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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 163 records · Page 9

Artificial neural network application for space station power system fault diagnosis

This study presents a methodology for fault diagnosis using a Two-Stage Artificial Neural Network Clustering Algorithm. Previously, SPICE models of a 5-bus DC power distribution system with assumed constant output power during contingencies from the DDCU were used to evaluate the ANN's fault diagnosis capabilities. This on-going study uses EMTP models of the components (distribution lines, SPDU, TPDU, loads) and power sources (DDCU) of Space Station Alpha's electrical Power Distribution System as a basis for the ANN fault diagnostic tool. The results from the two studies are contrasted. In the event of a major fault, ground controllers need the ability to identify the type of fault, isolate the fault to the orbital replaceable unit level and provide the necessary information for the power management expert system to optimally determine a degraded-mode load schedule. To accomplish these goals, the electrical power distribution system's architecture can be subdivided into three major classes: DC-DC converter to loads, DC Switching Unit (DCSU) to Main bus Switching Unit (MBSU), and Power Sources to DCSU. Each class which has its own electrical characteristics and operations, requires a unique fault analysis philosophy. This study identifies these philosophies as Riddles 1, 2 and 3 respectively. The results of the on-going study addresses Riddle-1. It is concluded in this study that the combination of the EMTP models of the DDCU, distribution cables and electrical loads yields a more accurate model of the behavior and in addition yielded more accurate fault diagnosis using ANN versus the results obtained with the SPICE models.

Momoh, James A.↗

Architecture for Web-Based Visualization of Large-Scale Energy Domains: Preprint

With the growing penetration of inverter-based distributed energy resources and increased loads through electrification, power systems analyses are becoming more important and more complex. Moreover, these analyses increasingly involve the combination of interconnected energy domains with data that are spatially and temporally increasing in scale by orders of magnitude, surpassing the capabilities of many existing analysis and decision-support systems. We present the architectural design, development, and application of a high-resolution web-based visualization environment capable of cross-domain analysis of tens of millions of energy assets, focusing on scalability and performance. Our system supports the exploration, navigation, and analysis of large data from diverse domains such as electrical transmission and distribution systems, mobility and electric vehicle charging networks, communications networks, cyber assets, and other supporting infrastructure. We evaluate this system across multiple use cases, describing the capabilities and limitations of a web-based approach for high-resolution energy system visualizations.

grid modernization↗

Deep Reinforcement Learning for Distribution System Operations: A Tutorial and Survey

Here, the rapid evolution of modern electric power distribution systems into complex networks of interconnected active devices, distributed generation (DG), and storage poses increasing difficulties for system operators. The large-scale integration of distributed energy resources (DERs) and the rapid exchange of measurement data via communication networks present major opportunities for advancing grid operations but also introduce greater uncertainty, higher data dimensionality, more complex network and device models, and challenging control and optimization problems. Deep reinforcement learning (DRL) algorithms are promising in addressing these challenges. However, they have not been effectively adapted for power systems applications, requiring extensive customization for implementation and evaluation. This has resulted in reproducibility challenges and a steep learning curve for researchers new to applying DRL algorithms to the power systems domain. To bridge these gaps, this tutorial aims to serve as a valuable resource for researchers interested in exploring learning-based algorithms to operate active power distribution networks. Specifically, this work presents a generalized process for translating sequential decision-making problems in power distribution systems into Markov decision process (MDP) formulations, illustrated through concrete grid service examples. Additionally, we introduce a simple environment design strategy to develop and evaluate example DRL algorithms for distribution system applications, complete with an included code repository to guide users through environment construction.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Annoyance to Noise Produced by a Distributed Electric Propulsion High-Lift System

A psychoacoustic test was performed using simulated sounds from a distributed electric propulsion aircraft concept to help understand factors associated with human annoyance. A design space spanning the number of high-lift leading edge propellers and their relative operating speeds, inclusive of time varying effects associated with motor controller error and atmospheric turbulence, was considered. It was found that the mean annoyance response varies in a statistically significant manner with the number of propellers and with the inclusion of time varying effects, but does not differ significantly with the relative RPM between propellers. An annoyance model was developed, inclusive of confidence intervals, using the noise metrics of loudness, roughness, and tonality as predictors.

Rizzi, Stephen A.↗

Simulation of a Lunar Surface Base Power Distribution Network for the Constellation Lunar Surface Systems

The Lunar Surface Power Distribution Network Study team worked to define, breadboard, build and test an electrical power distribution system consistent with NASA's goal of providing electrical power to sustain life and power equipment used to explore the lunar surface. A testbed was set up to simulate the connection of different power sources and loads together to form a mini-grid and gain an understanding of how the power systems would interact. Within the power distribution scheme, each power source contributes to the grid in an independent manner without communication among the power sources and without a master-slave scenario. The grid consisted of four separate power sources and the accompanying power conditioning equipment. Overall system design and testing was performed. The tests were performed to observe the output and interaction of the different power sources as some sources are added and others are removed from the grid connection. The loads on the system were also varied from no load to maximum load to observe the power source interactions.

Mintz, Toby↗

Hawaiian Electric Company (HECO) Grid Optimization with Solar (Cooperative Research and Development Final Report)

The purpose of this project is to provide a software platform that gives utility companies the capability to seamlessly dispatch legacy devices (at both the distribution and subtransmission levels) and distributed energy resources (DERs) to achieve system-wide performance and reliability targets–such as minimizing loss, reducing voltage violation, and corresponding imbalance–for extreme solar futures with well over 100% (capacity) penetrations.

14 SOLAR ENERGY↗

Expert System Detects Power-Distribution Faults

Autonomous Power Expert (APEX) computer program is prototype expert-system program detecting faults in electrical-power-distribution system. Assists human operators in diagnosing faults and deciding what adjustments or repairs needed for immediate recovery from faults or for maintenance to correct initially nonthreatening conditions that could develop into faults. Written in Lisp.

Walters, Jerry L.↗

Final Report: MaRSPlus Sensor System Electrical Cable Management and Distributed Motor Control Computer Interface

The success of JPL's Next Generation Imaging Spectrometer (NGIS) in Earth remote sensing has inspired a follow-on instrument project, the MaRSPlus Sensor System (MSS). One of JPL's responsibilities in the MSS project involves updating the documentation from the previous JPL airborne imagers to provide all the information necessary for an outside customer to operate the instrument independently. As part of this documentation update, I created detailed electrical cabling diagrams to provide JPL technicians with clear and concise build instructions and a database to track the status of cables from order to build to delivery. Simultaneously, a distributed motor control system is being developed for potential use on the proposed 2018 Mars rover mission. This system would significantly reduce the mass necessary for rover motor control, making more mass space available to other important spacecraft systems. The current stage of the project consists of a desktop computer talking to a single "cold box" unit containing the electronics to drive a motor. In order to test the electronics, I developed a graphical user interface (GUI) using MATLAB to allow a user to send simple commands to the cold box and display the responses received in a user-friendly format.

data cubes↗

Load Flow Analysis with Analytic Derivatives for Electric Aircraft Design Optimization

Many of the aircraft concepts of the future are exploring the use of hybrid-, turbo- or all-electric propulsion systems to improve performance and decrease environmental impacts. These aircraft concepts range from small rotorcraft for urban air mobility to conventional commercial transports to large blended wing body designs. Developing the conceptual design for these vehicles presents a challenge, however, as traditional aircraft design tools often were not developed to handle these unique propulsion system architectures. Previous studies on these vehicles have therefore relied on relatively simple models of the electrical transmission and distribution system. This paper presents the development of a hybrid AC-DC load flow (or power flow) analysis capability to enhance the conceptual design of these concept vehicles. Specifically, the desire was to create a load flow analysis capability within the OpenMDAO framework that is also being used to develop a set of compatible tools for rapid optimization of conceptual designs. This load flow analysis capability is unique in its flexible object-oriented structure and implementation of analytic derivatives to facilitate the use of solvers and gradient based optimization in the design process. The developed hybrid load flow analysis capability is first verified against a published 13-bus example then used to model the electrical distribution system for a turbo-electric tiltwing aircraft.

Load flow↗

Design and Development of a 200-kW Turbo-Electric Distributed Propulsion Testbed

The National Aeronautics and Space Administration (NASA) Armstrong Flight Research Center (AFRC) (Edwards, California) is developing a Hybrid-Electric Integrated Systems Testbed (HEIST) Testbed as part of the HEIST Project, to study power management and transition complexities, modular architectures, and flight control laws for turbo-electric distributed propulsion technologies using representative hardware and piloted simulations. Capabilities are being developed to assess the flight readiness of hybrid electric and distributed electric vehicle architectures. Additionally, NASA will leverage experience gained and assets developed from HEIST to assist in flight-test proposal development, flight-test vehicle design, and evaluation of hybrid electric and distributed electric concept vehicles for flight safety. The HEIST test equipment will include three trailers supporting a distributed electric propulsion wing, a battery system and turbogenerator, dynamometers, and supporting power and communication infrastructure, all connected to the AFRC Core simulation. Plans call for 18 high performance electric motors that will be powered by batteries and the turbogenerator, and commanded by a piloted simulation. Flight control algorithms will be developed on the turbo-electric distributed propulsion system.

distributed↗

Coordinated operation of pumped-storage hydropower with power and water distribution systems

Small pumped-storage hydropower (PSH) units have gained popularity as distributed energy storage options that can provide flexibility to the operation of power distribution systems. Optimal operation of small PSH units is not only dependent on the energy storage provided to power distribution system, but also on the inflow and outflow of water from and to the water distribution system. Here, in this context, this paper develops an optimization model for coordinated operation of PSH units with power and water distribution systems. The proposed model optimizes the operation of water tanks, variable-speed pumps and PSH in pumping and generating modes to minimize the operation cost of power distribution system, while respecting the power flow constraints of power distribution and hydraulic constraints of water distribution system. Appropriate electricity tariffs are implemented to avoid additional expenses in water distribution system that can be enforced by its coordinated operation in favor of power distribution system. The proposed model is implemented on a 33-bus and a 123-bus test power distribution system connected to a 16-node test water distribution system. Results demonstrate the effectiveness of proposed model in tapping PSH flexibility to reduce the operation cost of power and water distribution systems, while meeting the power and water demands.

13 HYDRO ENERGY↗

Distribution System Planning for Growth in Residential Electric Vehicle Adoption

Anticipated growth in Electric Vehicles (EV) adoption could stress distribution system circuits beyond their original design limits. Uncertainties related to when households will begin buying EVs in large numbers challenges existing distribution system planning approaches and complicates efforts to assess grid impacts. Anticipated location, timing, and demand for EV charging is critical information for distribution system planners as it guides investment strategies for infrastructure upgrades to ensure continued reliability. This research makes two significant contributions: an EV adoption model that uses socioeconomic data to forecast location and year-specific adoption patterns through a bottoms-up approach, and an EV hosting capacity assessment methodology that offers improvements to current utility planning and asset management practices for infrastructure investments. Both contributions are applied to a Southern California Edison feeder in 7 adoption years from 2025 to 2050, with the results indicating that they are likely valuable additions to distribution systems planning capabilities.

Sridhar, Siddharth↗

An Overview of Issues Related to IEEE Std 1547-2018 Requirements Regarding Voltage and Reactive Power Control

The revised Institute of Electrical and Electronics Engineers (IEEE) 1547 Standard for Interconnection and Interoperability of Distributed Energy Resources with Associated Electric Power Systems Interfaces (IEEE Std 1547-2018) was published in April 2018. This standard is one of the foundational documents in the United States needed for integrating distributed energy resources (DERs), including solar energy systems, with the electric distribution grid. The revised standard contains 11 chapters (clauses) and 8 annexes that comprise 136 pages. The revision is significantly different from the 2003 version, and it contains new concepts and new technical requirements. Each clause specifies information or requirements that apply to certain aspects important to the interconnection of DERs to the electric power system. Implementing the requirements necessitates a careful study of the underlying technical concept and requires the appropriate information required to calculate relevant settings and configurations. Various stakeholders have different roles in implementing the standard, and portions of the standard are directed toward a specific audience who must possess specialized information and technical training to use and apply the requirements. This document aims to (1) summarize a specific portion of the standard as concisely as possible and (2) provide the reader with introductory knowledge and information to support the utilization of the requirements.

14 SOLAR ENERGY↗

Computational Analysis of the X-57 Maxwell Airplane, the Landing Configuration with High-Lift Blowing and Aileron Deflections (Preliminary Fuselage)

The X-57 Maxwell is an all-electric airplane with a distributed electric propulsion system used for a high-lift system at takeoff and landing conditions. The Kestrel and USM3D flow solvers were used at NASA Langley to investigate the performance of the X-57 Maxwell in the development of an aerodynamic database. The configuration investigated in this paper had a 30° flap deflection, and in addition the pilot’s right aileron were deflected and undeflected in different cases. The solutions were computed at an airspeed of 58 KEAS, for an altitude of 6000 feet, and a flight Reynolds number of 0.588e+06 per foot. To evaluate the high-lift distributed electric propulsion system without aileron deflections, the solutions were computed for an angle-of-attack sweep from −2° to 20°, with the high-lift propellers blowing and the cruise propellers excluded from the simulation. To investigate the aileron effectiveness, the solutions were computed at angles of attack of −2° and 14°, for aileron deflections from −25° to 18° with the high-lift propellers blowing and the cruise propellers windmilling at idle-power. The high-lift propellers and the idle-power cruise propellers were modeled with an actuator disk. Results show negligible differences in lift, drag and pitching moment whether the idle-powered cruise propellers were included or excluded from the simulation. In general, the Kestrel and USM3D codes compared well for lift, drag and pitching moment for the landing configuration with no aileron control. The Kestrel code, using the Spalart-Allmaras turbulence model with the rotation corrections terms, predicted an increasing lift coefficient up to maximum lift coefficient of 4.65 at a 15° angle of attack. The USM3D code, using the Spalart-Allmaras turbulence model turbulence model with the Quadratic Constitutive Relation predicted an increasing lift coefficient up to maximum lift coefficient of 4.5 at a 12° angle of attack, with the lift remaining constant through a 14◦ angle of attack. A possible difference in lift coefficient between the codes for high angles of attack may result from the different available options used with the standard Spalart-Allmaras turbulence model. The Kestrel code predicted more drag across the range of angle of attack than the USM3D code. The codes compared well for pitching moment coefficient across the range of angle of attack. The Kestrel and USM3D codes compared well for aileron effectiveness at a 2° angle of attack. The Kestrel code predicts better aileron effectiveness than USM3D at a 14° angle of attack. There is more flow separation in the region outboard of the last high-lift nacelle for the USM3D solutions at a 14° angle of attack, which diminishes the ability of the aileron to be effective.

X-57 Maxwell Airplane↗

Detecting Anomalies for Fire Prevention in Distribution Systems: Challenges and Analytical Techniques

Electric utilities in California have historically been linked to up to 10% of wildfires. To mitigate this risk, Southern California Edison has invested significantly in wildfire prevention strategies, including undergrounding cables and enhancing equipment inspections. This article explores a novel approach to fire prevention by detecting anomalies in the distribution system that may indicate potential fire hazards. The focus is on identifying arcing conditions through high-resolution point-on-wave (POW) measurements. Arcing, a precursor to fires, is challenging to detect due to its subtle transients and complex system topology. The article discusses the use of advanced signal processing and machine learning techniques, such as spectral correlation function and discrete wavelet transform, to extract features from POW data and accurately identify arcing events. The study demonstrates a high accuracy rate in detecting arcing, paving the way for improved fire prevention measures in electric distribution systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Reinforcement Learning for Distribution Grid Optimization (PyCIGAR) v0.1

PyCIGAR is a python software package that merges off-the-shelf reinforcement learning libraries (RLLib and Ray) with electric power distribution system simulation tools (OpenDSS and a custom power flow solver built by LBL). PyCIGAR enables the training of neural networks to optimize the behavior of different components in the electric distribution grid, such as control systems in photovoltaic rooftop solar inverters and electric battery storage systems. The software package has been used to train neural networks to update settings in photovoltaic rooftop solar inverter control systems to mitigate cyber attacks on other solar photovoltaic rooftop devices.

Arnold, Daniel↗