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ML-Based Power System Stability Assessment Considering Network Topology Changes: WECC 20,000+ Bus System Case Study
Modern power grids are fast-changing and thus require real-time monitoring and online stability assessment. With the rapid development of machine learning (ML) techniques, using data-driven models to provide fast and accurate estimations of power system stability marginal information, such as frequency nadir for frequency stability and critical clearing time (CCT) for transient stability, have become possible. However, despite the numerous research on ML-based methods for frequency nadir and CCT prediction, there is limited work on the impact of different network topology changes. Furthermore, most previous studies only focused on small or synthetic systems, and there is a lack of research on actual large power system models. In this paper, the above issues are addressed by studying the actual U.S. Western Electricity Coordinating Council (WECC) system model with more than 20,000 buses. Massive simulations are conducted in PowerWorld Simulator to study the impact of various topology change scenarios on both frequency stability and transient stability. System operating information is extracted from the success dispatch cases of various network topologies to generate a comprehensive dataset for ML-based models. Two ML methods, random forest (RF) and multilayer perceptron (MLP) neural network, are trained and tested for both frequency nadir prediction and CCT prediction. Test results have proven the models are capable of online stability assessment for large power networks such as the WECC system with sufficient accuracy.
Open dynamic simulation dataset of the Texas 2000-bus synthetic power system on ANDES [SWR-25-110]
An open-source power system model (Texas2k), running on an open-source dynamic simulator (ANDES), designed to lower barriers for machine-learning studies of power systems.
DC Bus Collection of Type-4 Wind Turbine Farms with Phasing Control to Minimize Energy Storage.
Abstract not provided.
Characterization of throughput on the AXI DMA bus for burst data transfer over Ethernet
cThe Xilinx AXI Direct Memory Access (AXI DMA) module is an efficient solution for medium-speed data transfer in Xilinx SoC FPGAs, supporting data rates greater than 1000 Gbps even in very suboptimal operating modes. It facilitates direct transfer of AXI stream data into processor memory without constant software intervention, which reduces overhead and ensures consistent data logging. By utilizing the FPGA's available memory, large circular buffers (1-5 GiB) are used to buffer data and accommodate network limitations, enabling high-rate data bursts. In this study, we measured the performance of AXI DMA under conditions simulating its lowest practical data transfer speeds. The Arbitrary Length Data Sender was used to transmit AXI stream packets at 32-bit width and 100 MHz frequency, a narrow width and slow speed. Results show that the AXI DMA can transfer up to 3192.76 Mbps with large packet sizes but experiences reduced performance for smaller packets, as low as 2.6 Mbps for 4-byte packets. For Ethernet-limited applications, packet sizes between 8,000 and 16,000 bytes provided optimal transfer speeds of 874 to 1600 Mbps. These findings suggest that the AXI DMA is not the limiting factor in systems where packet sizes exceed 8,000 bytes.
Multimodal Learning in Cyber-Physical System: A Deep Dive with WSCC 9-Bus System
Explore the source record for details and available documents.
A Review of Regulations, Codes, and Standards for Hydrogen Fuel Cell Electric Bus Use on Airports
This report reviews regulations, codes, and standards to be considered for FCEB operations on airports governing vehicle safety, hydrogen infrastructure, and airport operations. Overall, the review found the existing regulatory framework largely suitable for FCEB operations on airports, with only minor gaps identified pertaining to heavy-duty vehicle fueling, operation and fire safety on airport aprons, and authorization for emergency power use.
Thermal Analysis of the Bus Bars for the 800MeV Injection Era
❑ Introduction ❑COMSOL thermal simulations for present conditions - Results - Validation ❑COMSOL thermal simulations for PIP-II conditions ❑Proposed changes - New busbars section - Results ❑Peak temperature tables ❑Conclusions
Feasibility and Qualitative Risk Assessment of Fuel Cell Electric Bus Use for Emergency Backup Power for Airport Applications
Airports rely on robust backup power systems to maintain critical operations during emergencies. This paper investigates the feasibility of using hydrogen fuel cell electric buses (FCEBs) as emergency backup power sources, focusing on their technical specifications, operational challenges, and associated risks. Using Portland International Airport as a case study, the analysis evaluates the power output and hydrogen consumption of New Flyer’s 40’ Xcelsior Charge fuel cell buses, to provide power for key airport systems. Additionally, the paper explores the design and layout of how FCEBs can be connected to airport facilities, and addresses safety considerations, hydrogen supply logistics, and electrical compatibility. While FCEBs present significant advantages in terms of sustainability and resilience, their implementation requires careful planning, infrastructure investment, and adherence to safety standards. This research provides actionable insights for airport stakeholders seeking to transition to hydrogen-based backup power system.
Edge ML for CAN bus intrusion detection in AVs
Autonomous Vehicles (AVs) are revolutionizing transportation, but their reliance on interconnected cyber-physical systems exposes them to unprecedented cybersecurity risks. This study addresses the critical challenge of detecting real-time cyber intrusions in self-driving vehicles by leveraging a dataset from the Udacity self-driving car project. We simulate four high-impact attack vectors, Denial of Service (DoS), spoofing, replay, and fuzzy attacks, by injecting noise into spatial features (e.g., bounding box coordinates) to replicate adversarial scenarios. We develop and evaluate two lightweight neural network architectures (NN-1 and NN-2) alongside a logistic regression baseline (LG-1) for intrusion detection. The models achieve exceptional performance, with NN-2 attaining an AUC score of 93.15% and 93.15% accuracy, demonstrating their suitability for edge deployment in AV environments. Through explainable AI techniques, we uncover unique forensic fingerprints of each attack type, such as spatial corruption in fuzzy attacks and temporal anomalies in replay attacks, offering actionable insights for feature engineering and proactive defense. Visual analytics, including confusion matrices, ROC curves, and feature importance plots, validate the models' robustness and interpretability. This research sets a new benchmark for AV cybersecurity, delivering a scalable, field-ready toolkit for Original Equipment Manufacturers (OEMs) and policymakers. By aligning intrusion fingerprints with SAE J3061 automotive security standards, we provide a pathway for integrating machine learning into safety-critical AV systems. Our findings underscore the urgent need for security-by-design AI, ensuring that AVs not only drive autonomously but also defend autonomously. This work bridges the gap between theoretical cybersecurity and life-preserving engineering, offering a leap toward safer, more secure autonomous transportation.
Design of a main-bus switching regulator with low RF interference for the radio astronomy Explorer satellite.
Variable ratio DC transformer regulator used in voltage boost configuration of power system in Radio Astronomy Explorer /RAE/ spacecraft, noting RF interference reduction
Bus voltage compensation circuit for controlling direct current motor
Automatic control of voltage supply to direct current motor
A buck-boost main bus voltage regulator for a solar array battery space power system
Design and operational analysis of buck-boost voltage regulator for solar array battery in space power system
Synchronous executive and bus control software for redundant data management systems
Development and characteristics of executive software for application to space shuttle data management system
Digital transmitter for data bus communications system
Digital transmitter designed for Manchester coded signals (and all signals with ac waveforms) generated at a rate of one megabit per second includes efficient output isolation circuit. Transmitter consists of logic control section, amplifier, and output isolation section. Output isolation circuit provides dynamic impedance at terminals as function of amplifier output level.
Study for identification of Beneficial Uses of Space (BUS) (phase 2). Volume 1: Executive summary
A study was conducted to analyze the benefits to the world which can be realized from space manufacturing processes. The study envisaged the use of the space shuttle and manned space stations for the purpose. For each proposed operation a data base and rationale were established for those processes or portions of processes which would be improved by performance in the orbital environment. The four experiments which were recommended for the initial investigation are identified. The procedures for conducting the weightless manufacturing processes are outline.
Study for identification of Beneficial Uses of Space (BUS). Volume 2: Technical report. Book 1: Sections 1 through 4
Consolidated information is presented for the study whose purpose was to identify products, processes, and services to be produced in future spacecraft environments for direct utilization on earth. Discussion of methodology for selecting from among potential space processing approaches, definition of requirements for experiments and tests needed to acquire sufficient knowledge for proof testing of selected processes, formulation of research and development schedules to achieve proof testing, and documentation of the decision processes involved in the programs are presented. Technology and programmatics are reported for the following select studies: (1) surface acoustic wave components; (2) transparent oxides; (3) high purity tungsten X-ray targets; and (4) high specificity isoenzymes.