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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Machine learning pipeline for denoising low signal-to-noise ratio and out-of-distribution transmission electron microscopy datasets

High-resolution transmission electron microscopy (HRTEM) is crucial for observing material’s structural and morphological evolution at Angstrom scales, but the electron beam can alter these processes. Devices such as CMOS-based direct-electron detectors operating in electron-counting mode can be utilized to substantially reduce the electron dosage. However, the resulting images often lead to a low signal-to-noise ratio, which requires frame integration that sacrifices temporal resolution. Several machine learning (ML) models have been recently developed to successfully denoise HRTEM images. Yet, these models are often computationally expensive, and their inference speeds on GPUs are outpaced by the imaging speed of advanced detectors, precluding in situ analysis. Furthermore, the performance of these denoising models on datasets with imaging conditions that deviate from the training datasets has not been evaluated. To mitigate these gaps, we propose a new self-supervised ML denoising pipeline specifically designed for time-series HRTEM images. This pipeline integrates a blind-spot convolution neural network with pre-processing and post-processing steps, including drift correction and low-pass filtering. Results demonstrate that our model outperforms various other ML and non-ML denoising methods in noise reduction and contrast enhancement, leading to improved visual clarity of atomic features. Additionally, the model is drastically faster than U-Net-based ML models and demonstrates excellent out-of-distribution generalization. The model’s computational inference speed is in the order of milliseconds per image, rendering it suitable for application in in-situ HRTEM experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Robust Distributed State Estimator for Interconnected Transmission and Distribution Networks (Final Report RPPR-1)

This project’s objective is to develop a combined transmission and distribution state estimator which accounts for very large system size and model complexity (by way of distributing the computations) and large number of solar PV units connected to the distribution system on multiple feeders. The project not only provides a robust formulation and solution to this problem but also tests the solution by implementing it on a well-established large utility system. It introduces several improvements with respect to the state of the art in existing state estimation software: (a) The developed state estimator (SE) allows robust and accurate monitoring of bidirectional flows in distribution systems which result due to the distributed energy sources which are not observable and thus not incorporated in generation dispatch; (b) Large utility systems with tens of thousands of transmission buses and hundreds of thousands of distribution nodes are difficult to model as a single integrated system. This shortcoming is addressed by developing a “scalable distributed computational framework” which allows splitting the ultra large system models into several small subsystems and coordinating their solution by a robust and practical state estimation formulation; (c) Measurement errors irrespective of their locations are detected and removed by the developed state estimator. Historically, transmission and distribution systems were analyzed and operated as two independent systems. Given the non-transposed short feeder sections, unevenly loaded phases, strictly radial configuration and unidirectional power flows in the absence of remote generation, distribution system analysis was customized to account for these characteristics. However, some of these assumptions are no longer valid (non-radial configuration, bidirectional power flows) and thus distribution system analysis should be revisited. Furthermore, in the past, the interaction between the transmission and distribution systems was quite passive, where distribution substations were modeled as lumped loads in the transmission system model. With substantial generation injected by renewable generation located in the distribution systems, such modeling will no longer be accurate. The developed state estimator facilitates proper monitoring of the interactions between the transmission and distribution systems and enables smart dispatch of these units which are made observable by the state estimator.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Real-World Distribution System Modeling Framework for Transmission-and-Distribution Cosimulation: Preprint

This paper presents a modeling methodology for realistic distribution system simulation and analysis. The methodology involves three major approaches: utility model conversion, feeder load modeling, and feeder model validation. The feeder models obtained from the utility are converted to the format that is more flexible for analysis and algorithm development. The load profiles down to each node are modeled in detail using advanced metering infrastructure data and supervisory control and data acquisition (SCADA) system measured load data. Then the distribution system models are validated by comparing the simulated feeder-head voltage results and SCADA measured voltage data. To better understand the bulk system operations and the interactions between transmission and distribution systems, the modeled realistic distribution systems are integrated into a transmission-and-distribution cosimulation framework to perform the system simulation from the bulk system down to each node in the distribution system.

load modeling↗
DOE OSTI2024

Technical Impacts of Light-Duty and Heavy-Duty Transportation Electrification on a Coordinated Transmission and Distribution System

In this study, we propose a strategy to model the required spatiotemporal charging demand from light-duty (LD) and medium- and heavy-duty (MHD) electric vehicles (EVs) using actual transportation data by mapping the demand for the required EV charging to a realistic and coordinated distribution and transmission electric grid at the predicted times of the day to study their impact on the power system in a variety of load, weather, and EV penetration scenarios. This work is the first study that includes the actual weather data and transportation data with realistic and coordinated distribution and transmission grid data in a large industry-scale level study. The main goal of this study is to identify possible issues and required upgrades in the electric grid, caused by an increase in EV integration. The transmission case study is a large grid with 6717 buses over a Texas footprint, and the distribution grid is over Houston, a city in Texas, covering over three million customers. The resulting overloads and voltage violations experienced in the system are discussed, and required planning upgrades to avoid these issues are suggested.

AC optimal power flow (AC-OPF)↗
NASA NTRS1982

Air data measurement using distributed processing and fiber optics data transmission

Distributed processing, fiber optics technology, and redundancy management in the aircraft environment are discussed. The project features the development of an angle-of-attack and sideslip data collection system hich features: (1) two independent microprocessor controlled data collection and calibration units; (2) transmission of data to the control system on a fiber optic data bus; and (3) software implemented error detection and recovery.

Farry, K. A.↗
DOE OSTI2020

Economic Dispatch With Distributed Energy Resources: Co-Optimization of Transmission and Distribution Systems

The increasing penetration of distributed energy resources (DERs) in the distribution networks has turned the conventionally passive load buses into active buses that can provide grid services for the transmission system. To take advantage of the DERs in the distribution networks, this letter formulates a transmission-and-distribution (T&D) systems co-optimization problem that achieves economic dispatch at the transmission level and optimal voltage regulation at the distribution level by leveraging large generators and DERs. A primal-dual gradient algorithm is proposed to solve this optimization problem jointly for T&D systems, and a distributed market-based equivalent of the gradient algorithm is used for practical implementation. Finally, the results are corroborated by numerical examples with the IEEE 39-Bus system connected with 7 different distribution networks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Synthetic, Realistic Transmission and Distribution Co-Simulation for Voltage Control Benchmarking: Preprint

As distributed energy resources play an increasing role in generation and grid services, control and market paradigms will need to be tested with models that incorporate transmission and distribution systems. The test systems will need to be realistic and accessible for researchers to form conclusions about realistic behaviors and maintain comparability and repeatability of results. These test systems also must have high resolution models of sufficient size for realistic distribution and transmission interaction. This paper demonstrates the tightly coupled co-simulation of realistic synthetic distribution and transmission models for the Austin metropolitan area and how this framework can be used to analyze resultant behaviors from distributed resources and their controls. The comparison of a distribution system run with fixed feed-in voltage is compared to the closely tied distribution-transmission co-simulation. It is determined that even without advanced voltage controls, the feed-in voltage response of the transmission system shows a lower level of voltage excursions. Therefore, control methods for voltage stability should be benchmarked on realistic transmission and distribution co-simulations for more accurate assessment of voltage profiles.

27 ARPA - Advanced Research Projects Agency-Energy↗
DOE OSTI2025

CPUC Avoided Transmission and Distribution Cost Study to Support the Avoided Cost Calculator: Avoided Transmission Costs Draft Research Plan

Pacific Northwest National Laboratory (PNNL) and Lawrence Berkeley National Laboratory (LBNL) have been contracted by the California Public Utilities Commission (CPUC) Energy Division (ED) to perform a study which explores and selects an improved methodology to estimate avoided electricity transmission and distribution (T&D) infrastructure costs that can be attributed to the presence of distributed energy resources (DERs). PNNL is performing the study for avoided electricity transmission infrastructure costs and LBNL is performing the study for avoided electricity distribution infrastructure costs. This document summarizes CPUC’s research questions related to avoided transmission infrastructure costs and PNNL’s proposed technical approach to answer these questions.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Cyber-Physical Events Emulation Based Transmission and Distribution Co-Simulation for Situation Awareness and Grid Anomaly (SAGA) Detection: Preprint

Energy management of transmission and distribution networks is becoming more challenged with the accelerated increasing of distributed energy resources (DERs) such as distributed photovoltaic (PV) generation and distributed energy storage. To better analyze the impacts of DERs on both transmission and distribution systems, a comprehensive transmission and distribution co-simulation platform should be developed. Furthermore, with DERs more actively participated in system operation such as providing real time grid services, their cyber vulnerability should be better understood to maintain system reliability. This paper discussed a cyber-physical events emulation based transmission & distribution co-simulation platform to perform different cyber events emulation and analyze the impacts of cyber physical events happened in distribution system on the T&D system operation. The case studies with both a transmission network and a synthetic distribution network data validate that the proposed T&D co-simulation platform can perform comprehensive cyber physical events emulation. Therefore, with extensive simulation using the proposed model, the system operator can accumulate adequate training data for the system situation awareness and grid anomaly detection purpose.

31 CESER - Office of Cybersecurity, Energy Securit↗
DOE OSTI2024

A Survey of Open-Source Tools for Transmission and Distribution Systems Research

This work presents a review of open-source electric power transmission and distribution systems analysis tools suitable for use by industry professionals and academic researchers. Due to the high complexity of the electric grid, there exist numerous tools and extensive research pertaining to nearly every aspect of the design, operation, and control of transmission and distribution networks. In addition to the commercial tools, a wide range of free, open-source tools, models, and data usable by the scientific community for related research have been developed by different organizations, including both international and US universities and national laboratories. However, due to the absence of a catalog of available tools, models and data, researchers often lack a knowledge of existing capabilities and may develop duplicative software and tools. Increasing awareness of these available resources seeks to accelerate their broader use, leading to more efficient and standardized grid analysis. This review paper (which is part of a larger survey effort that studied over 400 tools in the transmission, distribution, buildings, and electric vehicles space) outlines selected open-source resources that have been developed in power transmission and distribution systems research. It is anticipated that this work can serve as a guide for industry and academic researchers alike, ensuring that research efforts are well-channeled.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Secure Wireless Communication Using Distributed Coherent Transmission and Spatial Signal Decomposition

We present a new approach to secure wireless communications using coherent distributed transmission of signals that are spatially decomposed between a two-element distributed antenna array. High-accuracy distributed coordination of microwave wireless systems supports the ability to transmit different parts of a signal from separate transmitters such that they combine coherently at a designated destination. In this article, we explore this concept using a two-element coherent distributed phased array where each of the two transmitters sends a separate component of a communication signal, where each symbol is decomposed into a sum of two pseudorandom signal vectors, the coherent summation of which yields the intended symbol. By directing the transmission to an intended receiver using distributed beamforming, the summation of the two vector components is largely confined to a spatial region at the destination receiver. We implement the technique in a $50−λ$ array operating at 3 GHz. We evaluate the symbol error rate (SER) in 2-D space through simulation and measurement, showing that the approach yields a spatially confined secure region where the information is recoverable (i.e., the received signal has low SER), and outside of which the information is unrecoverable (high SER). The proposed system is also compared against a traditional beamforming system where each node sends the same data. We validate experimentally that our approach achieves a low SER of 0.0082 at broadside and an SER above 0.25 at all other locations compared to a traditional beamforming approach that achieves a SER of 0 at all locations measured.

Engineering - Electronic and electrical engineerin↗
DOE OSTI2021

Synthetic, Realistic Transmission and Distribution Co-Simulation for Voltage Control Benchmarking

As distributed energy resources (DERs) play an increasing role in generation and grid services, control and market paradigms will need to be tested with models that incorporate transmission and distribution systems. The test systems will need to be realistic and accessible for researchers to form conclusions about realistic behaviors and maintain comparability and repeatability of results. These test systems also must have high resolution models of sufficient size for realistic distribution and transmission interaction. This paper demonstrates the tightly coupled HELICS-based co-simulation of realistic synthetic distribution and transmission models for the Austin metropolitan area and how this framework can be used to analyze resultant behaviors from distributed resources and their controls. These results are compared to the same distribution system run without co-simulation using a fixed feed-in voltage. Results show that even without advanced voltage controls, the feed-in voltage response when coupled to the transmission system results a lower level of voltage excursions, suggesting the importance of using this type of realistic, tightly coupled, transmission and distribution cosimulation when assessing DERs.

27 ARPA - Advanced Research Projects Agency-Energy↗