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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 703 records · Page 39

Reduced global plant respiration due to the acclimation of leaf dark respiration coupled with photosynthesis

Summary Leaf dark respiration ( R d ) acclimates to environmental changes. However, the magnitude, controls and time scales of acclimation remain unclear and are inconsistently treated in ecosystem models. We hypothesized that R d and Rubisco carboxylation capacity ( V cmax ) at 25°C ( R d,25 , V cmax,25 ) are coordinated so that R d,25 variations support V cmax,25 at a level allowing full light use, with V cmax,25 reflecting daytime conditions (for photosynthesis), and R d,25 / V cmax,25 reflecting night‐time conditions (for starch degradation and sucrose export). We tested this hypothesis temporally using a 5‐yr warming experiment, and spatially using an extensive field‐measurement data set. We compared the results to three published alternatives: R d,25 declines linearly with daily average prior temperature; R d at average prior night temperatures tends towards a constant value; and R d,25 / V cmax,25 is constant. Our hypothesis accounted for more variation in observed R d,25 over time ( R 2 = 0.74) and space ( R 2 = 0.68) than the alternatives. Night‐time temperature dominated the seasonal time‐course of R d , with an apparent response time scale of c. 2 wk. V cmax dominated the spatial patterns. Our acclimation hypothesis results in a smaller increase in global R d in response to rising CO 2 and warming than is projected by the two of three alternative hypotheses, and by current models.

Plant Sciences↗

Reliability-Informed Economic and Energy Evaluation for Design for Remanufacturing: A Case Study on a Hydraulic Manifold

Design for Remanufacturing (DfRem) is an attractive approach for sustainable product development. Evaluation of DfRem strategies, from both economic and environmental perspectives, at an early design stage can allow the designers to make informed decisions when choosing the best design option. Studying the long-term implications of a particular design scenario requires quantifying the benefits of remanufacturing for multiple life cycles while considering the reliability of the product. In addition to comparing designs on a one-to-one basis, we find that including reliability provides a different insight into comparing design strategies. We present a reliability-informed cost and energy analysis framework that accounts for product reliability for multiple remanufacturing cycles within a certain warranty policy. The variation of reuse rate over successive remanufacturing cycles is formulated using a branched power-law model which provides probabilistic scenarios of reusing or replacing with new units. To demonstrate the utility of this framework, we use the case study of a hydraulic manifold, which is a component of a transmission used in some agricultural equipment, and use real-world field reliability data to quantify the transmission’s reliability. Three design improvement changes are proposed for the manifold and we quantify the costs and energy consumption associated with each of the design changes for multiple remanufacturing cycles.

design for remanufacturing↗

Bioaerosols are the dominant source of warm-temperature immersion-mode INPs and drive uncertainties in INP predictability

Ice-nucleating particles (INPs) are rare atmospheric aerosols that initiate primary ice formation, but accurately simulating their concentrations and variability in large-scale climate models remains a challenge. Doing so requires both simulating major particle sources and parameterizing their ice nucleation (IN) efficiency. Validating and improving model predictions of INP concentrations requires measuring their concentrations delineated by particle type. We present a method to speciate INP concentrations into contributions from dust, sea spray aerosol (SSA), and bioaerosol. Field campaign data from Bodega Bay, California, showed that bioaerosols were the primary source of INPs between –12° and –20°C, while dust was a minor source and SSA had little impact. We found that recent parameterizations for dust and SSA accurately predicted ambient INP concentrations. However, the model did not skillfully simulate bioaerosol INPs, suggesting a need for further research to identify major factors controlling their emissions and INP efficiency for improved representation in models.

54 ENVIRONMENTAL SCIENCES↗

Comparison of unfolding methods using RooFitUnfold

In this study we describe RooFitUnfold, an extension of the RooFit statistical software package to treat unfolding problems, and which includes most of the unfolding methods that commonly used in particle physics. The package provides a common interface to these algorithms as well as common uniform methods to evaluate their performance in terms of bias, variance and coverage. In this paper we exploit this common interface of RooFitUnfold to compare the performance of unfolding with the Richardson–Lucy, Iterative Dynamically Stabilized, Tikhonov, Gaussian Process, bin-by-bin and inversion methods on several example problems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

ArborX

ArborX library tackles a problem of efficiently finding geometric objects that are close in space. Variations of this problem, such as finding the nearest neighbors of a point, or finding all objects within a certain distance, are inherent components of applications in many fields. The data may be large so that solving the problem efficiently may require significant computational resources, such as multiple processors or accelerators such as general purpose GPUs. ArborX' main advantage in its ability to solve large problems efficiently utilizing a combination of distributed and on-node parallelism. ArborX can be run efficiently on a wide variety of hardware, including GPUs from different vendors, which distinguishes it from other available libraries which typically choose only few of these. The other advantage is that it supports both types of user problems: spatial problems (useful for intersections and finding objects within certain distance), and nearest neighbor problems. ArborX also supports flexible interface in its interaction with a user. Particularly, it allows a user to call user's own function on a positive match, a functionality not rarely available in other libraries. ArborX implements construction and traversal algorithms using efficient tree structures, such as bounding volume hierarchy (BVH). At its core, it uses linear BVH for its low construction cost and sufficient quality. ArborX is written using C++, and is parallelized using the message passing interface (MPI) for the distributed communication, and the Kokkos library for on-node parallelism. This approach allows ArborX to be run on a wide variety of hardware, from common laptops and desktops to supercomputers while using the same codebase. ArborX also implements several advanced algorithms using geometric search, such as density-based clustering algorithm DBSCAN.

ECP↗

ArborX 2.0

ArborX library tackles a problem of efficiently finding geometric objects that are close in space. Variations of this problem, such as finding the nearest neighbors of a point, or finding all objects within a certain distance, are inherent components of applications in many fields. The data may be large so that solving the problem efficiently may require significant computational resources, such as multiple processors or accelerators such as general purpose GPUs. ArborX' main advantage in its ability to solve large problems efficiently utilizing a combination of distributed and on-node parallelism. ArborX can be run efficiently on a wide variety of hardware, including GPUs from different vendors, which distinguishes it from other available libraries which typically choose only few of these. The other advantage is that it supports both types of user problems: spatial problems (useful for intersections and finding objects within certain distance), and nearest neighbor problems. ArborX also supports flexible interface in its interaction with a user. Particularly, it allows a user to call user's own function on a positive match, a functionality not rarely available in other libraries. ArborX implements construction and traversal algorithms using efficient tree structures, such as bounding volume hierarchy (BVH). At its core, ArborX uses linear BVH for its low construction cost and sufficient quality. ArborX implements both spatial and nearest-neighbor traversal algorithms. ArborX also provides several clustering algorithms (minimum spanning tree, DBSCAN, HDBSCAN*), interpolation using minimum least squares and ray tracing. ArborX is written using C++, and is parallelized using the message passing interface (MPI) for the distributed communication, and the Kokkos library for on-node parallelism. This approach allows ArborX to be run on a wide variety of hardware, from common laptops and desktops to supercomputers while using the same codebase.

Prokopenko, Andrey [Oak Ridge National Laboratory ↗

MLEC-Sim: A Simulator for Evaluating Multi-Level Erasure Coding

We present MLEC-Sim, a sophisticated simulator for Multi-Level Erasure Coding (MLEC), developed in approximately 13 KLOC. The simulator is engineered to analyze the impact of various system configurations and erasure coding policies on system durability and network overhead. It supports a comprehensive range of parameters including disk capacity, disk I/O bandwidth, failure rates, network bandwidth, and system scale, accommodating various erasure coding approaches such as Single-Level Erasure Coding (SLEC), Multi-Level Erasure Coding (MLEC), and Local Reconstruction Codes (LRC). MLEC-Sim provides support for multiple chunk placement policies, including clustered parity and declustered parity, and encompasses a variety of repair methods like Repair-ALL, Repair-FCO, Repair-HYB, and Repair-MIN. It is capable of simulating disk failures through a variety of means, including distribution-based or trace-based mechanisms, and can handle complex multi-level (de)clustered placements and repair processes. A key feature of MLEC-Sim is its adoption of the splitting simulation method for evaluating system durabilities at extremely high levels, which are challenging to assess with traditional simulation approaches. This feature allows for a detailed evaluation of system resilience under a range of conditions, aiding in the selection of appropriate erasure coding solutions for enhancing system durability. MLEC-Sim contributes to the field of data storage and reliability by providing a tool for the detailed evaluation of the durability and efficiency of erasure coding configurations, intended for use by researchers and practitioners in the design and optimization of storage systems.

Wang, Meng↗

Development of a dynamical model and energy analysis for wheel loader

The objective of this paper is to develop a fully integrated model for the wheel loader, including the subsystem dynamics of the engine, drivetrain, working circuit, steering circuit, and vehicle. It leads to a high-order strongly nonlinear system, and all state variables are coupled together to form a Multi-Input and Multi-Output (MIMO) system. A control architecture is proposed to decouple the MIMO system into several Single-Input and Single-Output (SISO) systems. Here, a tracking problem has been formulated to validate this fully integrated model with the field test data. The accuracy of the model is verified by the 2.3% difference between the measured and simulated fuel consumption. Meanwhile, an energy distribution analysis is conducted to reveal the energy consumption and energy loss of each portion of the wheel loader. Such a model can be used to plan the working pattern, guide the driving habits of human operators, or refine the underlying architecture, leading to the ultimate goal of reducing total fuel consumption and improving productivity.

42 ENGINEERING↗

Identifying Genomic Islands with Deep Neural Networks

Background Horizontal gene transfer is the main source of adaptability for bacteria, through which genes are obtained from different sources including bacteria, archaea, viruses, and eukaryotes. This process promotes the rapid spread of genetic information across lineages, typically in the form of clusters of genes referred to as genomic islands (GIs). Different types of GIs exist, and are often classified by the content of their cargo genes or their means of integration and mobility. While various computational methods have been devised to detect different types of GIs, no single method is capable of detecting all types. Results We propose a method, which we call Shutter Island, that uses a deep learning model (Inception V3, widely used in computer vision) to detect genomic islands. The intrinsic value of deep learning methods lies in their ability to generalize. Via a technique called transfer learning, the model is pre-trained on a large generic dataset and then re-trained on images that we generate to represent genomic fragments. We demonstrate that this image-based approach generalizes better than the existing tools. Conclusions We used a deep neural network and an image-based approach to detect the most out of the correct GI predictions made by other tools, in addition to making novel GI predictions. The fact that the deep neural network was re-trained on only a limited number of GI datasets and then successfully generalized indicates that this approach could be applied to other problems in the field where data is still lacking or hard to curate.

Computer Vision↗

Biogeochemical Fluxes for Three Bioenergy Crops

Perennial crops have been the focus of bioenergy research and development for their sustainability benefits associated with high soil carbon (C) and reduced nitrogen (N) requirements. However, perennial crops mature over several years and their sustainability benefits can be negated through land reversion. A photoperiod‐sensitive energy sorghum (Sorghum bicolor) may provide an annual crop alternative more ecologically sustainable than maize (Zea mays) that can more easily integrate into crop rotations than perennials, such as miscanthus (Miscanthus × giganteus). This study presents an ecosystem‐scale comparison of C, N, water and energy fluxes from energy sorghum, maize and miscanthus during a typical growing season in the Midwest United States. Gross primary productivity (GPP) was highest for maize during the peak growing season at 21.83 g C m−2 day−1, followed by energy sorghum (17.04 g C m−2 day−1) and miscanthus (15.57 g C m−2 day−1). Maize also had the highest peak growing season evapotranspiration at 5.39 mm day−1, with energy sorghum and miscanthus at 3.81 and 3.61 mm day−1, respectively. Energy sorghum was the most efficient water user (WUE), while maize and miscanthus were comparatively similar (3.04, 1.75 and 1.89 g C mm−1 H2O, respectively). Maize albedo was lower than energy sorghum and miscanthus (0.19, 0.26 and 0.24, respectively), but energy sorghum had a Bowen ratio closer to maize than miscanthus (0.12, 0.13 and 0.21, respectively). Nitrous oxide (N2O) flux was higher from maize and energy sorghum (8.86 and 12.04 kg N ha−1, respectively) compared with miscanthus (0.51 kg N ha−1), indicative of their different agronomic management. These results are an important first look at how energy sorghum compares to maize and miscanthus grown in the Midwest United States. This quantitative assessment is a critical component for calibrating biogeochemical and ecological models used to forecast bioenergy crop growth, productivity and sustainability.

Field Data↗

Microhole drilling technology utilizing a golden section search algorithm

A fundamental issue in microhole drilling is that delivering high weight-on-bit (WOB), high torque rotational horsepower to a conventional drill bit does not scale down to the hole sizes necessary to realize the envisioned cost savings An optimization algorithm called a golden section search (GSS) was used to systematically identify the preferred WOB for a given set of conditions. This research focused on implementing and evaluating two low WOB drilling technologies for microhole drilling: - Laser-assisted mechanical drill, which was tested in the laboratory - Lightly modified commercial off-the-shelf (COTS) percussive hammer, which was tested in a limited field test. Data were collected for microhole GSS using WOB optimization via simulation as well as at the Blue Canyon Dome Site in Socorro, NM. Information on the attached files and folders are as follows: - the .tdms files are LabView data files, which can be opened within Excel using a .tdms add-in or using a Matlab .tdms converter - the .tdms_index files are part of the .tdms file structure - sampling rate, column headers, and length data within the .tdms files follow SOP when utilizing Excel and/or Matlab as described above

15 GEOTHERMAL ENERGY↗

Surface water geochemistry along St. Louis River Estuary (Duluth/Superior, MN/WI)

This dataset is aimed at understanding changes in surface water chemistry associated with urbanization in the Great Lakes region. Surface water chemistry including cations, anions, organic and inorganic carbon, and nitrogen were collected from six locations along St. Louis River – a freshwater estuary entering Lake Superior (Duluth/Superior, MN/WI). The Duluth/Superior, MN/WI metropolitan area is the largest port on the United States side of Lake Superior. Samples were collected near different land uses every two weeks from late July 2023 to the onset of ice cover in November 2023. Water samples were analyzed using In-Situ AquaTroll 500 Multiparameter Sonde with Ammonium Ion Selective Electrode and Chlorophyll-a sensor (unfiltered), METTLER TOLEDO FiveEasy Plus FP20 and METTLER TOLEDO LE407 probe (unfiltered); HACH DR300 Pocket Colorimeter Iron FerroVer (filtered 0.22 μm in field); Shimadzu TOC-L Total Organic Carbon Analyzer with TNM-L Total Nitrogen Unit (filtered 0.22 μm in field); Agilent 8900 triple quadrupole ICP-MS (ICP-QQQ) (filtered 0.22 μm in field); and Dionex ICS-6000 HPIC System (filtered 0.22 μm in field).The data package is comprised of 5 files. dd.csv contains the description of columns in Geochemistry_LSNERR_water.csv and Sampling_sites.csv. flmd.csv contains descriptions of each file in the dataset. README.txt contains description of the dataset structure and file content. Geochemistry_LSNERR_water.csv contains geochemistry data for six sampling locations along the St. Louis River. Sampling_sites.csv contains latitude and longitude coordinates for each of the six sampling site locations along the St. Louis River.This data has not been previously published.

54 ENVIRONMENTAL SCIENCES↗

First Ever Polymer Flood Field Pilot to Enhance the Recovery of Heavy Oils on Alaska North Slope – Producer Responses and Operational Lessons Learned

The US Department of Energy and Hilcorp Alaska, LLC are jointly cosponsoring a field pilot project entitled “First Ever Field Pilot on Alaska’s North Slope to Validate the Use of Polymer Floods for Heavy Oil Enhanced Oil Recovery (EOR).” The objective of this pilot is to perform a field experiment to validate the use of an advanced polymer flooding technology to unlock the vast heavy oil resources on Alaska North Slope (ANS). Two pairs of horizontal injection and production wells have been deployed in an isolated fault block of the Schrader Bluff heavy oil reservoir at the Milne Point Field to conduct a polymer flood pilot which was designed to acquire field performance data to optimize polymer flood design in the Schrader Bluff heavy oil reservoirs on ANS. Hydrolyzed polyacrylamide (HPAM) polymer injection started on August 28, 2018 using a custom made polymer mixing and pumping unit. Polymer solution properties such as concentration, viscosity, and filter ratio, have been closely monitored and adjusted as necessary. Operational procedures have been improved to ensure adequate injectivity and polymer propagation through the formation. Oil and water production is tested frequently to monitor water cut performance, and produced water is sampled and analyzed for polymer content. Tracers were pumped pre and post polymer injection startup to compare polymer flood breakthrough timing and sweep efficiency. Polymer injectivity of the horizontal wells drilled in the Schrader Bluff NB sand is found to be sufficient to replace the reservoir production voidage although there were some declines as high viscosity polymer swept the near wellbore region. Production data show significant reduction in water cut and the oil production rate has stabilized. No polymer production has been confirmed from the two horizontal producers after 22 months of polymer injection into the two supporting horizontal injectors. Tracer data show very low sweep efficiencies with waterflood alone, whereas significant improvement has been achieved with polymer flood. Many operational lessons have been learned and improvements have been made regarding polymer mixing, pumping, and onsite quality control, particularly in a challenging Arctic environment. Adequate polymer injection rate can be achieved with diligent monitoring and quality assurance of the properties of the injected polymer solution.

Ning, Samson↗

Oak Ridge Response to Versatile Test Reactor Environmental Impact Statement Data Request

The Versatile Test Reactor (VTR) is a fast-spectrum test reactor being developed in the United States under the direction of the US Department of Energy Office of Nuclear Energy (DOE-NE). The VTR mission is to enable accelerated testing of advanced reactor fuels and materials required for advanced reactor technologies. The conceptual design of the 300 MWth sodium-cooled metallic-fueled pool-type fast reactor has been led by the US National Laboratories in collaboration with General Electric–Hitachi and Bechtel National, Inc. In support of the VTR project, DOE issued a Notice of Intent (NOI) in the Federal Register on August 5, 2019, announcing the intent to prepare an Environmental Impact Statement (EIS) in accordance with the National Environmental Policy Act (NEPA) and its implementing regulations. The EIS will evaluate alternatives for a versatile reactor–based fast-neutron source facility and associated facilities for the preparation, irradiation, and post-irradiation examination (PIE) of test/experimental fuels and materials. Specifically, the NOI identified two siting alternatives for the VTR reactor facility: Idaho National Laboratory (INL) or Oak Ridge National Laboratory (ORNL). In addition, the NOI also specified two siting alternatives for VTR fuel fabrication: INL and the Savannah River Site (SRS). This report provides information in response to data requests made to ORNL to fill in site-specific knowledge gaps to develop a high-quality EIS. The responses provided are not required to provide full details in every aspect; instead, they adequately bound possible environmental impacts or provide sufficient information to adequately assess likely environmental impacts. This work is being performed under a subcontract from INL to ORNL using DOE-NE funds and is directed by DOE-NE and DOE-ID. Leidos has been contracted by DOE-NE to write the VTR EIS, so most data requests have come from Leidos but were often routed through INL or DOE-ID. DOE-ID is overseeing the NEPA and EIS processes for the VTR project. Leidos will use the information provided in this report to inform the VTR EIS and will also cite this document to establish a clear, publicly available source of the information. Section 2 of this report briefly describes the proposed ORNL VTR Alternative and illustrates the location of the proposed site for the ORNL VTR Alternative. Sections 3 through 7 provide direct responses to data requests received by ORNL. These sections use a tabular format in which data requests are divided into separate items to be addressed; the items are numbered, the data requests are restated with more topical information included, and then the responses are provided. Initial data requests and follow-on requests for additional information (RAIs) are combined under the original data request fields. Finally, Section 8 presents summarized conclusions and describes future work.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

A Closed-Loop Distribution System Restoration Tool for Natural Disaster Recovery. Final CRADA report

We propose to continue the development of the restoration algorithms and the tool’s user interface, both of which have been developed under the GMLC-0131 project. This project aims to develop a distribution restoration decision support tool that will assist utilities in performing distribution restoration after extreme weather events in an optimal and efficient manner. The tool will integrate the weather information/forecasts and system fragility assessment together with the field measurement data to improve the situational awareness and estimate the system damage status. Advanced optimization models will be leveraged to dispatch repair crews and associated resources. New resources (e.g., automatic switches and distributed generators (DGs)) enabled by distribution automation and smart grid development will be utilized to reconfigure distribution grids and pick up loads promptly to reduce the outage sizes and durations. The closed-loop feature of the tool will make the tool adaptive to the evolving weather events and varying restoration capabilities. In this CRADA, we will collaborate with S&C Electric Company (S&C) to refine ANL-1060 (07/17/2019) the restoration algorithms that can be potentially applicable for any utility systems and vendor products, including: 1) Customizable information from both utility users and vendor users; 2) User interface design.

54 ENVIRONMENTAL SCIENCES↗

Assessing the Consistency of Estimated Ground Cover Fractions between the BLM AIM Method and Optical Remote Sensing Method

Since 2012, Argonne National Laboratory (Argonne) has supported the Bureau of Land Management (BLM) in developing remote sensing methodologies for long-term environmental monitoring of Palo Verde Mesa in eastern Riverside County, California, including methods for: detailed mapping of ephemeral streams, estimating fractional cover of desert-land surface components (e.g., trees, shrubs, litters, and bare ground), evaluating erosion risk or land stability, and characterizing vegetation alliances using spatial structure and geostatistical approaches. These studies showed the promise of remote sensing for monitoring changes in desert landscapes by providing information that would be difficult to obtain through field surveys. During this time the BLM has also worked to establish long-term monitoring protocols and compiled field-observation data collected using standardized protocols from the Assessment, Inventory, and Monitoring (AIM) strategy. The AIM data can be compared to data derived from remote sensing methods to evaluate their relative operational utility in monitoring landscape change. If ground cover estimated using remotely sensed imagery is comparable to AIM ground cover estimates, then remote sensing can be used to monitor whether any land cover change in desert landscapes may be related to solar energy development. Therefore, the goal of this study was to determine the consistency in ground cover estimates between AIM data and those derived from publicly- available remotely sensed imagery, such as that available through the U.S. Department of Agriculture, National Agricultural Imagery Program (NAIP), to examine feasibility of a remote sensing method for complementing AIM monitoring. Based on the image analysis in this study, we also provide recommendations for how small unmanned aerial system (sUAS) data may be used to complement BLM’s AIM data and NAIP imagery for future vegetation monitoring. The ground cover types we originally planned to investigate were trees, shrubs, and bare ground. However, the small sample size and a limited range of cover fraction of trees and shrubs in the AIM dataset (e.g., 33 samples with a maximum shrub cover of 18%, 14 samples with a maximum tree cover of 17%) did not allow for performing a meaningful evaluation for the remote sensing approach. Therefore, we conducted the study focusing on bare ground, foliar, and rock cover, all of which are indicators reported in the AIM remote sensing dataset.

47 OTHER INSTRUMENTATION↗

Real Time - Optimal Power Flow Based Distributed Energy Resources Management System (DERMS) (CRADA Number CRD-20-16909 Final Report)

The integration of behind-the-meter distributed energy resources (DERs) into distribution systems brings transformative changes to power systems. This requires operators and planners to find solutions to modernize electric grids and to effectively manage DERs for grid services. NREL developed novel DER management algorithms (referred to as Real-Time Optimal Power Flow, RT-OPF) through U.S. Department of Energy (DOE)-funded efforts, including Advanced Research Projects Agency–Energy (ARPA-E) Network Optimized Distributed Energy Systems (NODES) funding. This cutting-edge control technology aims to modernize distribution systems with large amounts of DER integration, which will help utilities solve issues brought by renewable integration and build resilient and renewable-based electric grids nationwide. Utilidata worked with NREL to investigate the commercialization opportunity of this RT-OPF-based distributed energy resource management system (DERMS). In this project, NREL performs the technology transfer of the RT-OPF to Utilidata to help them fully understand the RT-OPF solution, to identify potential engineering hurdles, and to assess the expected commercial value of various RT-OPF use cases and deployment. The technology transfer work includes two major tasks. First, NREL performs an in-depth knowledge transfer of the entire RT-OPF solution to Utilidata to help them gain an extensive and detailed understanding of the complete RT-OPF solution. In this task, NREL provides exhaustive information (e.g., documentation, code packages, laboratory and field trial data, performance results) while conducting in-depth training sessions to provide a thorough explanation of the entire solution. NREL hosts meetings to present different topics related to the RT-OPF solution, and question-and-answer sessions are included in each meeting to better explain the RT-OPF-related work. Second, the RT-OPF simulations are performed in a laboratory environment. The main objectives of this task are to walk through with Utilidata engineers how to set up a simulation of RT-OPF, identifying each RT-OPF code block/component in operation, learning how these components interact with each other, and eventually running RT-OPF simulations under various system conditions. This task helps Utilidata engineers understand performance limitations and constraints while also quantifying the commercial value of the RT-OPF for different use cases. Based on these two tasks, Utilidata engineers should be able to define and prioritize the next steps of RT-OPF implementation with an eye toward commercial success and scalability of the solution. The next steps are expected to be part of a new project following the conclusion of this project.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Weather impacts on solar PV operations summary of the current body of knowledge and implications for further investigation

There is growing concern that severe weather events are negatively affecting solar photovoltaic (PV) systems and pose ongoing and unrecognized risks. Clearly research is needed to quantify and characterize the risks so that properly calibrated improvements can be implemented. To begin this process, this report is a collection of information of severe weather impacts on solar PV available today taken from research, insurance data, and field inspections. While it is not comprehensive enough to draw conclusions, this information provides a baseline for action and indicates an urgent need to investigate further.

14 SOLAR ENERGY↗