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DOE OSTI2024

Microgrid to Microgrid Synchronization with Grid-Forming Inverters: Challenges and Solution

Research on network microgrids has primarily focused on control and optimization. However, application aspects such as microgrid-to-microgrid synchronization have not been fully addressed in existing literature. This paper first addresses the challenges of networking microgrids with grid-forming inverter in droop control. Then, it proposes a pre-synchronization algorithm to improves the synchronization speed and transient stability. To improve the speed, the phase difference between adjacent microgrids is minimized. Transients such as inrush current and oscillations are effectively mitigated by increasing the virtual impedance during interconnection. The proposed strategy allows smooth transitions when reconfiguration of the microgrids is needed. The applicability of this strategy to today’s microgrid systems is demonstrated through a validation in a 480V three-phase network microgrid testbed with commercial-grade inverters, protective devices, and switchgear.

Ferrari Maglia, Max↗

NASA NTRS2018

Portable, Low-Cost, Column Carbon Dioxide and Methane Measurements for Validating Satellite Observations in Remote Locations

We present a low-cost (~$10K per instrument), portable solution to ground-based validation of satellite observations for difficult to reach locations with precisions of 1 ppm XCO2 and 10 ppb XCH4 for hourly data products. While Total Carbon Column Observing Network (TCCON) is the gold-standard for ground validation, there are locations where a ground column validation data point would be useful but conditions are not conducive to a permanent station. Examples include wetlands, thawing permafrost, the tropics, the Amazon, sub-Saharan Africa, as well as locations without a power grid or with geopolitical conflict. In addition, the low-cost and portability mean a geographical region can be studied in depth with multiple instruments. This passive, sun-pointing instrument is a miniaturized, laser heterodyne radiometer (mini-LHR) that has been under development by our team since 2009. It can be operated either in tandem with AERONET (a global network of 500 instruments that measure aerosol optical depth), or as a stand-alone instrument with a low-cost (~$3K), light-weight sun tracker. One of the main benefits of the mini-LHR is that it can quickly reach remote locations and provide a validation measurement even if there is limited or no infrastructure at the site. The instrument weighs ~10 lbs, fits into a backpack, and is powered by two folding solar panels and a battery pack. In clear conditions, the instrument can be set-up in under an hour. Portability means that mini-LHRs can be easily moved for side-by-side comparisons with other mini-LHRs and with TCCON which simplifies assessing instrument bias as well as accuracy. Like TCCON, the mini-LHR points directly at the sun with a narrow field-of-view and is its insensitivity to cloud and aerosol scattering that is common to nadir-pointing passive satellite approaches. Here we present a collection of sample data sets to demonstrate performance from locations that vary in climate, altitude, solar zenith angle, hours of sun per day, etc., as well as data from side-by-side TCCON comparisons. Retrievals of CO2 and CH4 were completed using the NASA/Goddard's Planetary Spectrum Generator (PSG) that incorporates meteorological inputs from Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) data set.

Wilson, Emily W.↗

NASA NTRS2010

MMIC Amplifiers and Wafer Probes for 350 to 500 GHz

A wireless avionics interface exploits the constrained nature of data networks in flight systems to use a lightweight routing method. This simplified routing means that a processor is not required, and the logic can be implemented as an intellectual property (IP) core in a field-programmable gate array (FPGA). The FPGA can be shared with the flight subsystem application. In addition, the router is aware of redundant subsystems, and can be configured to provide hot standby support as part of the interface. This simplifies implementation of flight applications requiring hot stand - by support. When a valid inbound packet is received from the network, the destination node address is inspected to determine whether the packet is to be processed by this node. Each node has routing tables for the next neighbor node to guide the packet to the destination node. If it is to be processed, the final packet destination is inspected to determine whether the packet is to be forwarded to another node, or routed locally. If the packet is local, it is sent to an Applications Data Interface (ADI), which is attached to a local flight application. Under this scheme, an interface can support many applications in a subsystem supporting a high level of subsystem integration. If the packet is to be forwarded to another node, it is sent to the outbound packet router. The outbound packet router receives packets from an ADI or a packet to be forwarded. It then uses a lookup table to determine the next destination for the packet. Upon detecting a remote subsystem failure, the routing table can be updated to autonomously bypass the failed subsystem.

Samoska, Lorene A.↗

NASA NTRS2010

Interface Supports Lightweight Subsystem Routing for Flight Applications

Lux, James P.↗

DOE OSTI2023

Large-Signal Stability of Phase-Balanced Equilibria in Single-Phase Grid-Forming Inverter Systems

This article explores the setup where large numbers of single-phase grid-forming inverters with droop control across distribution networks self-organize into a stable and balanced system with 120° phase offsets across aggregates in the absence of balanced three-phase generating resources or external communication. A suite of circuit- and system-theoretic notions are leveraged to derive a dynamical model for phase-angle differences across aggregates of inverters connected in the three phases. Focusing on this model, large-signal stability is established and the region of attraction of the phase-balanced equilibria is determined with the aid of a Lyapunov function. Experimental validation for a bench-top prototype network is included to support the analytical developments. Altogether, the effort supports the vision of facilitating balanced operation of distribution networks with grid-forming inverters during service disruptions at the bulk transmission network.

Droop control↗

DOE OSTI2024

ATR NEXSHARE Fact Sheet

This fact sheet will provide information for the database of experimental facilities supported by the IAEA as outlined below: NEXSHARE: As part of the Nuclear Harmonization and Standardization Initiative (NHSI), the IAEA proposes to establish a Network for global cooperation and resource sharing for experiments and code validation between experimental facilities, SMRs design organizations, International Organizations and Technical Support Organizations (TSOs). The proposed Network, NEXSHARE, will be done in collaboration with the OECD/NEA. EXPERIMENTAL FACILITY DATABASE: As part of this activity, the IAEA is compiling a database of experimental facilities applicable to SMRs (including water cooled, high temperature gas cooled, molten salt and fast neutron spectrum reactors). This database will also form part of NEXSHARE and will be documented in an IAEA publication.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NASA NTRS2021

Assessment of aerosol burden over Ghana

Although air pollution in Ghana is ranked number one in environmental health threats to public health and sixth to cause of deaths, routine monitoring is rare. This paper presents fourteen years (2005-2018) assessment of aerosol optical depth (AOD) at 3 km resolution from MODIS Aqua and Terra satellites to ascertain the Spatio-temporal and seasonal distribution of aerosols over Ghana and its major cities. The MODIS AOD at 3 km were validated against ground-based Aerosol Robotic Network (AERONET) AODs to ascertain the suitability of the MODIS 3 km data for air quality application in the region. The contribution of distant aerosols to city aerosol loadings was also assessed with Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) backscatter model. A moderate-high aerosol burden (AODs ~ 0.50) was observed over Ghana with a significant contribution from the pre-monsoon season. City centres of Takoradi and Kumasi showed higher aerosol loads (AODs ~ 0.80) than Accra and Tamale. The HYSPLIT model showed that distant or transported aerosol sources to the city centres were of both marine and land generated origins. Linear regression analysis between MODIS AOD and AERONET AOD showed a reasonably good correlation of ~ 0.60 for Aqua and Terra. From the validation analysis, both Aqua and Terra satellites can be used for air quality monitoring over Ghana; however, more ground research must be conducted to ascertain better aerosol model assumptions for the region.

Aerosols↗

NASA NTRS2023

Evaluating MODIS Snow Products Using an Extensive Wildlife Camera Network

Snow covers a maximum of 47 million km 2 of Earth's northern hemisphere each winter and is an important component of the planet's energy balance, hydrology cycles, and ecosystems. Monitoring regional and global snow cover has increased in urgency in recent years due to warming temperatures and declines in snow cover extent. Optical satellite instruments provide large-scale observations of snow cover, but cloud cover and dense forest canopy can reduce accuracy in mapping snow cover. Remote camera networks deployed for wildlife monitoring operate below cloud cover and in forests, representing a virtually untapped source of snow cover observations to supplement satellite observations. Using images from 1,181 wildlife cameras deployed by the Norwegian Institute for Nature Research (NINA), we compared snow cover extracted from camera images to Moderate Resolution Imaging Spectroradiometer (MODIS) snow cover products during winter months of 2018–2020. Ordinal snow classifications (scale = 0–4) from cameras were closely related to normalized difference snow index (NDSI) values from the MODIS Terra Snow Cover Daily L3 Global 500m (MOD10A1) Collection 6 product (R 2 = 0.70). Tree canopy cover, the normalized difference vegetation index (NDVI), and image color mode influenced agreement between camera images and MOD10A1 NDSI values. For MOD10A1F, MOD10A1's corresponding cloud-gap filled product, agreement with cloud-gap filled values decreased from 78.5% to 56.4% in the first three days of cloudy periods and stabilized thereafter. Using our camera data as validation, we derived a threshold to create daily binary maps of snow cover from the MOD10A1 product. The threshold corresponding to snow presence was an NDSI value of 40.50, which closely matched a previously defined global binary threshold of 40 using the MOD10A2 8-day product. These analyses demonstrate the utility of camera trap networks for validation of snow cover products from satellite remote sensing, as well as their potential to identify sources of inaccuracy.

Validation↗

NASA NTRS2018

AMSR2 Soil Moisture Downscaling Using Temperature and Vegetation Data

Soil moisture (SM) applications in terrestrial hydrology require higher spatial resolution soil moisture products than those provided by passive microwave remote sensing instruments (grid resolution of 9 km or larger). In this investigation, an innovative algorithm that uses visible/infrared remote sensing observations to downscale Advanced Microwave Scanning Radiometer 2 (AMSR2) coarse spatial resolution SM products was developed and implemented for use with data provided by the Advanced Microwave Scanning Radiometer 2 (AMSR2). The method is based on using the Normalized Difference Vegetation Index (NDVI) modulated relationships between day/night SM and temperature change at corresponding times. Land surface model output variables from the North America Land Data Assimilation System (NLDAS), remote sensing data from the Moderate-Resolution Imaging Spectroradiometer (MODIS), and Advanced Very High Resolution Radiometer (AVHRR) were used in this methodology. The functional relationships developed using NLDAS data at a grid resolution of 12.5 km were applied to downscale AMSR2 JAXA (Japan Aerospace Exploration Agency) SM product (25 km) using MODIS land surface temperature (LST) and NDVI observations (1 km) to produce the 1 km SM estimates. The downscaled SM estimates were validated by comparing them with ISMN (International Soil Moisture Network) in situ SM in the Black Bear-Red Rock watershed, central Oklahoma between 2015-2017. The overall statistical variables of the downscaled AMSR2 SM validation R2, slope, RMSE and bias, demonstrate good accuracy. The downscaled SM better characterized the spatial and temporal variability of SM at watershed scales than the original SM product.

AMSR2; passive microwave soil moisture; soil moist↗

DOE OSTI2020

CEEP (Cyber-Energy Emulation Platform) [SWR-20-102]

NREL's Cyber-Energy Emulation Platform (CEEP) provides the capability to realize cyber-energy security and resilience through automation and orchestration of virtualized systems and software defined networks for the electric grid. CEEP enables testing and validation of grid-security and -control methodologies as the grid evolves to include smart technologies/systems, such as virtualization and containerization of grid components, software defined networking, simulation and co-simulation frameworks, and hardware in the loop. CEEP is a modular system that can be distributed and deployed across different hardware infrastructure sizes and network architectures. For example, CEEP can visualize, emulate, and/or coordinate the Smart-Grid Network Visualization, Intrusion Detection, and Network Healing system. Using CEEP, intrusion-detection and network-self-healing solutions can be deployed at grid control centers, within secure private clouds, and in cyber-energy appliances.

Vaughan, Evan↗

DOE OSTI2022

Cyber Energy Emulation Platform (CEEP) [SWR-20-102]

Rivera, Joshua↗

DOE OSTI2022

Rates and Reversibilities in Interconnected Reaction Networks

Mathematical relations prescribing unidirectional forward and reverse rates originally derived based on single-path reaction sequences do not apply to interconnected reaction networks. The presence of branches in reaction networks, leading to alternative stable products, decreases unidirectional rates in reference to those calculated by single-path functional forms, as shown by simulated isotopic exchange rates, but impacts the unidirectional forward and reverse rates equally such that the functional form of effective reversibility remains unchanged. Regardless of stoichiometric numbers and network connectivity, the application of the pseudo-steady-state hypothesis on reactive intermediates in conjunction with consideration of unidirectional rates toward the product of interest and all alternative stable products results in mathematical expressions that accurately reflect simulated isotopic exchange rates. Further analyses based on kinetic resistance, a property akin to electrical resistance, illustrate the manifestation of nodal resistances in addition to the single-path kinetic resistance for interconnected reaction networks. The generalized formalism for assessing rates and reversibilities in interconnected networks derived herein enables us to demonstrate that unidirectional rates cannot be assessed solely from effective reversibilities and net rates of generation of stable species in such networks. Furthermore, isotopic exchange rates, under the condition that each elementary step in the overall reaction sequence forms a unique reactive intermediate that is consumed solely by the subsequent step, can be utilized to determine unidirectional rates and can serve to validate postulated reaction pathways in highly interconnected reaction networks (e.g., CO x hydrogenation).

42 ENGINEERING↗

DOE OSTI2021

Machine learning based rate optimization under geologic uncertainty

We propose a novel approach for rate optimization during a waterflood under geologic uncertainty in reservoir properties such as permeability and porosity. The traditional approach typically involves several runs of the forward simulator. This may not scale well when the optimization is to be performed at the full field-level and over multiple geologic realizations. A machine-learning (ML) based approach which is quick and scalable for rate optimization over multiple geologic realizations is proposed instead. The training data for the model is generated by running the forward simulator with randomly assigned well rates using multiple geologic realizations. A reduced order representation of the permeability heterogeneity in each of the realizations is derived using a grid connectivity transformation (GCT). This step involves finding basis functions corresponding to the different modal frequencies of the grid connectivity represented by the grid Laplacian. The projection of the heterogeneous property field along these basis functions gives the basis coefficients that form the reduced order representation. Subsequently, for each training datapoint, streamlines are traced and the minimum time of flight (TOF) representing the tracer breakthrough time at each producer is recorded. The basis coefficients and well rates are fed to a machine learning model as input and the minimum TOF at the producers forms the output of the model. This trained model can then be used along with an optimizer for computing the optimal injection rates to maximize the injection sweep efficiency. This corresponds to minimizing the variance in the minimum TOF within each well group. Different architectures of neural network are tested using 5-fold cross validation to decide the best ML model to compute the streamline time of flight. The trained model is used to perform well rate optimization over multiple realizations of geology by using a risk tolerance penalty. The optimal well rates thus obtained are compared with two cases: a) equal well rates assigned to all injectors and producers and b) well rates obtained by optimizing over a single realization without considering the uncertainty in geology. The optimal well rates are seen to offer better oil recovery and sweep efficiency than both cases.

02 PETROLEUM↗

DOE OSTI2025

Controlling matric potential in microfluidics to examine microbial dynamics in unsaturated porous media

The use of microfluidics for the study of soil microbial ecology is an emerging field. Most microfluidic studies of biological systems, however, have been performed under fully saturated conditions that are not representative of natural soil. Therefore, while microfluidics offer many unique capabilities that other methodologies cannot, they are not currently suited to address the effects of matric potential, an important variable defining the microbial moisture niche. Here, a methodology is presented that allows the user to control the aqueous conditions within microfluidic networks by manipulating matric potential using a hanging water column. The method relies on hydrophilic surface treatment of the microfluidic device using polyvinyl alcohol (PVA) and incorporating a bed of small pores at the network boundaries, which serve as a porous ceramic plate analogue (PPA). The method was validated on a simple capillary bundle and then on a more complex pore network. A water retention curve, exhibiting hysteresis, was generated for the pore network over a narrow matric potential range of 0 to – 5 kPa. Both the drainage and wetting curves were reproducible, as were the spatial configuration and the number of fragmented moisture niches in the pore network, particularly on the drainage curve. In contrast, the wetting curve exhibited greater variability in spatial configuration due to the “ink bottle effect,” where capillarity was interrupted by wider pore bodies. Ultimately, the methodology provides realistic pore-scale moisture conditions that can be easily manipulated and maintained, enabling new opportunities to explore soil biophysics and microbial biogeography in unsaturated porous media. As a brief example, images showing the localization of fluorescently tagged Pantoea sp. YR343 at −4.3 kPa are presented, highlighting bacterial distributions in water films and air-water interfaces.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS2002

A Lightning Channel Retrieval Algorithm for the North Alabama Lightning Mapping Array (LMA)

A new multi-station VHF time-of-arrival (TOA) antenna network is, at the time of this writing, coming on-line in Northern Alabama. The network, called the Lightning Mapping Array (LMA), employs GPS timing and detects VHF radiation from discrete segments (effectively point emitters) that comprise the channel of lightning strokes within cloud and ground flashes. The network will support on-going ground validation activities of the low Earth orbiting Lightning Imaging Sensor (LIS) satellite developed at NASA Marshall Space Flight Center (MSFC) in Huntsville, Alabama. It will also provide for many interesting and detailed studies of the distribution and evolution of thunderstorms and lightning in the Tennessee Valley, and will offer many interesting comparisons with other meteorological/geophysical wets associated with lightning and thunderstorms. In order to take full advantage of these benefits, it is essential that the LMA channel mapping accuracy (in both space and time) be fully characterized and optimized. In this study, a new revised channel mapping retrieval algorithm is introduced. The algorithm is an extension of earlier work provided in Koshak and Solakiewicz (1996) in the analysis of the NASA Kennedy Space Center (KSC) Lightning Detection and Ranging (LDAR) system. As in the 1996 study, direct algebraic solutions are obtained by inverting a simple linear system of equations, thereby making computer searches through a multi-dimensional parameter domain of a Chi-Squared function unnecessary. However, the new algorithm is developed completely in spherical Earth-centered coordinates (longitude, latitude, altitude), rather than in the (x, y, z) cartesian coordinates employed in the 1996 study. Hence, no mathematical transformations from (x, y, z) into spherical coordinates are required (such transformations involve more numerical error propagation, more computer program coding, and slightly more CPU computing time). The new algorithm also has a more realistic definition of source altitude that accounts for Earth oblateness (this can become important for sources that are hundreds of kilometers away from the network). In addition, the new algorithm is being applied to analyze computer simulated LMA datasets in order to obtain detailed location/time retrieval error maps for sources in and around the LMA network. These maps will provide a more comprehensive analysis of retrieval errors for LMA than the 1996 study did of LDAR retrieval errors. Finally, we note that the new algorithm can be applied to LDAR, and essentially any other multi-station TWA network that depends on direct line-of-site antenna excitation.

Koshak, William↗

DOE OSTI2024

Sorghum SbGhd7 is a major regulator of floral transition and directly represses genes crucial for flowering activation

Molecular genetic understanding of flowering time regulation is crucial for sorghum development. GRAIN NUMBER, PLANT HEIGHT AND HEADING DATE 7 (SbGhd7) is one of the six classical loci conferring photoperiod sensitivity of sorghum flowering. However, its functions remain poorly studied. The molecular functions of SbGhd7 were characterized. The gene regulatory network controlled by SbGhd7 was constructed and validated. The biological roles of SbGhd7 and its major targets were studied. SbGhd7overexpression (OE) completely prevented sorghum flowering. Additionally, we show thatSbGhd7is a major negative regulator of flowering, binding to the promoter motif TGAATG(A/T)(A/T/C) and repressing transcription of the major florigen FLOWERING LOCUS T 10(SbFT10) and floral activators EARLY HEADING DATE(SbEhd1),FLAVIN-BINDING,KELCH REPEAT,F-BOX1(SbFKF1) and EARLY FLOWERING 3(SbELF3). Reinforcing the direct effect ofSbGhd7,SbEhd1OE activated the promoters of three functional florigens (SbFT1,SbFT8andSbFT10), dramatically accelerating flowering. Here our studies demonstrate that SbGhd7 is a major repressor of sorghum flowering by directly and indirectly targeting genes for flowering activation. The mechanism appears ancient. Our study extends the current model of floral transition regulation in sorghum and provides a framework for a comprehensive understanding of sorghum photoperiod response.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Sample-Efficient Adaptive Calibration of Quantum Networks Using Bayesian Optimization

All physical systems employed for quantum information tasks must act as unbiased carriers of encoded quantum states. Ensuring such indistinguishability of information carriers is a major challenge in many quantum information applications, including advanced quantum communication protocols. For photons, the workhorses of quantum communication networks, it is difficult to obtain and maintain their indistinguishability because of environment-induced transformations and loss imparted by communication channels, especially in noisy scenarios. Conventional strategies to mitigate these transformations often require hardware or software overhead that is restrictive (e.g., adding noise), infeasible (e.g., on a satellite), or time-consuming for deployed networks. In this work we propose and develop resource-efficient Bayesian optimization techniques to rapidly and adaptively calibrate the indistinguishability of individual photons for quantum networks using only information derived from their measurement. To experimentally validate our approach, we demonstrate the optimization of Hong-Ou-Mandel interference between two photons-a central task in quantum networking- finding rapid, efficient, and reliable convergence towards maximal photon indistinguishability in the presence of high loss and shot noise. We expect our resource-optimized and experimentally friendly methodology will allow fast and reliable calibration of indistinguishable quanta, a necessary task in distributed quantum computing, communications, and sensing, as well as for fundamental investigations.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

NASA NTRSDate not supplied

Measuring Upwelling Longwave in the Presence of an Obstruction

One of the key measurements from the Clouds and the Earth’s Radiant Energy System (CERES) satellite is Earth emitted or longwave (LW) radiation. The Baseline Surface Radiation Network (BSRN) aims to provide upwelling LW observations of the best possible quality across all their measurement sites. The disestablished CERES Ocean Validation Experiment (COVE), located at Chesapeake Light Station, approximately 25 kilometers east of Virginia Beach, Virginia (coordinates: 36.90N, 75.71W) was a validation site for CERES measurements and part of the BSRN network. One of the measurements at COVE was upwelling LW radiation made with an Eppley pyrgeometer. However, this measurement was complicated due to the Light Station tower being in its field of view. According to our estimates, the Light Station tower altered 15% of the upwelling LW radiation. To resolve this issue, we obtain a different upwelling longwave value using data from an infrared radiation thermometer (IRT), a pyrgeometer that measures downwelling longwave, and meteorological data. Using an IRT allows conversion from sea surface temperature to a water emission value, the downwelling pyrgeometer provides the reflected flux of the downward longwave radiation, and the meteorological data accounts for the air affects between the ocean surface and the upwelling LW measurement height. Comparing the upwelling LW pyrgeometer value with the newly derived value shows the unwanted consequence of the tower. The tower appears to enhance the upwelling LW signal during the summer, most obvious on a summer clear day, but depresses the upwelling signal, even more, during winter sky conditions (both clear and overcast). The tower affects the upwelling LW measurement in these scenarios up to 5% (20 W/m^2) when compared to the newly derived value. BSRN target uncertainty is 2%. Installing a pyrgeometer to measure upwelling LW without obstructions may not be possible at some measurement sties. This issue can be mitigated using other measurements to derive an upwelling LW value.

Bryan Fabbri↗