SEARCH · Engineering Papers

Results for “power transformers”

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.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 775 records · Page 43

All sources NASA NTRS DOE OSTI

DOE OSTI2024

System and method for power converter interfacing with multiple series-stacked voltage domains

According to various embodiments, a power conversion circuit is disclosed. The power conversion circuit includes at least one DC bus. The power conversion circuit further includes a plurality of DC-AC conversion units coupled to the DC bus and configured to convert a DC voltage into an AC voltage. The power conversion circuit also includes a multi-winding transformer comprising a magnetic core and a plurality of windings, where each DC-AC conversion unit is coupled to a corresponding winding of the multi-winding transformer.

Chen, Minjie↗

DOE OSTI2025

Comparing Control Performance Between Simulation and Experiment using the Microreactor Automated Control System Testbed

In the advanced reactor domain, a flexible and scalable software/hardware infrastructure is crucial for integrating and validating various control technologies. This study used the Microreactor Automated Control System (MACS) hardware platform as a testbed. MACS was originally designed to mirror Idaho National Laboratory (INL)'s Microreactor Applications Research Validation and Evaluation (MARVEL), a 85-kW thermal fission microreactor. It features control drums for simulated reactivity control; lights that function as a surrogate reactor core, with the brightness being proportional to the reactor power; and light sensors that emulate neutron detectors. To transform MACS into a physical twin of MARVEL for evaluating control methods, the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND) software was employed. This software integrated the hardware with two models of the MARVEL core, based on Reactor Excursion and Leak Analysis Program (RELAP5-3D) and Monte Carlo N-Particle (MCNP) models. The study aimed to demonstrate the gap between control theory and actual practice—a gap that often necessitates empirical adjustments such as control gain retuning, filters, time discretization, and integrator anti-windup measures. Controllers were developed based on increasingly complex simulations without hardware, starting from the base MARVEL model and then introducing actuator saturation constraints and sensor noise. The final control strategy was then tested using MACS, and a comparative performance analysis was conducted.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

DOE OSTI2021

System and method for implementing a zero-sequence current filter for a three-phase power system

In a three-phase, four-wire electrical distribution system, a zig-zag transformer and at least one Cascade Multilevel Modular Inverter (CMMI) is coupled between the distribution system and the neutral. A controller modulates the states of the H-bridges in the CMMI to build an AC waveform. The voltage is chosen by the controller in order to control an equivalent impedance that draws an appropriate neutral current through the transformer. This neutral current is generally chosen to cancel the neutral current sensed in the line. The chosen neutral current may be based on a remotely sensed imbalance, rather than on a local value, determined by the power utility as a critical load point in the system. The desired injection current is then translated by the controller into a desired zero-sequence reactive impedance, based on measurement of the local terminal voltage, allowing the controller to regulate the current without generating or consuming real power.

Benavides, Nicholas↗

DOE OSTI2024

ARPA-E Grid Optimization (GO) Competition Challenge 3

Synthetic Input Data and Team Results for the GO Competition Challenge 3 for Events 1 - 4 and the Sandbox, along with problem and format descriptions and code to validate data and solutions, are available here. Data for industry scenarios will not be made public. The Grid Optimization (GO) Competition Challenge 3 focused on the security-constrained optimal power flow (SCOPF) problem. It is part of a continuing effort begun with Challenges 1 and 2, to successfully discover, develop, and test innovative and disruptive software solutions for critical energy challenges and to overcome existing barriers. The broader goal of the of the GO Competition is to accelerate the development of transformational and disruptive methods for solving problems related to the electric power grid and to provide a transparent, fair, and comprehensive evaluation of new solution methods. Challenge 3 used multiperiod dynamic markets, including advisory models for extreme weather events, day-ahead markets, and the real-time markets with an extended look-ahead. In Event 4, whose submission window was August 31-September 4, 2023, 14 teams solved for the objective values of 669 scenarios (39 scenarios required solutions both with and without line switching being allowed). The 591 synthetic scenarios from 9 network models (3.6 GB) are available here. Ten teams were funded to participate and 7 won prizes totaling $2,400,000. The largest prize ($550,000) went to Mississippi State University. An additional $600,000 was awarded in Event 3 (6/15-16/2023). No prizes were awarded in Events 1 (1/25-27/2023) or 2 (4/13-14/2023). For more information on the competition and challenge see the "GO Competition Challenge 3 Information" resource below.

ACOPF↗

DOE OSTI2022

The Power of a Network

The Solar Energy Innovation Network (SEIN) helps communities discover transformative ways of adopting solar energy. Teams develop their ideas in real-world contexts, yielding results that can unlock tomorrow's solar markets.

analysis↗

NASA NTRS1990

Light weight, high power, high voltage dc/dc converter technologies

Power-conditioning weight reductions by orders of magnitude will be required to enable the megawatt-power-level space systems envisioned by the Strategic Defense Initiative, the Air Force, and NASA. An interagency program has been initiated to develop an 0.1-kg/kW dc/dc converter technology base for these future space applications. Three contractors are in the first phase of a competitive program to develop a megawatt dc/dc converter. Researchers at NASA Lewis Research Center are investigating innovative converter topology control. Three different converter subsystems based on square wave, resonant, and super-resonant topologies are being designed. The components required for the converter designs cover a wide array of technologies. Two different switches, one semiconductor and the other gas, are under development. Issues related to thermal management and material reliability for inductors, transformers, and capacitors are being investigated in order to maximize power density. A brief description of each of the concepts proposed to meet the goals of this program is presented.

Kraus, Robert↗

DOE OSTI2021

New Modulation and Impact of Transformer Leakage Inductance on Current-Source Solid-State Transformer

This article presents a novel modulation scheme for device voltage stress mitigation and comprehensive analysis of the impact of transformer leakage inductance in a current-source solid-state transformer (SST). Different from dual active bridge (DAB) SST, the operation of the current-source SST is similar to that of a flyback converter. The device bridge on only one side of the transformer is active to store energy into or release energy from the magnetizing inductance which acts as a current-source dc link. Such flyback operation with reverse-blocking switches can lead to additional device voltage stress and incomplete zero-voltage switching (ZVS) on the current-source soft-switching solid-state transformer (S4T) under conventional modulation. A new modulation scheme is proposed to address this issue. Moreover, different from the DAB, the leakage inductance of the medium-frequency transformer (MFT) in the S4T is a parasitic element similar to that in a matrix SST and can cause additional device voltage stress. Though the resonant capacitors, originally added to achieve ZVS, can absorb and recycle the leakage energy in the S4T, these capacitors need to be increased with larger leakage inductances to limit the voltage stress. However, large resonant capacitors can result in more lost duty cycles and reduced efficiency. The impact of such leakage inductance on device voltage stress is analyzed comprehensively, which is critical to guide future research and design of the S4T. Experimental results from S4T prototypes for DC-DC, multiport AC-DC, and AC-AC conversion with 1:1 and 4:1 MFT comprehensively verify the proposed concepts. Lastly, a case study of a three-phase AC-AC S4T over a power range from 1 kVA to 100 kVA each module reveals that the MFT leakage inductance should be less than 1% of the magnetizing inductance for safe operation.

14 SOLAR ENERGY↗

DOE OSTI2024

IoT-Enabled Traveling Wave Microgrid Protection

Traveling Wave Protection based on the Internet of Things (TWP-IoT) is developed to enable ultra-resilient microgrids. TWP-IoT adopts a directional traveling wave approach that utilizes the voltage and current modal components obtained from Discrete Hilbert Transform to identify the fault features via ultra-lightweight IoT hardware. Furthermore, the main contributions of this work include (1) a novel TWP-IoT for microgrid and distribution networks that can achieve the time-of-arrival fault detection and localization with composite wave impedance and conductance using Discrete Hilbert Transform, (2) a cost-effective smart IoT prototype with functionalities outperforming commercial relays, and (3) a real-time hardware-in-the-loop prototype based on RTDS that verifies the robustness and efficacy of TWP-IoT subject to a diverse set of working conditions. TWP-IoT is found to have excellent performance under a wide spectrum of internal and external fault conditions across a myriad of microgrid locations, which is unattainable by today’s TWP products.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS1979

Loudness of steady sounds - A new theory

A new mathematical theory for calculating the loudness of steady sounds from power summation and frequency interaction, based on psychoacoustic and physiological information, assuems that loudness is a subjective measure of the electrical energy transmitted along the auditory nerve to the central nervous system. The auditory system consists of the mechanical part modeled by a bandpass filter with a transfer function dependent on the sound pressure, and the electrical part where the signal is transformed into a half-wave reproduction represented by the electrical power in impulsive discharges transmitted along neurons comprising the auditory nerve. In the electrical part the neurons are distributed among artificial parallel channels with frequency bandwidths equal to 'critical bandwidths for loudness', within which loudness is constant for constant sound pressure. The total energy transmitted to the central nervous system is the sum of the energy transmitted in all channels, and the loudness is proportional to the square root of the total filtered sound energy distributed over all channels. The theory explains many psychoacoustic phenomena such as audible beats resulting from closely spaced tones, interaction of sound stimuli which affect the same neurons affecting loudness, and of individually subliminal sounds becoming audible if they lie within the same critical band.

Howes, W. L.↗

NASA NTRSDate not supplied

Update on SUSAN Concept Vehicle Power and Propulsion System

This paper provides an update on the power and propulsion (P&P) system design for the SUbsonic Single Aft eNgine (SUSAN) Electrofan. The SUSAN vehicle concept is a transformative concept hybrid electric aircraft with a single tail-mounted turbofan engine that provides thrust and power to 16 electric propulsors located on the wings. This configuration makes uses of large-scale power extraction along with a high-power electrical system transmitting 20 MW of power from the engine to the wing propulsors. This paper goes into detail on P&P advances relating turbine engine design, electrical system capabilities, advanced turbine control techniques, and electrical system cooling techniques. It should be noted that the SUSAN concept continues to be developed and this paper simply offers an update on the design.

aircraft concept↗

NASA NTRSDate not supplied

Update on SUSAN Concept Vehicle Power and Propulsion System

aircraft concept↗

NASA NTRSDate not supplied

Update on SUSAN Concept Vehicle Power and Propulsion System

aircraft concept↗

DOE OSTI2024

Study of eVTOL Charging Impact on Airport Electrical Grids

Growth in commercial air traffic has increased the aviation industry's contribution to global emissions. Aircraft electrification can reduce greenhouse gas emissions along with being efficient and reliable. Advanced air mobility introduces the idea of an advanced and more efficient air transportation system. Electric and hybrid aircraft designs, such as electric vertical takeoff and landing (eVTOL), are being considered for a number of applications, such as urban air mobility, cargo delivery, and medical emergencies. Although the electrification of aircraft provides environmental benefits, their charging needs will place significant demand on the electrical grid. This work presents a grid impact study and infrastructure upgrade requirements analysis of eVTOL charging on a realistic distribution grid through power flow simulation analysis. The case study results show that the eVTOL charging can lead to power quality issues, such as undervoltage and equipment capacity overloading. Grid infrastructure, such as lines and transformers, would need to be upgraded, and voltage management strategies would need to be deployed to accommodate eVTOL charging at an existing airport.

advanced air mobility (AAM)↗

DOE OSTI2026

Integrating AI Data Centers with the Power Grid

The rapid expansion of artificial intelligence (AI) has triggered an unprecedented surge in electricity demand, with US data center energy use projected to double or triple 2023 levels by 2028. This exponential growth places strain on grid infrastructure, which can hinder timely construction of desired computing capacity. To bridge this supply-demand gap, utilities and AI developers are increasingly turning to demand flexibility, a strategy that incentivizes shifting or reducing power use during peak periods of grid stress. Data centers are uniquely equipped for flexible operations due to their digital workloads, built-in redundancy, and onsite energy assets. This article outlines four primary mechanisms to enable data center flexibility: computational load flexibility (shifting tasks temporally or geographically), flexible use of core facility infrastructure adjustments, energy storage utilization, and onsite electricity generation. To encourage adoption, utilities are deploying new tariff designs, including voluntary interruptible service riders, mandated flexibility requirements, and streamlined interconnection processes for flexible loads. For the highly capitalized and rapidly growing AI industry, the primary motivators for embracing these strategies are expediting facility interconnection, satisfying emerging regulatory mandates, and mitigating community resistance. While demand flexibility cannot substitute the long-term need for new bulk power generation, it serves as an essential, immediate solution for enabling near-term deployment. By transforming data centers from grid stressors into stabilizing assets, flexible operations can ensure reliable grid integration, ease market pressures, and support a resilient power system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

A Machine Learning-Based Method to Estimate Transformer Primary-Side Voltages with Limited Customer-Side AMI Measurements

Distribution control applications such as volt/var optimization, network reconfiguration, and distribution automation require accurate knowledge of the distribution system state. The lack of sufficient sensors on the primary side of distribution networks often limits the accuracy of the control decisions by these applications. The deployment of advanced metering infrastructure (AMI) provides utilities an opportunity to translate the AMI data on the secondary onto the primary so that it can be used as pseudo-measurements to augment the limited existing measurements on the primary. This paper develops a machine learning based approach for estimating service transformer primary-side voltages by using limited secondary-side AMI measurement. The machine learning model is developed by using random forest algorithm. The estimated primary-side voltages can be used by utilities as pseudo-measurements for distribution control applications. The detailed secondary model topology, which is an essential input data for many existing algorithms, is not required for the proposed method. The performance of the proposed method is validated by using AMI measurements from the field and an actual distribution feeder model of San Diego Gas & Electric Company.

advanced metering infrastructure↗

DOE OSTI2022

A Threat Model of High-Power Electric Vehicle Charging Infrastructure

While electric vehicle powertrains have inherent efficiencies over their conventional counterparts, recharge time remains a significant concern. High power charging (HPC) alleviates the concerns by delivering greater power to speed charging. HPC requires communication among the vehicle, charging infrastructure, and electric supply to facilitate charging. Consequently, the transformation extends the reach and heightens the risks posed by cyberattacks, as an incident may threaten both the power grid and transportation systems. In this paper, a novel consequence-centric methodology is used to formulate an HPC infrastructure threat model. By linking threats to electricity and transportation impacts, a broad understanding of consequences is acquired.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

Modeling the AC Power Flow Equations with Optimally Compact Neural Networks: Application to Unit Commitment

Nonlinear power flow constraints render a variety of power system optimization problems computationally intractable. Emerging research shows, however, that the nonlinear AC power flow equations can be successfully modeled using neural networks. These neural networks can be exactly transformed into mixed integer linear programs and embedded inside challenging optimization problems, thus replacing nonlinearities that are intractable for many applications with tractable piecewise linear approximations. Such approaches, though, suffer from an explosion of the number of binary variables needed to represent the neural network. Accordingly, this paper develops a technique for training an "optimally compact'' neural network, i.e., one that can represent the power flow equations with a sufficiently high degree of accuracy while still maintaining a tractable number of binary variables. We demonstrate the use of this neural network as an approximator of the nonlinear power flow equations by embedding it in the AC unit commitment problem, transforming the problem from a mixed integer nonlinear program into a more manageable mixed integer linear program. We use the 14-, 57-, and 89-bus networks as test cases and compare the AC-feasibility of commitment decisions resulting from the neural network, DC, and linearized power flow approximations. Our results show that the neural network model outperforms both the DC and linearized power flow approximations when embedded in the unit commitment problem. The neural network formulation most often selects a feasible unit commitment schedule, and furthermore, it only s

AC power flow↗

NASA NTRS2012

Getting a Cohesive Answer from a Common Start: Scalable Multidisciplinary Analysis through Transformation of a System Model

One of the challenges of systems engineering is in working multidisciplinary problems in a cohesive manner. When planning analysis of these problems, system engineers must tradeoff time and cost for analysis quality and quantity. The quality is associated with the fidelity of the multidisciplinary models and the quantity is associated with the design space that can be analyzed. The tradeoff is due to the resource intensive process of creating a cohesive multidisciplinary system model and analysis. Furthermore, reuse or extension of the models used in one stage of a product life cycle for another is a major challenge. Recent developments have enabled a much less resource-intensive and more rigorous approach than handwritten translation scripts or codes of multidisciplinary models and their analyses. The key is to work from a core system model defined in a MOF-based language such as SysML and in leveraging the emerging tool ecosystem, such as Query-View- Transform (QVT), from the OMG community. SysML was designed to model multidisciplinary systems and analyses. The QVT standard was designed to transform SysML models. The Europa Hability Mission (EHM) team has begun to exploit these capabilities. In one case, a Matlab/Simulink model is generated on the fly from a system description for power analysis written in SysML. In a more general case, a symbolic mathematical framework (supported by Wolfram Mathematica) is coordinated by data objects transformed from the system model, enabling extremely flexible and powerful tradespace exploration and analytical investigations of expected system performance.

Cole, Bjorn↗