Modelling procedures for interactions between thermal and electrical device parameters.
Flowgraph models describing relationships between thermal and electrical parameters of devices and associated circuits
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Flowgraph models describing relationships between thermal and electrical parameters of devices and associated circuits
Phasors representing positive sequence voltages and currents in a power network are in the most important parameters in several monitoring, control, and protection functions in interconnected electric power networks. Recent advances in computer relaying have led to very efficient and accurate phasor measurement systems. When the phasors to be measured are separated by hundreds of miles, it becomes necessary to synchronize the measurement processes, so that a consistent description of the state of the power system can be established. Global Positioning System (GPS) transmissions offer an ideal source for synchronization of phasor measurements. The concept and implementation of this technique are described. Several uses of synchronized phasor measurements are also described. Among these are improved state estimation algorithms, state estimator enhancements, dynamic state estimates, improved control techniques, and improved protection concepts.
Electrical design of large lightweight solar array for electric propulsion type Mars-bound spacecraft, discussing magnetic effects and power losses
Megaampere-scale electrical wire experiments (EWEs) provide a platform for studying magnetohydrodynamic (MHD) instability growth in magneto-inertial fusion (MIF) devices. Even when nonlinear simulations of these experiments can digitally reproduce much of the experimentally observed instability growth, interpreting the results and understanding mode growth and evolution can be non-trivial. As a first step toward providing better interpretation of these simulation features, this work investigates the use of a deep neural network that uses Koopman operator theory to analyze the dynamics of pulsed-power-driven explosions of EWEs. This deep neural network is trained on 1-D resistive MHD simulations of EWEs. This neural network learns to transform the nonlinear data into a lower-dimensional representation where the time dynamics are linear. Layers of this neural network are shown to learn features of the simulations, including the locations of shock waves and different physical regimes of the simulation. Using the learned features, the network can compress a time state of the simulation consisting of 5120 data point into a 36-parameter lower-dimensional latent space embedding. Furthermore, these embeddings are shown to be clustered in the latent space by initial radius and time state.
Organic molecule-doped n-type single-walled carbon nanotube (SWCNT) networks are promising candidates for advanced energy applications, such as flexible thermoelectrics and photovoltaics. Yet charge transport in n-type SWCNTs is limited by two factors: i) charge localization impeding inter-tube transport caused by disordered mesostructure of randomly oriented SWCNTs and ii) reduction of charge carrier concentration driven by oxidation. Herein, studied the relationship between the mesostructure and thermoelectric properties of n-type SWCNTs obtained by surfactant-functionalization and polymer-dopant grafting. Surprisingly, the electrical conductivity of the polymer-doped SWCNTs keeps increasing with increasing polymer content, even after the saturation of carrier concentration, resulting in 12x higher conductivity on polymer-doping compared to surfactant-functionalization. While hopping transport typically dominates in disordered systems, it is shown that a bridging effect from the polymer causes unusual band-like conduction in polymer-doped SWCNTs. Additionally, since surfactants are essential to prevent oxidation and retain n-type over a long duration, shows that SWCNTs obtained through a dual-functionalization strategy using both polymer-dopant and surfactant, demonstrates a long-term stable high n-type thermoelectric power factor, when the surfactant amount is carefully controlled. Besides thermoelectrics, the findings are of general interest to developing stable and conductive n-type SWCNTs for various energy and electronic applications.
The parameters of electric machine thermal equivalent circuit networks are difficult to predict due to material and manufacturing uncertainties. In this paper, a Greybox system identification approach is used to identify parameters of electric machine stator lumped parameter thermal networks (LPTNs). LPTNs provide a low order, computationally efficient, dynamic model of temperatures at specific locations. Second and third order LPTN model structures are defined as state space equations with stator thermal parameters to be identified. To test the Greybox electric machine stator thermal system identification, five stator motorette prototypes were constructed with controlled variations in slot fill and slot liner thickness. The variation in the motorette thermal parameters and thermal time constants are detected using the Greybox identification. Special attention is given to the impact of sampling rate and Greybox data record length on parameter estimation accuracy.
Porous-floating-gate, "vertical" field-effect transistor proposed as programmable analog memory device especially suitable for use in electronic neural networks. Analog value of electrical conductance of device represents synaptic weight (strength of synaptic connection) repeatedly modified by application of suitable writing or erasing voltage. Suited for hardware implementations of massively parallel neural-network architectures for two important reasons: vertical transistor structure requires only two external electrodes, and use of tailored amorphous semiconductors provides choice of very wide range of low conductivity values, dictated by overall power dissipation requirements in massively parallel neural-network circuits.
A major phase of the Federal Wind Energy Program, the Mod-2 wind turbine, a second-generation machine developed by the Boeing Engineering and Construction Co. for the U.S. Department of Energy and the Lewis Research Center of the National Aeronautics and Space Administration, is described. The Mod-2 is a large (2.5-MW power rating) horizontal-axis wind turbine designed for the generation of electrical power on utility networks. Three machines were built and are located in a cluster at Goodnoe Hills, Washington. All technical aspects of the project are described: design approach, significant innovation features, the mechanical system, the electrical power system, the control system, and the safety system.
The 2021 Infrastructure Investment and Jobs Act, also known as the Bipartisan Infrastructure Law (BIL), invests $\$$7.5 billion to build out a national electric vehicle (EV) charging network and created the Joint Office of Energy and Transportation (Joint Office) to “study, plan, coordinate, and implement issues of joint concern between the two agencies.” The BIL represents a historic effort to electrify the U.S. transportation system, which has significant potential to reduce U.S. greenhouse gas emissions and help tackle the climate crisis. The U.S. transportation sector accounts for one-third of the nation’s greenhouse gas emissions—the largest share of all primary sectors, including electricity production, industry, commercial and residential, and agriculture. The National Electric Vehicle Infrastructure (NEVI) Formula Program, one of the BIL funding programs, was launched in February 2022, providing nearly $\$$5 billion over 5 years to help states, the District of Columbia, and Puerto Rico (hereafter referred to as “states”) create a network of EV charging stations beginning with designated Federal Highway Administration (FHWA) Alternative Fuel Corridors (AFCs), with an emphasis on the Interstate Highway System. The funding is made available to the states in allocations each year pending FHWA certification of the state’s annual deployment plan. The NEVI program is in its third year, so there's a lot to celebrate. As of July 2024, 39 states have released solicitations for their NEVI programs and eight states have opened their first NEVI-funded stations (61 ports in total), which have already powered thousands of charging sessions for EV drivers across America. Additional stations are in the pipeline with more than 2,500 additional ports having been awarded or conditionally awarded by the states. All states released their Fiscal Year (FY) 2024 deployment plan updates to reflect the new minimum requirements and guidance, and several states added newly designated EV AFCs in their FY 2024 deployment plan updates, bringing the total AFC network of EV corridors to more than 81,000 miles.
This paper presents the results of a study into the feasibility of using satellite communications for a country-wide system of electric distribution system monitoring and control. The concept selected for study involves the use of a geostationary satellite with a large multi-beam antenna to provide a major part of the communications and control network between participating utilities and various elements of their power distribution networks, including customer loads. Electric utility communications requirements are projected through 1995 in order to size the required capacity of the system. Two basic systems are examined: a one-way system for load control, and a two-way system for distribution system monitoring and control, including customer meter reading. An operating protocol is proposed for each system. Preliminary cost estimates are identified element by element. Finally, expansion of the basic system to include a set of ancillary communications functions is briefly discussed.
With the rapid advancement and acceleration in the electric vehicle (EV) industry within the United States, major automakers and EV charging companies are increasingly adopting the North American Charging Standard (NACS) connector style, now officially known as J3400. This shift is expected to enhance charging infrastructure, providing a better customer experience by making it easier for all EV drivers to access a wider network of direct-current (DC) fast chargers (DCFCs). However, the adoption of the J3400 standard presents challenges for many EVs already on the roads and some currently coming off production lines that are equipped with the Combined Charging System (CCS) connector, which this report will refer to as the North American standard, CCS1. These vehicles will need adapters to use new or existing J3400 infrastructure. During this transition, several issues have emerged. Firstly, there is a need to standardize the new connector type to ensure it is interoperable, safe, and reliable. Second, existing CCS EV drivers need a way to access the J3400 network, which will require electric vehicle supply equipment (EVSE) or sites with both connector types, driver-provided adapters to physically convert from CCS to J3400, or EVSE with retained adapters designed for use with the EVSE. Third, adapter standards will need to be written to specify how they will be designed and what evaluations will be needed to ensure safe and reliable performance. To address these challenges, adapters that support different types of charging connectors will be essential. These adapters will play a crucial role in supporting the transition and ensuring continued service for legacy EVs with CCS inlets as the J3400 standard becomes the predominant one in the United States. Consequently, the National Charging Experience (ChargeX) Consortium has investigated and performed a teardown analysis on the different adapter versions on the market. The aim is to create a failure mode and effects analysis (FMEA) on what are expected to be the most common adapter types used in this transition. In order to support this work, we executed an FMEA exercise with the main goal of identifying gaps in the existing adapters' performance and conformance to the most common safety requirements of high-power and high-voltage devices. This effort focused on adapters provided by the driver, as these may present the highest safety and reliability risks. The recommendations made here apply to both retained and driver-provided adapters.
The paper presents a survey on the development and experience with artificial neural net (ANN) applications for electric power systems, with emphasis on operational systems. The organization and constraints of electric utilities are reviewed, motivations for investigating ANN are identified, and a current assessment is given from the experience of 2400 projects using ANN for load forecasting, alarm processing, fault detection, component fault diagnosis, static and dynamic security analysis, system planning, and operation planning.
This volume (2 of 4) contains the specification, structured flow charts, and code listing for the protocol. The purpose of an autonomous power system on a spacecraft is to relieve humans from having to continuously monitor and control the generation, storage, and distribution of power in the craft. This implies that algorithms will have been developed to monitor and control the power system. The power system will contain computers on which the algorithms run. There should be one control computer system that makes the high level decisions and sends commands to and receive data from the other distributed computers. This will require a communications network and an efficient protocol by which the computers will communicate. One of the major requirements on the protocol is that it be real time because of the need to control the power elements.
A computer algorithm for deriving accurate values of lightning-caused changes in cloud electric fields under active storm conditions was developed and applied to data obtained during two thunderstorms from a network of ground-based electric field mills at the NASA Kennedy Space Center and the Cape Canaveral Air Force Station. The resulting field changes were analyzed using a least-squares optimization procedure and point-charge (Q) and point-dipole (P) models. The values and the time variations of the Q-model parameters under active storm conditions were found to be similar to those reported by Maier and Krider (1986) for small storms, when the computations were carried out with the same analysis criteria and comparable biases. The parameters of the P solutions were found to vary with time within the storm interval and from storm to storm.
Carbon nanotubes (CNTs) are shown to promise great opportunities in nanoelectronic devices and nanoelectromechanical systems (NEMS) because of their inherent nanoscale sizes, intrinsic electric conductivities, and seamless hexagonal network architectures. I present our collaborative work with Stanford on exploring CNTs for nanodevices in this talk. The electrical property measurements suggest that metallic tubes are quantum wires. Furthermore, two and three terminal CNT junctions have been observed experimentally. We have proposed and studied CNT-based molecular switches and logic devices for future digital electronics. We also have studied CNTs based NEMS inclusing gears, cantilevers, and scanning probe microscopy tips. We investigate both chemistry and physics based aspects of the CNT NEMS. Our results suggest that CNT have ideal stiffness, vibrational frequencies, Q-factors, geometry-dependent electric conductivities, and the highest chemical and mechanical stabilities for the NEMS. The use of CNT SPM tips for nanolithography is presented for demonstration of the advantages of the CNT NEMS.
Security is one of the most if not the most important areas today. After the several attacks on the United States, security everywhere has heightened from airports to communication among the military branches legionnaires. With advanced persistent threats (APTs) on the rise following Stuxnet, government branches and agencies are required, more than ever, to follow several standards, policies and procedures to reduce the likelihood of a breach. Attack vectors today are very advanced and are going to continue to get more and more advanced as security controls advance. This creates a need for networks and systems to be in an updated, patched and secured state in a launch control system environment. Attacks on critical systems are becoming more and more relevant and frequent. Nation states are hacking into critical networks that might control electrical power grids or water dams as well as carrying out advanced persistent threat (APTs) attacks on government entities. NASA, as an organization, must protect its self from attacks from all different types of attackers with different motives. Although the International Space Station was created, there is still competition between the different space programs. With that in mind, NASA might get attacked and breached for various reasons such as espionage or sabotage. My project will provide a way for NASA to complete an in house penetration test which includes: asset discovery, vulnerability scans, exploit vulnerabilities and also provide forensic information to harden systems. Completing penetration testing is a part of the compliance requirements of the Federal Information Security Act (FISMA) and NASA NPR 2810.1 and related NASA Handbooks. This project is to demonstrate how in house penetration testing can be conducted that will satisfy all of the compliance requirements of the National Institute of Standards and Technology (NIST), as outlined in FISMA. By the end of this project, I hope to have carried out the tasks stated above as well as gain an immense knowledge about compliance, security tools, networks and network devices, as well as policies and procedures.
Timely removal of ice and snow from roads is critical to safe, fast, and uninterrupted transportation networks in cold regions. Constructing electrically conductive asphalt pavements to melt the ice and snow on the roads through resistive eating is an emerging alternative technology to traditional snow/ice removal approaches such as utilizing snowplow machines and deicing chemicals. Carbon-based fibers and fillers including carbon fiber and graphite have been widely reported to make electrically conductive hot mix asphalt mixtures for pavement snow/ice-melting applications. This study aimed to develop and demonstrate a novel type of electrically conductive asphalt pavements for snow/ice-melting, which utilizes electrically conductive cold mix asphalt (CMA) mixtures incorporating coal-derived carbon-based coke aggregate as resistive heating elements. Both laboratory experiments and field tests were conducted to investigate the electrical, mechanical, and thermal properties of such electrically conductive asphalt mixtures and pavements. The laboratory experiment results indicated that the electrically conductive CMA mixtures incorporating coke aggregate had sufficiently high electrical conductivity and satisfactory mechanical performance and the pavement prototype slab utilizing a thin layer of such CMA mixtures could successfully raise the pavement surface temperatures to 8.3–11.7 °C rom a low temperature of –5 °C with an input power density of 473 W/m 2 . The field test results showed that the full-scale coal-derived electrically conductive asphalt pavements were able to increase the pavement surface temperatures when electricity was applied, but the magnitude of temperature increase was highly dependent on the power density. Furthermore, it is promising to use coke aggregate to construct coal-derived electrically conductive asphalt pavements for snow/ice melting.
The behind-the-meter (BTM) thermal and battery energy storage can help improve energy efficiency, reduce energy costs, and enhance energy resilience, particularly in rural areas and for disadvantaged communities. Aggregating numerous BTM energy storage systems can act as a price influencer with a significant source of load shifting and peak demand reduction. An integrated and scalable control mechanism is required to effectively utilize energy storage systems and flexible building loads to maximize the economic benefits, considering various distribution system constraints. Here, this paper presents an innovative hierarchical coordination framework for energy storage and flexible load in buildings, considering various factors such as electricity prices, thermal comfort, and distribution system modeling and constraints. At the upper level, a distribution system operator optimizes the power flow to minimize its power procurement costs from the electricity wholesale market, while at the lower level, aggregators determine the optimal dispatch of battery and thermal energy storage systems in multiple buildings on behalf of end-users to minimize operating costs according to the power prices. These problems are solved using a game-theoretic approach through negotiations between the distribution system operator and aggregators as a bi-level decision model. Simulation case studies have been performed for a test distribution network with a number of building end-users using energy storage systems to quantify the performance of aggregators. The results demonstrate that the proposed strategy can reduce peak load for a reliable electricity distribution network while saving electricity bills for customers.