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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Comparative Study of Nonlinear Black-Box Modeling for Power Electronics Converters

With the increasing penetration level of renewable sources and power electronics loads in modern power systems, accurate and computationally efficient models are needed. Black-box model (BBM) could be a useful method in such systems. However, not very extensive research efforts have been made for power electronics BBM so far, and existing works mostly focus on steady-state operation, neglecting the important transient behaviors such as load transients, voltage transients, and faults. This paper presents a comparative study of three commonly used nonlinear BBM approaches for transient behaviors of power electronics converters. Comparison methods are proposed, and the evaluations are conducted under different transients using a grid-connected single-phase photovoltaic inverter. The findings of this study provide valuable references for further feasibility investigations on implementing BBMs in large-scale power electronics-rich power systems.

Qiao, Liang↗
DOE OSTI2020

Co-Optimization of Boost Converter Reliability and Volumetric Power Density [Brief]

Optimized designs were achieved using a genetic algorithm to evaluate multi-objective trade space, including Mean-Time-Between-Failure (MTBF) and volumetric power density. This work provides a foundational platform that can be used to optimize additional power converters, such as an inverter for the EV traction drive system as well as trade-offs in thermal management due to the use of different device substrate materials.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2024

A graphical user interface platform to support power electronic converters and integrated systems

Power Electronic Systems have grown in size and complexity over the past years. Therefore, users require interfaces to properly configure, develop, and deploy these systems. This work presents a Graphical User Interface that dynamically adapts to the system and allows the user to control and monitor its operation. This GUI uses networked communication and open-source Python libraries to allow the user to interact with the system at its different hierarchical layers, as well as visualize the interconnection of the full system. This is demonstrated by showing the user interface applied to a megawatt class charging station that consists of various energy resources.

Dean, Ben↗
DOE OSTI2020

Power at Sea: Use of Wave Energy Converters for Powering Offshore Oil and Gas Operations

New innovative services and goods based on artificial intelligence, next-generation robotics, autonomy, digitization, and electrification are taking root in the ocean economy. More typical competitive forces, such as value enhancement and safety improvement, are also present, as suppliers constantly strive to improve their competitive positioning. Concurrently, the Oil and Gas sector is experiencing mounting pressure to decrease its operational carbon emissions, forcing efforts to reduce or eliminate liquid fuel consumption offshore. Companies in the ocean economy are having to react to this combination of macro- and micro-level drivers and innovate at an ever more rapid pace. However, before many of these new capabilities can be implemented, new, clean, reliable power sources are needed, especially as liquid fuel grows increasingly out of favor. For many of these loads—both old and new and ranging from watts to megawatts—wave energy systems provide the best solution for remote power generation. As such, research, development and demonstration activities are underway to prove wave energy's ability to provide reliable, consistent energy supplies for certain offshore Oil and Gas activities, paving the way for near term commercialization. Furthermore, this paper outlines these drivers, competitive reaction to them, and why and how wave energy can be a preferable choice for power at sea.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

Reliability-based hull geometry optimisation of a point-absorber wave energy converter with power take-off structural reliability objectives

Recent studies have focused on optimising wave energy converter (WEC) designs, maximising their power performance and techno-economic feasibility. Reliability has yet to be fully considered in these formulations, despite its impact on cost and performance. In this study, this gap is addressed by developing a reliability-based design optimisation framework for WEC hull geometries to explore the trade-off between power performance and power take-off (PTO) system damage equivalent loading (DEL). Optimised hull geometries for two sites are considered (from the centre of the North Sea and off the west coast of Norway), and two directions of motions (heave and surge). Results indicate that site characteristics affect the potential power production and DEL for an optimal WEC design. These are also affected by the direction of motion for power extraction, which also significantly changes optimal hull shape characteristics. Optimal surging WEC designs have edges facing oncoming wave directions, while heaving WECs have pointed bottoms, both to streamline movement. Larger, more convex WECs result in greater power production and DEL, while smaller, more concave WECs result in lesser power production and DEL. These findings underline the importance of considering WEC hull geometry in early design processes to optimise cost, power production, and reliability.

16 TIDAL AND WAVE POWER↗
DOE OSTI2024

Extreme Efficiency 240 Vac to Load Data Center Power Delivery Topologies and Control

The research explored innovative new circuit topologies and power converter architectures for data center power delivery, from the 240 V ac voltage at the input of a server rack, down to the less than 1 V dc power supply of the latest microprocessors. The research pursued three parallel tracks to increase the power conversion efficiency and to reduce the overall size of the servers: 1) An innovative new ac-dc power converter topology which enables improved efficiency through use of a novel direct step-down topology, well suited for the popular 48V dc power distribution. 2) A new series-stacked power delivery approach for servers comprising a large number of similar loads, such as hard drives in storage servers. The approach greatly reduces the power conversion losses, and achieves efficiency well over 99%. 3) A new family of hybrid switched-capacitor power converters that enable improved efficiency and reduced size through the use of dense ceramic capacitors and new circuit topologies that leverage GaN and low-voltage Si transistor technology. Together, the accomplished research achieved the goal of reducing the power conversion losses in datacenters, thereby reducing greenhouse gas emissions, operating costs, and overall electricity consumption.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Hardware Design and Demonstration of a 100kW, 99% Efficiency Dual Active Half Bridge Converter Based on 1700V SiC Power MOSFET

High efficiency, high density and galvanically isolated power converters are attractive for numerous medium voltage high power applications. This paper presents a 1.5kVdc, 100kW bidirectional Dual Active Half Bridge (DAHB) using newly developed 1.7kV SiC MOSFET modules. The DAHB achieved an efficiency of 98.6% at full load of 100kW and a maximum of 99% at 45kW, operating as an isolated DC/DC converter. The converter also achieved an efficiency of 97.8% operating as an isolated DC/AC inverter. An optimized PCB-based busbar design has significantly reduced the voltage overshoot across the device, making the design suitable for 1500Vdc input application such as 1500V PV inverters. Typical partial discharge inception voltage (PDIV) of the optimized PCB busbar is 1.7kVpeak with total charge <10pC. The power density of the DAHB converter is 1.8MVA/m 3 which is much higher than traditional two-stage industry products. The DAHB converter can be used as a building block for a 4.16kV/1MVA utility scale PV systems with input parallel and output series configuration.

Xu, Wei↗
DOE OSTI2020

Design of 1500V/200kW 99.6% Efficiency Dual Active Bridge Converters Based on 1700V SiC Power MOSFET Module

High efficiency, high density and galvanically isolated power converters are attractive for medium voltage high power applications. This paper presents a 1.5kV/200kW bidirectional Dual Active Bridge (DAB) converter using a newly developed 1.7kV SiC MOSFET module. The intended application is megawatt scale solid state transformer (SST) and 1500V PV inverter application using modular architecture. One novel model to estimate the turn-off loss using snubber capacitors is proposed and experimentally verified. An optimized PCB-based busbar design is introduced to reduce the voltage overshoot across the SiC device, making the design suitable for 1.5kVdc applications. The mechanism of how the optimized PCB-based busbar can reduce the voltage overshoot is quantitatively interpreted and experimentally verified. The DAB converter achieved an efficiency of 98.85% at 200kW and a maximum of 99.53% at 60kW. The maximum efficiency for series-resonant mode is 99.6% at 85kW and 99.3% at 200kW. The power density is 26W/inch3 (1.6MW/m3) which is much higher than traditional industry products.

Xu, Wei↗
DOE OSTI2025

Assessing Dynamic Behaviors in Converter- Dominated Power Systems via RMS and EMT Simulations: A Study of Hawaii’s NELHA Microgrid

The transition from conventional power systems to converter-based microgrids has significantly advanced sustainability, clean energy integration, and operational reliability. However, this paradigm shift introduces operational challenges due to the intermittent nature of renewable energy sources and the non-linear characteristics of power electronic loads, inducing voltage fluctuations and harmonic distortions that complicate voltage and frequency regulation. Accurate dynamic modeling is hypothesized to be critical for capturing such effects, enabling reliable simulation and control strategy development. This study introduces an innovative dynamic modeling framework for a real-world converter-based microgrid, utilizing both root mean square (RMS) and electromagnetic transient (EMT) simulation methods. The microgrid was modeled in DIgSILENT PowerFactory, with simulations calibrated against high-resolution field measurements from SEL-735 power quality meters. Results show that RMS simulations effectively characterize steady-state dynamics, while EMT simulations are essential for capturing high-frequency transients and non-linear effects from photovoltaic inverters and variable frequency drives (VFDs). This complementary approach provides a comprehensive understanding of microgrid behavior, providing critical insights for improving simulation accuracy, advancing protection schemes, and improving resilience in future low-inertia power networks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

LENS: Learning Enabled Network Synthesis

RTRC and UMD have developed novel machine learning based methods under the ARPA-E DIFFERENTIATE program for rapid acceleration of hypothesis generation in complex architecture design spaces involving both discrete choices of component inclusion and interconnection and continuous parametric decisions. The project named Learning Enabled Network Synthesis (LENS) further demonstrated the developed methods on challenging electrical power converter design problems by identifying the most suitable circuit topologies and simultaneously selecting the most appropriate components to achieve optimized design of power converter with improved performances. We demonstrated that LENS could enable exploration of very large design space of circuit topologies and components by addressing the limitations of conventional design process in non-linear, high switching speed, multi-dimensional power converter design and optimization. The key innovation developed in LENS is the seamless integration of statistical learning and logical reasoning techniques and building on the individual strengths of these techniques for rapid hypothesis discovery. The main component of LENS comprises of: 1) Graph Reasoning Engine (GRE) to enforce composition rules that rapidly reject all discrete architectures that are composed incorrectly and generates an adaptive database of feasible designs which can be used by ML modules, 2) Graph Generative Learning module which is a deep neural network based generative model for graph architectures which can enable design space exploration beyond the dataset generated by the GRE, 3) Graph Reduced Order Model (ROM) for graph domains for accelerating computation of output metrics, and 4) Active learning and Rule Discovery module for sample efficient learning and extracting logical rules from the learned ML models which will be integrated in the GRE to enhance the filtering effectiveness. LENS approach can be applied to any design domains where designs can be represented as multi-attribute graphs. The LENS team integrated the various technical innovations listed above into an optimization pipeline and exercised the optimization pipeline on the converter design problem. The LENS project demonstrated that the developed AI/ML technologies can be used to generate novel converter circuits >45x faster than experts on chosen use-cases. This can enable faster design space exploration and identification of new designs which are not considered by experts due to the increasing design space complexity. This has significant potential impact on the public and energy needs of the country. It is currently estimated that 30% of all electrical powers generated passes through power converters. The future estimate is that 80% of all power generated would be passing through converters. LENS fills a critical gap in this space since by accelerating the design process the designers would be able to generate more efficient converters which can lead to significant energy savings for the country.

42 ENGINEERING↗
DOE OSTI2022

Load-Packaged AC/DC and DC/DC Power Electronics Converter Performance Data

This data set contains experimentally characterized performance data from load-packaged alternating current to direct current (AC/DC) and direct current to direct current (DC/DC) power electronics converters associated with lighting devices and miscellaneous electrical loads typically found in commercial buildings in the United States. The data set contains input power, output power, efficiency, and harmonic spectrum data for 58 AC/DC converters and 35 DC/DC converters.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗