaluated for different power grid scenarios on an advanced outdoor power line sensor testbed at the US De-partment of Energy’s Oak Ridge National Laboratory. The sensor is based on a capacitive divider for voltage monitoring and a Rogowski coil with integrator for current monitoring. The advanced outdoor power line sensor testbed has a real-time simulator that was used to generate transient scenarios (e.g., electrical faults, capacitor bank operation, service restoration), while the analog signals were recorded by the same high resolution power meter. The behavior of analog signals, harmonic components, total harmonic distortion, and crest factors were assessed for this power line sensor compared with the reference PT/CT, because of the absence for testing standards for advanced outdoor power line sensors.
Piesciorovsky, Emilio↗
Data-Driven Protection Software to classify fault locations by protective zone in distribution systems with high PV penetration
The software contains (a) the source codes to generate Point-on-Wave (PoW) transient data for any feeder model in Alternative Transient Program (ATP) format. Codes provide options to change different steady state settings, including the loading condition and PV capacity and transient state setting like faults type, location and initiation time (b) data post-processing source code to converted data from native format to COMTRADE, csv, HDF5 (c) Docker container to train CNN to classify fault locations by protective zone. The container takes dataset and other training parameters (sampling rate, training epochs, batch size etc) as input to train CNN. The container writes back the trained CNN model, training and testing metrics and plots to the local workstation
Ramesh, Meghana↗
Fault detection in a three-phase dab converter
A system and method of fault detection based on a detailed waveform analysis is presented for transient and steady-state fault operation of 3-Φ DAB converter. Main symptoms of the converter during normal and fault conditions have been identified and a unique pattern in DC bias of phase currents under fault mode is noted. The logic-based fault diagnosis scheme is used to detect the fault and identify the faulty transistor.
Rastogi, Sagar K.↗