Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “active distribution networks”

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.

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

At least 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
NASA NTRS2015

Zero Boil-Off System Testing

Cryogenic propellants such as liquid hydrogen (LH2) and liquid oxygen (LO2) are a part of NASA's future space exploration due to their high specific impulse for rocket motors of upper stages suitable for transporting 10s to 100s of metric tons of payload mass to destinations outside of low earth orbit and for their return. However, the low storage temperatures of LH2 and LO2 cause substantial boil-off losses for missions with durations greater than several months. These losses can be eliminated by incorporating high performance cryocooler technology to intercept heat load to the propellant tanks and modulating the cryocooler to control tank pressure. The active thermal control technology being developed by NASA is the reverse turbo-Brayton cycle cryocooler and its integration to the propellant tank through a distributed cooling tubing network coupled to the tank wall. This configuration was recently tested at NASA Glenn Research Center, in a vacuum chamber and cryoshroud that simulated the essential thermal aspects of low Earth orbit, its vacuum and temperature. Testing consisted of three passive tests with the active cryocooler system off, and 7 active tests, with the cryocooler powered up. The test matrix included zero boil-off tests performed at 90 full and 25 full, and several demonstrations at excess cooling capacity and reduced cooling capacity. From this, the tank pressure response with varied cryocooler power inputs was determined. This test series established that the active cooling system integrated with the propellant tank eliminated boil-off and robustly controlled tank pressure.

Plachta, David W.↗
NASA NTRS2002

Relation Between Polar Plumes and Fine Structure in the Solar Wind from Ulysses High-Latitude Observations

Ulysses observations showed that pressure balance structures (PBSs) are a common feature in the high-latitude and high-speed solar winds near the solar minimum. On the other hand, coronal plumes are common in polar coronal holes. PBSs are believed to be remnants of coronal plumes and to be related to network activity such as magnetic reconnection in the photosphere from previous studies. This suggests that information on the magnetic structure of PBSs would help to confirm the relation between PBSs and polar plumes We have investigated the magnetic structures of the PBSs by applying a minimum variance analysis to Ulysses/Magnetometer data and by examining the pitch-angle distribution of energetic electrons measured with Ulysses/SWOOPS. We have found that PBSs have relatively more tangential discontinuities rather than rotational from the minimum variance analysis. Further, most PBSs also show bi-directional electron flux or isotropic pitch-angle distribution or the distribution expected in association with current-sheet structures from the analysis of high-energy electron data. In this, we find further evidence that PBSs are generated due by network activity at the base of polar plumes and their magnetic structures are like current sheets or plasmoids.

Yamauchi, Yohei↗
NASA NTRS2021

Advances in the Ocean Color Component of the Aerosol Robotic Network (AERONET-OC)

The Ocean Color Component of the Aerosol Robotic Network(AERONET-OC) supports activities related to ocean color such as validation of satellite data products, assessment of atmospheric correction schemes, and evaluation of bio-optical models through globally distributed standardized measurements of water-leaving radiance and aerosol optical depth. In view of duly assisting the AERONET-OC data user community, this work (i) summarizes the latest investigations on a number of scientific issues related to above-water radiometry, (ii) emphasizes the network expansion that from 2002 until the end of 2020 integrated 31 effective measurement sites, (iii) shows the equivalence of data product accuracy across sites and time for measurements performed with different instrument series, (iv) illustrates the variety of water types represented by the network sites ensuring validation activities across a diversity of observation conditions, and (v) documents the availability of water-leaving radiance data corrected for bidirectional effects by applying a method specifically developed for chlorophyll-a-dominated waters and an alternative one that is likely suitable for any water type.

In situ oceanic observations↗
DOE OSTI2023

Data-Driven Affinely Adjustable Robust Volt/VAr Control

Recent years have seen the increasing proliferation of distributed energy resources with intermittent power outputs, posing new challenges to the voltage management in distribution networks. To this end, this paper proposes a data-driven affinely adjustable robust Volt/VAr control (AARVVC) scheme, which modulates the smart inverter’s reactive power in an affine function of its active power, based on the voltage sensitivities with respect to real/reactive power injections. To achieve a fast and accurate estimation of voltage sensitivities, we propose a data-driven method based on deep neural network (DNN), together with a rule-based bus-selection process using the bidirectional search method. Our method only uses the operating statuses of selected buses as inputs to DNN, thus significantly improving the training efficiency and reducing information redundancy. Finally, a distributed consensus-based solution, based on the alternating direction method of multipliers (ADMM), for the AARVVC is applied to decide the inverter’s reactive power adjustment rule with respect to its active power. Only limited information exchange is required between each local agent and the central agent to obtain the slope of the reactive power adjustment rule, and there is no need for the central agent to solve any (sub)optimization problems. Finally, numerical results on the modified IEEE-123 bus system validate the effectiveness and superiority of the proposed data-driven AARVVC method.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2017

Liquid Nitrogen Zero Boiloff Testing

Cryogenic propellants such as liquid hydrogen (LH2) and liquid oxygen (LO2) are a part of NASAs future space exploration due to their high specific impulse for rocket motors of upper stages suitable for transporting 10s to 100s of metric tons of payload mass to destinations outside of low earth orbit and for their return. However, the low storage temperatures of LH2 and LO2 cause substantial boil-off losses for missions with durations greater than several months. These losses can be eliminated by incorporating high performance cryocooler technology to intercept heat load to the propellant tanks and modulating the cryocooler to control tank pressure. The active thermal control technology being developed by NASA is the reverse turbo-Brayton cycle cryocooler and its integration to the propellant tank through a distributed cooling tubing network coupled to the tank wall. This configuration was recently tested at NASA Glenn Research Center, in a vacuum chamber and cryo-shroud that simulated the essential thermal aspects of low Earth orbit, its vacuum and temperature. Testing consisted of three passive tests with the active cryo-cooler system off, and 7 active tests, with the cryocooler powered up. The test matrix included zero boil-off tests performed at 90 full and 25 full, and several demonstrations at excess cooling capacity and reduced cooling capacity. From this, the tank pressure response with varied cryocooler power inputs was determined. This test series established that the active cooling system integrated with the propellant tank eliminated boil-off and robustly controlled tank pressure.

Cryogenic fluid management↗
NASA NTRS2011

The Development of the Puerto Rico Lightning Detection Network for Meteorological Research

A land-based Puerto Rico Lightning Detection Network (PR-LDN) dedicated to the academic research of meteorological phenomena has being developed. Five Boltek StormTracker PCI-Receivers with LTS-2 Timestamp Cards with GPS and lightning detectors were integrated to Pentium III PC-workstations running the CentOS linux operating system. The Boltek detector linux driver was compiled under CentOS, modified, and thoroughly tested. These PC-workstations with integrated lightning detectors were installed at five of the University of Puerto Rico (UPR) campuses distributed around the island of PR. The PC-workstations are left on permanently in order to monitor lightning activity at all times. Each is networked to their campus network-backbone permitting quasi-instantaneous data transfer to a central server at the UPR-Bayam n campus. Information generated by each lightning detector is managed by a C-program developed by us called the LDN-client. The LDN-client maintains an open connection to the central server operating the LDN-server program where data is sent real-time for analysis and archival. The LDN-client also manages the storing of data on the PC-workstation hard disk. The LDN-server software (also an in-house effort) analyses the data from each client and performs event triangulations. Time-of-arrival (TOA) and related hybrid algorithms, lightning-type and event discriminating routines are also implemented in the LDN-server software. We also have developed software to visually monitor lightning events in real-time from all clients and the triangulated events. We are currently monitoring and studying the spatial, temporal, and type distribution of lightning strikes associated with electrical storms and tropical cyclones in the vicinity of Puerto Rico.

Legault, Marc D.↗
DOE OSTI2022

Phase Identification in Real Distribution Networks with High PV Penetration Using Advanced Metering Infrastructure Data

Many distribution network monitoring and control applications - including state estimation, volt/VAR optimization, and network reconfiguration - rely on accurate network models; however, the network models maintained by utilities can become outdated because of restoration activities, network reconfiguration, and missing data. With the widespread deployment of advanced metering infrastructure (AMI), abundant measurement data from low-voltage secondary networks are available. The AMI measurement data can be used for phase identification to improve the network models. Although the existing phase identification techniques work well in passive distribution feeders that do not have photovoltaic (PV) generation, they can fail to accurately identify the phases in the presence of PV. This paper proposes a robust phase identification algorithm based on supervised machine learning that accurately identifies the AMI meter phase connectivity in the presence of significant PV generation. The proposed algorithm does not require network topology information or feeder head measurement data. The algorithm is validated using the AMI measurement data collected in the field and the field-validated phase connectivity database on two real distribution feeders from San Diego Gas & Electric Company that have significant PV generation.

advanced metering infrastructure↗
DOE OSTI2022

Phase Identification in Real Distribution Networks with High PV Penetration Using Advanced Metering Infrastructure Data: Preprint

Many distribution network monitoring and control applications - including state estimation, volt/VAR optimization, and network reconfiguration - rely on accurate network models; however, the network models maintained by utilities can become outdated because of restoration activities, network reconfiguration, and missing data. With the widespread deployment of advanced metering infrastructure (AMI), abundant measurement data from low-voltage secondary networks are available. The AMI measurement data can be used for phase identification to improve the network models. Although the existing phase identification techniques work well in passive distribution feeders that do not have photovoltaic (PV) generation, they can fail to accurately identify the phases in the presence of PV. This paper proposes a robust phase identification algorithm based on supervised machine learning that accurately identifies the AMI meter phase connectivity in the presence of significant PV generation. The proposed algorithm does not require network topology information or feeder head measurement data. The algorithm is validated using the AMI measurement data collected in the field and the field-validated phase connectivity database on two real distribution feeders from San Diego Gas & Electric Company that have significant PV generation.

advanced metering infrastructure↗
DOE OSTI2022

Phase Identification in Real Distribution Networks with High PV Penetration Using Advanced Metering Infrastructure Data

Many distribution network monitoring and control applications - including state estimation, Volt/VAr optimization, and network reconfiguration - rely on accurate network models; however, the network models maintained by utilities can become outdated because of restoration activities, network reconfiguration, and missing data. With the widespread deployment of advanced metering infrastructure (AMI), abundant measurement data from low-voltage secondary networks are available. The AMI measurement data can be used for phase identification to improve the network models. Although the existing phase identification techniques work well in passive distribution feeders that do not have photovoltaic (PV) generation, they can fail to accurately identify the phases in the presence of PV. This paper proposes a robust phase identification algorithm based on supervised machine learning that accurately identifies the AMI meter phase connectivity in the presence of significant PV generation. The proposed algorithm does not require network topology information or feeder-head measurement data. The algorithm is validated using the AMI measurement data collected in the field and the field-validated phase connectivity database on two real distribution feeders from San Diego Gas & Electric Company that have significant PV generation.

advanced metering infrastructure (AMI)↗
DOE OSTI2021

High-Performance All-Polymer Solar Cells and Photodetectors Enabled by a High-Mobility n-Type Polymer and Optimized Bulk-Heterojunction Morphology

All-polymer solar cells (all-PSCs) and all-polymer photodetectors (all-PPDs) are promising for application in flexible electronics, but their performance is greatly limited by the lack of polymer acceptors and the difficulties in morphology control. Herein, we report the use of a high-mobility n-type polymer semiconductor, PNDI-DTBT, for fabricating high-performance all-PSCs and all-PPDs. By pairing PNDI-DTBT with a matched polymer donor, a prominent power conversion efficiency of 8.5% was obtained in all-PSCs, demonstrating the great potential of high-mobility n-type polymers with a conventional donor–acceptor skeleton for photovoltaic application. Moreover, all-PPDs with a low dark current density of 1.32 × 10 –8 A cm –2 at –0.1 V bias and a high specific detectivity of 4.77 × 10 12 Jones were achieved, which belong to the best results of organic photodetectors. Morphology investigations revealed that the formation of a bicontinuous interpenetrating network with optimal phase separation scale, high domain purity, and preferential vertical composition distribution in the bulk-heterojunction active layer contribute to the remarkable device performance. Furthermore, these results suggest that combining high-mobility n-type polymers and morphology optimization is fruitful to achieving high-performance all-PSCs and all-PPDs.

36 MATERIALS SCIENCE↗
NASA NTRS1984

Modeling the weather with a data flow supercomputer

A static concept of data flow architecture is considered for a supercomputer for weather modeling. The machine level instructions are loaded into specific memory locations before computation is initiated, with only one instruction active at a time. The machine would have processing element, functional unit, array memory, memory routing and distribution routing network elements all contained on microprocessors. A value-oriented algorithmic language (VAL) would be employed and would have, as basic operations, simple functions deriving results from operand values. Details of the machine language format, computations with an array and file processing procedures are outlined. A global weather model is discussed in terms of a static architecture and the potential computation rate is analyzed. The results indicate that detailed design studies are warranted to quantify costs and parts fabrication requirements.

Dennis, J. B.↗
NASA NTRS1993

Predicting scheduling success

This paper provides an analytical formulation to predict scheduling success for a class of problems frequently referred to as activity scheduling. Space Network communications scheduling is an example of activity scheduling. The principal assumption is that the activity start times are randomly distributed over the available time in the time line. The formulation makes it possible to estimate how much of the demand can be scheduled as a function of the demand, number of resources, activity duration, and activity flexibility. The paper includes computed results for a variety of resource and demand conditions. The results demonstrate that even with highly flexible activities, it is difficult to schedule demand greater than 60 percent of resources without the use of optimization and conflict resolution capabilities in the scheduling system.

Messing, Fredric↗
NASA NTRS2002

Studies of Transient Meteor Activity

Meteoroids bombard Earth's atmosphere daily, but occasionally meteor rates increase to unusual high levels when Earth crosses the relatively fresh ejecta of comets. These transient events in meteor activity provide clues about the whereabouts of Earth-threatening long-period comets, the mechanisms of large-grain dust ejection from comets, and the particle composition and size distribution of the cometary ejecta. Observations of these transient events provide important insight in natural processes that determine the large grain dust environment of comets, in natural phenomena that were prevalent during the time of the origin of life, and in processes that determine the hazard of civilizations to large impacts and of man-made satellites to the periodic blizzard of small meteoroids. In this proposal, three tasks form a coherent program aimed at elucidating various aspects of meteor outbursts, with special reference to planetary astronomy and astrobiology. Task 1 was a ground-based effort to observe periods of transient meteor activity. This includes: (1) stereoscopic imaging of meteors during transient meteor events for measurements of particle size distribution, meteoroid orbital dispersions and fluxes; and (2) technical support for Global-MS-Net, a network of amateur-operated automatic counting stations for meteor reflections from commercial VHF radio and TV broadcasting stations, keeping a 24h vigil on the level of meteor activity for the detection of new meteor streams. Task 2 consisted of ground-based and satellite born spectroscopic observations of meteors and meteor trains during transient meteor events for measurements of elemental composition, the presence of organic matter in the meteoroids, and products generated by the interaction of the meteoroid with the atmosphere. Task 3 was an airborne effort to explore the 2000 Leonid meteor outbursts, which are anticipated to be the most significant of transient meteor activity events in the remainder of the agreement period. This includes technical support for a multi-instrument aircraft campaign, Leonid MAC.

Jenniskens, Peter M. M.↗
DOE OSTI2023

A Mixed integer linear programming‐based distributed energy management for networked microgrids considering network operational objectives and constraints

Abstract Mixed integer linear programming (MILP)–based distributed energy management for networked microgrids embedded modern distribution systems is proposed. Considering the diverse ownership of microgrids, distributed energy resources (DERs) that interface directly with utilities and responsive loads, an alternating direction method of multipliers–based distributed framework was formulated for the scheduling of networked microgrids embedded modern distribution systems by adjusting nodal price signals iteratively. In addition, to make the formulated optimization problems resolvable through more accessible and popular MILP solvers, different linearisation techniques were employed to transform the nonlinear terms into linear or mixed integer linear formats. The proposed MILP‐based distributed method preserves all participants' autonomy (e.g., microgrids, DERs that interface directly with utilities and responsive loads), while incentivising them to actively participate in the distribution system operation with price signals. The proposed method is validated with results of numerical simulation using a modern distribution system consisting of multiple networked microgrids, DERs that interface directly with utilities, as well as responsive loads.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2017

A 3D Active Learning Application for NeMO-Net, the NASA Neural Multi-Modal Observation and Training Network for Global Coral Reef Assessment

NeMO-Net, the NASA neural multi-modal observation and training network for global coral reef assessment, is an open-source deep convolutional neural network and interactive active learning training software aiming to accurately assess the present and past dynamics of coral reef ecosystems through determination of percent living cover and morphology as well as mapping of spatial distribution. We present an interactive video game prototype for tablet and mobile devices where users interactively label morphology classifications over mm-scale 3D coral reef imagery captured using fluid lensing to create a dataset that will be used to train NeMO-Nets convolutional neural network. The application currently allows for users to classify preselected regions of coral in the Pacific and will be expanded to include additional regions captured using our NASA FluidCam instrument, presently the highest-resolution remote sensing benthic imaging technology capable of removing ocean wave distortion, as well as lower-resolution airborne remote sensing data from the ongoing NASA CORAL campaign. Active learning applications present a novel methodology for efficiently training large-scale Neural Networks wherein variances in identification can be rapidly mitigated against control data. NeMO-Net periodically checks users input against pre-classified coral imagery to gauge their accuracy and utilize in-game mechanics to provide classification training. Users actively communicate with a server and are requested to classify areas of coral for which other users had conflicting classifications and contribute their input to a larger database for ranking. In partnering with Mission Blue and IUCN, NeMO-Net leverages an international consortium of subject matter experts to classify areas of confusion identified by NeMO-Net and generate additional labels crucial for identifying decision boundary locations in coral reef assessment.

NeMO=NET↗
NASA NTRS2003

Software To Secure Distributed Propulsion Simulations

Distributed-object computing systems are presented with many security threats, including network eavesdropping, message tampering, and communications middleware masquerading. NASA Glenn Research Center, and its industry partners, has taken an active role in mitigating the security threats associated with developing and operating their proprietary aerospace propulsion simulations. In particular, they are developing a collaborative Common Object Request Broker Architecture (CORBA) Security (CORBASec) test bed to secure their distributed aerospace propulsion simulations. Glenn has been working with its aerospace propulsion industry partners to deploy the Numerical Propulsion System Simulation (NPSS) object-based technology. NPSS is a program focused on reducing the cost and time in developing aerospace propulsion engines

Blaser, Tammy M.↗
NASA NTRS2000

BOREAS AFM-5 Level-1 Upper Air Network Data

The Boreal Ecosystem-Atmosphere Study (BOREAS) Airborne Fluxes and Meteorology (AFM)-5 team collected and processed data from the numerous radiosonde flights during the project. The goals of the AFM-05 team were to provide large-scale definition of the atmosphere by supplementing the existing Atmospheric Environment Service (AES) aerological network, both temporally and spatially. This data set includes basic upper-air parameters collected from the network of upper-air stations during the 1993, 1994, and 1996 field campaigns over the entire study region. The data are contained in tabular ASCII files. The level-1 upper-air network data are available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). The data files also are available on a CD-ROM (see document number 20010000884).

Barr, Alan↗
NASA NTRS2004

User-Friendly Interface Developed for a Web-Based Service for SpaceCAL Emulations

A team at the NASA Glenn Research Center is developing a Space Communications Architecture Laboratory (SpaceCAL) for protocol development activities for coordinated satellite missions. SpaceCAL will provide a multiuser, distributed system to emulate space-based Internet architectures, backbone networks, formation clusters, and constellations. As part of a new effort in 2003, building blocks are being defined for an open distributed system to make the satellite emulation test bed accessible through an Internet connection. The first step in creating a Web-based service to control the emulation remotely is providing a user-friendly interface for encoding the data into a well-formed and complete Extensible Markup Language (XML) document. XML provides coding that allows data to be transferred between dissimilar systems. Scenario specifications include control parameters, network routes, interface bandwidths, delay, and bit error rate. Specifications for all satellite, instruments, and ground stations in a given scenario are also included in the XML document. For the SpaceCAL emulation, the XML document can be created using XForms, a Webbased forms language for data collection. Contrary to older forms technology, the interactive user interface makes the science prevalent, not the data representation. Required versus optional input fields, default values, automatic calculations, data validation, and reuse will help researchers quickly and accurately define missions. XForms can apply any XML schema defined for the test mission to validate data before forwarding it to the emulation facility. New instrument definitions, facilities, and mission types can be added to the existing schema. The first prototype user interface incorporates components for interactive input and form processing. Internet address, data rate, and the location of the facility are implemented with basic form controls with default values provided for convenience and efficiency using basic XForms operations. Because different emulation scenarios will vary widely in their component structure, more complex operations are used to add and delete facilities.

Liszka, Kathy J.↗