Engineering topics

Wilson, Aaron

Publications and source records attributed to Wilson, Aaron.

11 records

DOE OSTI2024

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↗

DOE OSTI2023

On the Investigation of Phase Fault Classification in Power Grid Signals: A Case Study for Support Vector Machines, Decision Tree and Random Forest

In monitoring the power grid, an ability to differentiate between fault types is essential to ensuring electrical safety. Accordingly, this study introduces a fault detection and classification method by considering different machine learning (ML) and feature extraction (FE) methods combinations. Specifically, the proposed method is established in two classification layers; the first layer determines the fault, and the second layer distinguishes the type of fault. Based on the proposed system model, this study seeks to determine the influential data attributes in a power grid signal using FE methods, including fast Fourier transform, power spectral density (PSD), auto-correlation, and wavelet transform (WT). A cross-comparison of the effectiveness of the Support Vector Machine (SVM), Decision Tree (DT), and Random Forest (RF) is also performed to accomplish the classification layers of the proposed method. The designed algorithm is analyzed under the various combinations of FE and ML methods, and outcomes are presented by considering the trade-off between computational complexity and prediction accuracy. The results reveal that the RF-based ML algorithm shows the most accurate classification performance with PSD, and the most time-saving of the models is the DT WT. Also, SVM emerges superior on a subsequent test of the simulated models on real-world signals.

Galbraith, Kelli↗

DOE OSTI2023

Detection of Grid-Signal Distortions Using the Spectral Correlation Function

This study proposes a novel method for signal detection and feature extraction based on the spectral correlation function, enabling improved characterization of grid-signal distortions. Our approach differs from existing treatments of signal distortion in its analysis of the varied spectral content of signals observed in real-world scenarios. The method we propose has state-of-the-art discriminative power that provides meaningful and understandable characterizations of various grid events and anomalies. In conclusion, to validate the approach, we use real world data from the Grid Event Signature Library, which is maintained jointly by Oak Ridge National Laboratory and Lawrence Livermore National Laboratory.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2023

Adaptive Envelope Detector-Based Phase Fault Detection Method for Power System Grid Distortions

In this study, a phase fault detection algorithm is developed by employing the envelope detector method. The proposed method diagnoses faults among phases and defines fault areas in the incoming signal. The designed algorithm consists of three steps: analytical signal conversion, complex magnitude, and fault detection. Initially, an analytical signal is obtained from the incoming power signal to determine the instantaneous amplitude and phase of the signal. A complex magnitude operation is applied to analytical signals to display changes in amplitude. On the basis of the threshold values specified by the user, the last step identifies the distortion signal in terms of the type of error and size. The proposed method is tested with realistically simulated substation power signal data and real power system data from the Grid Event Signature Library. The obtained results revealed that the proposed method detects distortions accurately.

Alaca, Ozgur↗

DOE OSTI2022

A Simple and Accurate Energy-Detector-Based Transient Waveform Detection for Smart Grids: Real-World Field Data Performance

Integration of distributed energy sources, advanced meshed operation, sensors, automation, and communication networks all contribute to autonomous operations and decision-making processes utilized in the grid. Therefore, smart grid systems require sophisticated supporting structures. Furthermore, rapid detection and identification of disturbances and transients are a necessary first step towards situationally aware smart grid systems. This way, high-level monitoring is achieved and the entire system kept operational. Even though smart grid systems are unavoidably sophisticated, low-complexity algorithms need to be developed for real-time sensing on the edge and online applications to alert stakeholders in the event of an anomaly. In this study, the simplest form of anomaly detection mechanism in the absence of any a priori knowledge, namely, the energy detector (also known as radiometer in the field of wireless communications and signal processing), is investigated as a triggering mechanism, which may include automated alerts and notifications for grid anomalies. In contrast to the mainstream literature, it does not rely on transform domain tools; therefore, utmost design and implementation simplicity are attained. Performance results of the proposed energy detector algorithm are validated by real power system data obtained from the DOE/EPRI National Database of power system events and the Grid Signature Library.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Comparison of Power System Current Sensors via Playback of Electrical Disturbances

The need to accurately measure high-frequency content in power system voltage and current phenomena is increasingly becoming more of a priority. As the amount of distributed energy resources (DER) and nonlinear loads penetrating the grid increases, so do challenges associated with traditional measurement and metering applications. In this paper, three commercially-available medium-voltage-level current sensors are characterized in terms of their harmonic amplitude and phase performance against reference signals that are “played back” through the sensors through the use of an arbitrary waveform generator. It is shown that none of the three sensors studied are able to faithfully replicate all of the input signals completely, though there are advantages and disadvantages to each in terms of noise, resonance, and induced phase drift. Additionally, the Goodness-of-Fit metric, typically used for PMU model validation, is used to generate side-by-side comparisons of sensor accuracy over a small window around the events under study.

Wilson, Aaron↗

DOE OSTI2021

Frequency and Temporal Analysis of Cicada Brood X Sounds

Cicadas are insects that belong to the order Hemiptera (i.e., true bugs). They feed on plant fluids above and below ground. Cicada species fall into two categories: periodical and annual. Seven species of periodical cicadas have been identified, emerging in 13-, 17-, and 21-year cycles [1]. The largest brood (i.e., periodical cicadas of the same cycle) of 17-year cicadas is Brood X, examples of which are shown in Fig. 1. Male cicadas produce the loudest sounds of the insect world. A single male can produce a clicking sound that exceeds 100 dB sound pressure level. This male cicada sound emanates from an organ called the tympanic membrane, which is located on both sides of the body near the base of the wing [2]. The vibrations from this organ generate the sound. Female cicadas make a similar— although less loud—clicking sound with their wings. Figure 2 shows the locations of active cicadas within the United States.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

Measurements from an Electrical Distribution System Substation During Hurricane Zeta

Hurricane Zeta made landfall on the United States mainland on October 29, 2020. The hurricane’s impacts on electrical service within the storm path included millions of customers losing power. The eye of the hurricane crossed over Chattanooga, Tennessee, USA, where advanced sensors were monitoring the operational state of a utility substation. A report on the measurement capability and rudimentary results is presented here.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

Sampling Rate Comparison for Distribution System Voltage Measurements

Measurement of the voltage delivered by an electric distribution is a relatively straight forward task. When determining the harmonic distortion in the voltage, matters associated with what orders of the 50/60 Hz harmonics to be analyzed dictate the sampling rate. A study addressing this matter is presented.

42 ENGINEERING↗

DOE OSTI2020

Distributed Ledger Technology Preliminary Performance Assessment for Applications in Utilities Operational Technology

This paper provides descriptions of the key components of different distributed ledger technology platforms. Distributed ledger technology (DLT) allows for distribution of databases among different organizations and devices. The platforms use cryptographically linked “blocks” to store and verify transactional information between these organizations. DLT increases data security, data integrity, trust among its participants. Different organizations are looking to deploy this distributed and decentralized approach to avoid the single-point-of-failure vulnerabilities associated with centralized data repositories. In this study we examine twelve different DLT platforms. There is agreement within the community that of all the platforms considered here, Hyperledger and Ethereum are the most mature when it comes to privacy and permissions. These DLT platforms are being used for applications such as transactive energy, health care, and the food and goods supply chain. However, further development is required to realize the full promise of DLT. Our assessment includes a general description of each DLT and its key characteristics. Such characteristics include consensus protocol and cryptography used, public vs. private, and permissioned or permissionless. The selection and implementation of a DLT architecture depends heavily on the use case and performance requirements. During this research we found key parameters to measure performance and existing tools for assessment. Four different parameters were identified 1) consensus, 2) throughput, 3) latency, and 4) scalability. The architectures of Hyperledger Caliper and Blockbench are described as different performance assessment frameworks. From this preliminary study it is evident that there are dissimilarities on the performance assessments methods developers and users are characterizing DLT architectures. The purpose of this paper is to identify key parameters to test performance, tools that are being used and provide information on results from previous studies.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2009

A Summary of the Development of a Nominal Land Landing Airbag Impact Attenuation System for the Orion Crew Module

Airborne Systems North America (formally Irvin Aerospace Inc) has developed an Airbag Landing System for the Orion Crew Module of the Crew Exploration Vehicle. This work is in support of the NASA Langley Research Center Landing System Advanced Development Project. Orion is part of the Constellation Program to send human explorers back to the moon, and then onwards to Mars and other destinations in the Solar System. A component of the Vision for Space Exploration, Orion is being developed to also enable access to space following the retirement of the Space Shuttle in the next decade. This paper documents the development of a conceptual design, fabrication of prototype assemblies, component level testing and two generations of airbag landing system testing. The airbag system has been designed and analyzed using the transient dynamic finite element code LS-DYNA(RegisteredTradeMark). The landing system consists of six airbag assemblies; each assembly comprising a primary impact venting airbag and a non-venting anti-bottoming airbag. The anti-bottoming airbag provides ground clearance following the initial impact attenuation sequence. Incorporated into each primary impact airbag is an active vent that allows the entrapped gas to exit the control volume. The size of the vent is tailored to control the flow-rate of the exiting gas. An internal shaping structure is utilized to control the shape of the primary or main airbags prior to ground impact; this significantly improves stroke efficiency and performance.

Tutt, Ben↗