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At least 145 records · Page 8

Scale-up of Novel Low-Cost Carbon Fibers Leading to High-Volume Commercial Launch

The project started in September, 2012 with the goal of scaling up from the existing laboratory scale process for producing carbon fiber (CF) from polyolefin (PO) based precursor fiber using a Dow proprietary sulfonation-desulfonation stabilization process. The award was used to develop a process that was capable of producing market development quantities of CF from PO precursor fiber at a rate of 4 kg/h of CF. The CF would target properties that met or exceeded the Department of Energy (DOE) Vehicles Technology [1] standard; i.e., 172 GPa modulus and 1.72 GPa strength at greater than or equal to 1% strain. The Dow proprietary process was capable of meeting and exceeding these targets properties. Project DE-EE0005760 resulted from a Collaborative Research and Development Agreement (CRADA) between Dow and Oak Ridge National Laboratory (ORNL) with support from the Michigan Economic Development Corporation (MEDC) and DOE. In the first budget period, the main goal was to design a sulfonation-desulfonation market development plant capable of stabilizing PO precursor fiber at a rate of 5 kg/h using a sulfonation solution. The detailed design, location, and cost estimate were determined as scheduled in the Project Management Plan (PMP). In parallel with this DOE award project was a fundamentals and economic evaluation funded by The Dow Chemical Company (Dow). The goal of the Dow sponsored project was to finalize the mass balances, energy balances, and levelized cost to produce CF using the Dow process. A Go-No-Go decision was scheduled in June, 2013 based on the findings of the DOE sponsored scale up project and the Dow sponsored project. In June, 2013, Dow made the No-Go decision to halt and abandon the Dow proprietary sulfonation-desulfonation process for stabilizing PO precursor fibers for the manufacturing of CF. This No-Go decision was identified in the original proposal and at the start of this project, and the decision was made as scheduled. The decision was based on the high levelized economic cost of the process relative to the manufacture of CF from polyacrylonitrile (PAN) precursor fibers. The capital required to sulfonate the fibers adds a significant cost to the process due to the need for investment in a sulfuric acid recovery plant. This high additional capital over the capital for a PAN based CF plant, reduces the levelized economic cost to slightly advantaged over PAN based CF. The sulfonation-desulfonation stabilization route failed to meet the Dow’s return on investment criterion and the cost advantage target set forth for the DOE project. The DOE and Dow decided to halt spending on the project until a new PO fiber stabilization process could be identified that met the DOE physical properties standard and the levelized economic cost constraints of Dow. When the new technology was developed, then award DE-EE0005760 would be re-started with the same goals of the development of a market development plant capable of producing CF at 4 kg/h with the properties that met or exceed those set forth by the Department of Energy Vehicles Technology standard. Progress on the development of the new process has been slow and thus has delayed the scale up project. Dow’s efforts to date have not progressed to the point of demonstrating a commercially-viable process for production of low cost CF from PO precursors for Dow’s rigorous economic constraints. After extensive discussions within Dow and consultation with DOE’s Advanced Manufacturing Office (AMO) Headquarters and Golden Field Office teams, Dow has decided to proceed with the formal recommendation to terminate subject project. DOE’s AMO Headquarters and Golden Field Office teams agreed with the termination of the project.

36 MATERIALS SCIENCE↗

Strategic Stability in South Asia: An Indian?s Perspective.

The security environment in South Asia has been marked by instability for several decades. The foremost causes of regional instability are the nuclear weapons-cum-missile development program of China, North Korea and Pakistan, the strident march of Islamist fundamentalism, the diabolical nexus between narcotics trafficking and terrorism, the proliferation of small arms and the instability inherent in the rule of despotic regimes. Instability on the Indian sub-continent is manifested, first and foremost, in the continuing conflict in Afghanistan, its tense relations with Iran and the Central Asian Republics (CARs); Pakistan’s struggle against the Taliban, the emerging fissiparous tendencies in Balochistan and Pakhtoonkhwa, the rise of Jihadi Islam and what some fear is Pakistan’s gradual slide towards becoming a ‘failed state’ despite some economic gains in the last five years. Also symptomatic of an unstable and uncertain security environment in the South Asian region are what some see as Sri Lanka’s inability to find a lasting solution to its internal challenges; the potential for Bangladesh’s gradual emergence as the new hub of Islamist fundamentalist terrorism and its struggle for economic upliftment to subsistence levels; the continuing negative impact of Maoist insurgency on Nepal’s fledgling democracy; the simmering discontent in Tibet and Xinjiang and what some see as a low-key uprising against China’s regime; and, the Myanmar peoples’ nascent movement for democracy. In all these countries, socio-economic development has been slow and, consequently, per capita income is alarmingly low. Transborder narcotics trafficking – the golden triangle lies to the east of South Asia and the golden crescent to its west – and the proliferation of small arms, make a potent cocktail. Ethnic tensions and fairly widespread radicalization, worsened by the advent of the vicious ideology of the Islamic state, add further to regional instability.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

A Heterogeneous System for Eagle Detection, Deterrent, and Wildlife Collision Detection for Wind Turbines (Final Technical Report)

This report summarizes the design, implementation, and test of an integrated system for automated detection and deterrence of eagles, with included wind turbine blade strike detection and imaging functionality. A machine learning approach was used in conjunction with a 360° camera system for automated detection and classification of golden eagles. This was developed using footage obtained from trained golden eagles and other raptors, in collaboration with wildlife biologists and professional bird handlers. Oregon State University developed a visual deterrent system, which uses inflatable anthropomorphic sculptures with random, kinetic motion to deter eagles, and conducted limited field testing on live eagles; the deterrent can be triggered by the visual detection of eagles using the vision system. Finally, a multi-sensor module was developed that is mounted at the turbine blade root. This module measures vibration and other motions to detect blade strikes, and an integrated on-blade camera captures an image of any impacting objects. Long-term, this blade strike detection system is intended to support an automatic monitoring and certification system for the eagle detection and deterent system. Independent field testing of each system component is described. Testing of the integrated system on an operational wind turbine was conducted across three separate field tests. This includes multi-day fields tests on a General Electric 1.5MW wind turbine at the National Renewable Energy Laboratory (NREL) National Wind Technology Center (NWTC) in Boulder, CO in October 2018 and July 2019; installation procedures, test procedures, and a summary of collected data are presented. A third multi-day on-turbine field test is also presented, which was performed using a General Electric 1.5MW wind turbine at the North American Wind Research and Training Center (NAWRTC) at Mesalands Community College, Tucumcari, NM in April 2019. Across these field tests, the vision system was demonstrated using unmanned aerial vehicles (UAV), and the eagle classification algorithm was not tested; the visual deterrent system was demonstrated, including automatic, remote deployment following surrogate visual detections; and, multi-sensor on-blade data was recorded across multiple wind turbine operational conditions and through more than 100 surrogate blade strikes using soft projectiles, including the successful demonstration of automatic image capture of striking objects. This data set was also used for offline development and validation of enhanced collision detection algorithms. As summarized in this report, the development and field validation of an integrated detection, deterrent, and blade collision detection system represents a critical proof of concept for future technology development of related detection and deterrent technologies, where both deterrent as well as collision detection recording devices are needed for future siting, monitoring, and operation of wind turbine installations, both onshore and offshore.

17 WIND ENERGY↗

KamLAND SENSITIVITY TO NEUTRINOS FROM PRE-SUPERNOVA STARS

In the late stages of nuclear burning for massive stars (M > 8 M{sub ⊙}), the production of neutrino–antineutrino pairs through various processes becomes the dominant stellar cooling mechanism. As the star evolves, the energy of these neutrinos increases and in the days preceding the supernova a significant fraction of emitted electron anti-neutrinos exceeds the energy threshold for inverse beta decay on free hydrogen. This is the golden channel for liquid scintillator detectors because the coincidence signature allows for significant reductions in background signals. We find that the kiloton-scale liquid scintillator detector KamLAND can detect these pre-supernova neutrinos from a star with a mass of 25 M{sub ⊙} at a distance less than 690 pc with 3σ significance before the supernova. This limit is dependent on the neutrino mass ordering and background levels. KamLAND takes data continuously and can provide a supernova alert to the community.

79 ASTRONOMY AND ASTROPHYSICS↗

Investigation of Correlation between Field Performance and Indoor Acceleration Measurements of Potential Induced Degradation (PID) for c-Si PV Modules

The correlation between outdoor field testing and indoor chamber measurement for potential-induced degradation in crystalline silicon PV modules is unclear. The motivation of this work is to build up a direct comparison and investigate the correlation between indoor and outdoor performance. First of all, four PID indoor tests were defined from basic to premium, based on the difficulty of the test. Six groups of modules were designed and fabricated in Trina Solar, with different grades of PID resistance from weak to strong. The outdoor field test systems were built in three different climates: tropical, subtropical, and semi-arid climates in Singapore, Changzhou (China) and Golden (CO, USA) respectively, in a collaborative testing campaign involving Trina, SERIS and NREL. The system in Golden has been on-sun for more than 13 months where <4% power loss which includes PID and other reliability losses was detected and power loss of <2% is shown for all six groups of modules after 21 weeks in the field in the subtropical climate in Changzhou. However, PID of 23% was observed after 18 weeks in Singapore for the most PID-susceptible module, while the other PID module types showed degradation of only less than 5%.

14 SOLAR ENERGY↗

BENEFIT with Northeastern University: HVAC Hardware-in-the-Loop Experimental Testing of a Heat Pump and Air Conditioner

This dataset includes HVAC Hardware-in-the-Loop (HIL) experimental results for a single stage, SEER 16, HSPF 9.5, 3-ton single-speed air source heat pump with 15 kW of backup auxiliary heating tested in both cooling and heating mode, and a two stage, SEER 21, 2-ton central air conditioner tested in cooling mode for a set of outdoor temperatures and indoor setpoint temperatures. In addition to these tests, experimental tests focused on the operation of auxiliary heating for the heat pump for winter condition were also conducted. The laboratory experiments for transient testing of the heat pump and air conditioner were conducted using the two HIL systems in the Systems Performance Laboratory (SPL) at NREL’s Energy Systems Integration Facility (ESIF). Further information on laboratory design and capabilities of the SPL along with the architecture of HVAC HIL system can be found in: Sparn, B. F. 2018. Laboratory Resources and Techniques to Evaluate Smart Home Technology (No. NREL/CP-5500-71696). National Renewable Energy Laboratory (NREL), Golden, CO (United States). https://www.nrel.gov/docs/fy18osti/71696.pdf and the experimental setup and validation of HVAC HIL platform can be found in: Ramaraj, S. and Sparn, B. 2022. Validation of HVAC Hardware-In-the-Loop Simulation for Advanced Control Strategies in Smart Homes (No. NREL/CP-5500-82562). National Renewable Energy Lab (NREL), Golden, CO (United States). https://www.nrel.gov/docs/fy22osti/82562.pdf. These experimental results can be used to validate how we currently model the cycling behavior of heat pumps and air conditioners. Additionally, many demand response programs implement heat pump and air conditioner control by changing the thermostat set point – these data may also be used to verify our models for heat pump and air conditioner demand response control are implemented correctly. The Test_Matrix file describes all the indoor and outdoor test conditions for heat pump and air conditioner and the file names of data sets include information about the test conditions. A wide range of outdoor air temperatures were chosen to accommodate summer and winter conditions. In addition to operating the HVAC equipment with different outdoor temperatures, we also operate the system with different indoor temperature set points to represent different grid signals or different operating conditions. For cooling conditions, the baseline set point is 72°F. To represent Load Up signals, the setpoint is changed to 68°F. The Load Shed set point is 76°F. For heating conditions, the baseline set point was assumed to be 68°F. The Load add set point is 72°F and the Load shed set point is 64°F. The starting indoor temperature for cooling conditions was set ~2°F above the indoor setpoint temperature so that the equipment turned on quickly. Similarly, the initial indoor temperature was set ~2°F lower than setpoint for heating mode tests to ensure that heating began quickly. The return air temperature was assumed to be equal to the indoor setpoint temperature in all cases. The experimental data are sampled at 1-second intervals. The data from ecobee thermostat at 5-minute interval are resampled and added to the corresponding file. The content of each data set is as follows: • T_Return (C): Measured return air temperature [C] • T_Return_SP (C): Return air temperature setpoint from E+ model, sent to HIL [C] • T_Supply (C): Measured supply air temperature at evaporator outlet [C] • T_Outdoor (C): Measured outdoor air temperature [C] • T_Outdoor_SP (C): Outdoor air temperature setpoint from weather file, sent to HIL [C] • T_Indoor (C): Measured indoor air temperature [C] • T_Indoor_SP (C): Indoor air temperature setpoint from E+ model, sent to HIL [C] • Outdoor Unit Power (W): Measured power of the outdoor unit [W] • Indoor Unit Power (W): Measured power of the indoor unit [W] • Evaporator Airflow Rate (CFM): Measured evaporator or indoor unit airflow rate sent to E+ model [CFM] • Cooling/Heating Capacity (kW): Calculated cooling/heating capacity sent to E+ model [kW] • T_SP_Thermostat (C): Thermostat cooling/heating setpoint temperature [C] • T_Indoor_Thermostat (C): Thermostat indoor air temperature [C]

24 POWER TRANSMISSION AND DISTRIBUTION↗

County Electric Vehicle Home Charging Access Shares from the 2030 National Charging Network Study

This file contains modeled county-level home electric vehicle (EV) charging access shares from the study, "The 2030 National Charging Network: Estimating U.S. Light-Duty Demand for Electric Vehicle Charging Infrastructure" by Wood et al. (2023). These are based on modeling in "There's No Place Like Home: Residential Parking, Electrical Access, and Implications for the Future of Electric Vehicle Charging Infrastructure" by Ge et al. (2021). Wood, Eric, et al. 2023. The 2030 National Charging Network: Estimating U.S. Light-Duty Demand for Electric Vehicle Charging Infrastructure. Golden, CO: National Renewable Energy Laboratory. NREP/TP-5400-85654. https://www.nlr.gov/docs/fy23osti/85654.pdf . Ge, Yanbo, et al. 2021. There's No Place Like Home: Residential Parking, Electrical Access, and Implications for the Future of Electric Vehicle Charging Infrastructure. Golden, CO: National Renewable Energy Laboratory. NREL/TP-5400-81065. https://www.nlr.gov/docs/fy22osti/81065.pdf .

24 POWER TRANSMISSION AND DISTRIBUTION↗

Semiclassical theory of unimolecular dissociation induced by a laser field

A semiclassical nonperturbative theory of direct photodissociation in a laser field is developed in which photon absorption and dissociation are treated in a unified fashion. This is achieved by visualizing nuclear dynamics as a representative particle moving on electronic-field surfaces. Methods are described for calculating dissociation rates and probabilities by Monte Carlo selection of initial conditions and integration of classical trajectories on these surfaces. This unified theory reduces to the golden rule expression in the weak-field and short-time limits, and predicts nonlinear behavior, i.e., breakdown of the golden rule expression in intense fields. Field strengths above which lowest-order perturbation theory fails to work have been estimated for some systems. Useful physical insights provided by the electronic-field representation have been illustrated. Intense field effects are discussed which are amenable to experimental observation. The semiclassical methods used here are also applicable to multiple-surface dynamics in fieldfree unimolecular and bimolecular reactions.

Yuan, J.-M.↗

Interpretation of an index of phytoplankton population composition calculated from Remote Airborne Fluorsensor (RAF) data

The calculation of indices of phytoplankton population composition from chlorophyll a fluorescence at 685 nm excited by narrow band light at 454 and 539 nm is discussed. The ratio of the fluorescence excited by light of these two wavelengths is a function of the distribution of the phytoplankton between two color groups, designated the golden-brown and the green. The golden-brown group consists of those species which have the highly photosynthetically active carotenoid-chlorophyll-a-protein complexes, i.e. members of the classes Bacillariophyceae, diatoms Dinophyceae, dinoflagellates, and some members of the class Prymnesiophyceae. The green color group consists those species of phytoplankton which apparently lack those complexes, i.e. members of the classes Chlorophyceae, Euglenophyceae, Prasinophyceae, Eustigmatophyceae, Xanthophyceae, and a few members of the Prymnesiophyceae. A few species of phytoplankton appear to have intermediate characteristics, and would apparently belong to neither group. Most of these species are members of the class Cryptophyceae. The composition index for this class is examined in detail.

Farmer, F. H.↗

Succinate dehydrogenase activity and soma size of motoneurons innervating different portions of the rat tibialis anterior

The spatial distribution, soma size and oxidative enzyme activity of gamma and alpha motoneurons innervating muscle fibres in the deep (away from the surface of the muscle) and superficial (close to the surface of the muscle) portions of the tibialis anterior in normal rats were determined. The deep portion had a higher percentage of high oxidative fibres than the superficial portion of the muscle. Motoneurons were labelled by retrograde neuronal transport of fluorescent tracers: Fast Blue and Nuclear Yellow were injected into the deep portion and Nuclear Yellow into the superficial portion of the muscle. Therefore, motoneurons innervating the deep portion were identified by both a blue fluorescent cytoplasm and a golden-yellow fluorescent nucleus, while motoneurons innervating the superficial portion were identified by only a golden-yellow fluorescent nucleus. After staining for succinate dehydrogenase activity on the same section used for the identification of the motoneurons, soma size and succinate dehydrogenase activity of the motoneurons were measured. The gamma and alpha motoneurons innervating both the deep and superficial portions were located primarily at L4 and were intermingled within the same region of the dorsolateral portion of the ventral horn in the spinal cord. Mean soma size was similar for either gamma or alpha motoneurons in the two portions of the muscle. The alpha motoneurons innervating the superficial portion had a lower mean succinate dehydrogenase activity than those innervating the deep portion of the muscle. An inverse relationship between soma size and succinate dehydrogenase activity of alpha, but not gamma, motoneurons innervating both the deep and superficial portions was observed. Based on three-dimensional reconstructions within the spinal cord, there were no apparent differences in the spatial distribution of the motoneurons, either gamma or alpha, associated with the deep and superficial compartments of the muscle. The data provide evidence for an interdependence in the oxidative capacity between a motoneuron and its target muscle fibres in two subpopulations of motoneurons from the same motor pool, i.e. the same muscle.

NASA Discipline Musculoskeletal↗

Solving A Corrosion Problem

The corrosion problem, it turned out, stemmed from the process called electrolysis. When two different metals are in contact, an electrical potential is set up between them; when the metals are surrounded by an electrolyte, or a conducting medium, the resulting reaction causes corrosion, often very rapid corrosion. In this case the different metals were the copper grounding system and the ferry's aluminum hull; the dockside salt water in which the hull was resting served as the electrolyte. After identifying the source of the trouble, the Ames engineer provided a solution: a new wire-and-rod grounding system made of aluminum like the ferry's hull so there would no longer be dissimilar metals in contact. Ames research on the matter disclosed that the problem was not unique to the Golden Gate ferries. It is being experienced by many pleasure boat operators who are probably as puzzled about it as was the Golden Gate Transit Authority.

Source record↗

j5 v2.8.4

j5 automates and optimizes the design of the molecular biological process of cloning/constructing DNA. j5 enables users to benefit from (combinatorial) multi-part scar-less SLIC, Gibson, CPEC, Golden Gate assembly, or variants thereof, for which automation software does not currently exist, without the intense labor currently associated with the process. j5 inputs a list of the DNA sequences to be assembled, along with a Genbank, FASTA, jbei-seq, or SBOL v1.1 format sequence file for each DNA source. Given the list of DNA sequences to be assembled, j5 first determines the cost-minimizing assembly strategy for each part (direct synthesis, PCR/SOE, or oligo-embedding), designs DNA oligos with Primer3, adds flanking homology sequences (SLIC, Gibson, and CPEC; optimized with Primer3 for CPEC) or optimized overhang sequences (Golden Gate) to the oligos and direct synthesis pieces, and utilizes BLAST to check against oligo mis-priming and assembly piece incompatibility events. After identifying DNA oligos that are already contained within a local collection for reuse, the program estimates the total cost of direct synthesis and new oligos to be ordered. In the instance that j5 identifies putative assembly piece incompatibilities (multiple pieces with high flanking sequence homology), the program suggests hierarchical subassemblies where possible. The program outputs a comma-separated value (CSV) file, viewable via Excel or other spreadsheet software, that contains assembly design information (such as the PCR/SOE reactions to perform, their anticipated sizes and sequences, etc.) as well as a properly annotated genbank file containing the sequence resulting from the assembly, and appends the local oligo library with the oligos to be ordered j5 condenses multiple independent assembly projects into 96-well format for high-throughput liquid-handling robotics platforms, and generates configuration files for the PR-PR biology-friendly robot programming language. j5 thus provides a new way to design DNA assembly procedures much more productively and efficiently, not only in terms of time, but also in terms of cost. To a large extent, however, j5 does not allow people to do something that could not be done before by hand given enough time and effort. An exception to this is that, since the very act of using j5 to design the DNA assembly process standardizes the experimental details and workflow, j5 enables a single person to concurrently perform the independent DNA construction tasks of an entire group of researchers. Currently, this is not readily possible, since separate researchers employ disparate design strategies and workflows, and furthermore, their designs and workflows are very infrequently fully captured in an electronic format which is conducive to automation.

Hillson, Nathan↗

Process Control Plan to Monitor Acceptable Levels of Flux and other residues

IPC J-STD –001G, Amendment 1 requires that the assembler have a sampling plan to assure that the process remains in control once qualified and validated. It is well documented that electrochemical failures occur at component sites where flux residues are not fully activated. It is also well known that specific components have a higher risk of electrochemical failure. Selecting a control plan that monitors the process and its performance on challenging components provides assurance that the process maintains control once established during process qualification. The test board used to qualify the process establishes an upper and lower spec limit for each of the component types on the test board. Surface Insulation Resistance upper and lower control limits, using challenging components that are representative of production hardware, represent a golden process condition. The golden image is a measure of process deviations that represents the performance of a resistance curve within a specific period. The objective is to judge whether the process in or out of control.

42 ENGINEERING↗

Mesoscale Modeling to Characterize Eagle Soaring Habitat

Uncovering drivers of risk is crucial to understanding interactions between wildlife and wind turbines, and identifying options for impact minimization. These drivers tie to co-variates linked to behavior and movement patterns that allow us to estimate locations and periods of risk. For volant species, atmospheric flow can have significant influence on flight patterns. For obligate soaring birds, like golden eagles, updraft velocities can inform where eagles are likely to travel, at what altitude, and where conditions are not likely sufficient to sustain soaring flight. This has been an active area of study in recent years, using relatively coarse atmospheric data generally at the 20km x 20km scale or larger. Leveraging a 20-year dataset from the Weather Research and Forecasting Model (WRF) (https://www.mmm.ucar.edu/weather-research-and-forecasting-model), we are quantifying vertical velocities across the continental United States at a 2km x 2km resolution. Wind resource data sets originally were static maps showing the mean annual wind speed over an area. However, for these data sets to be optimally used for various applications they must be high-resolution time series, seamlessly span large geographic contexts, and account for uncertainty in wind speed. The National Renewable Energy Laboratory is producing public available datasets that meet these criteria and will be bias corrected to yield the most accurate wind resource data. This effort is an augment to the current WIND Toolkit which houses a high resolution data set. In the new iteration of the WIND Toolkit, a 20-year dataset will be used to improve the accuracy and estimate uncertainty using ensemble and machine-learning techniques. The resulting product will be the most accurate dataset of its size and at a 2km x 2km spatial and 5-minute temporal resolution. Through this work, a mesoscale vertical velocity layer will be produced by calculating the likelihood of orographic updraft and thermal updraft conditions across the continental United States. Specifically, we will use WRF model output combined with digital elevation maps to predict updrafts and then determine if vertical velocities are sufficient to support Golden Eagle soaring and gliding. Ultimately this data layer will be made available as a GIS layer in the Wind Prospector (maps.nrel.gov/wind-prospector/) tool or a similar framework. Data that will be incorporated include wind speed, direction temperature, relative humidity, barometric pressure, air density, precipitation rate, solar radiation, atmospheric stability, skin temperature, and upward heat flux. These products will advance research on interactions between volant species and wind energy by providing open access to highly resolved data with uncertainty quantification not previously available at this scale.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Validating Irradiance Models for High-Latitude Vertical Bifacial Photovoltaic Systems

Bifacial photovoltaic systems oriented vertically facing east-west are an emerging design, targeting production in morning and afternoon hours and providing competitive annual energy yield to traditional south-tilted modules for high latitude locations. The accuracy of existing bifacial PV models when modules are oriented vertically has yet to be examined in detail. Here, we compare four bifacial PV irradiance models in ~150 locations between 15-80 degrees N on the utility-scale, finding higher inter-model deviations for vertical PV systems than south-tilted across all latitudes less than 75 degrees N. We validate model-predicted irradiance with test-site data collected in Golden, Colorado and Fairbanks, Alaska for E-W vertical and south-tilted arrays. View factor models agree with E-W vertical test-site data in Golden with RMSE=15%. Modelling error increases for the Alaskan test-site to RMSE values between 21-30%, driven in part by high albedo measurement uncertainty during snowy months.

bifacial↗

Optimal Electric Vehicle Charging and Discharging Strategies Under DER Compensation Programs: Preprint

The adoption of electric vehicles (EVs) is becoming increasingly popular because of environmental concerns, the greater availability of models, and increased cost-competitiveness with gas vehicles. Because EVs have both charging and discharging capabilities, they provide great potential to help electric utilities with grid operation. When the grid demand is high, EVs can discharge to the grid to reduce the peak load, and vice versa; therefore, electric utilities have designed different policies to encourage EV charging station operators to charge or discharge at certain time periods. The New York State Public Service Commission established the Value of Distributed Energy Resources (VDER), or the Value Stack, to compensate for energy created by distributed energy resources, including EVs. This paper presents an optimization-based approach to identify the "golden hours" and "golden spots," i.e., the effective time periods and geographic locations for EV charging station operators to charge or discharge under the VDER program that can provide them the highest benefit. The proposed methodology can be applied to other compensation mechanisms and distribution systems as well. By working with industry partner NineDot Energy, realistic charging station information is used in this study, and the proposed approach is tested on a distribution feeder. The results from this study can help electric utilities and EV charging station operators determine the ideal charging/discharging time and the ideal locations for the charging station(s) in their distribution systems to achieve maximized benefit.

electric vehicle↗

NREL at a Glance

NREL leads research, innovation, and strategic partnerships that advance and strengthen energy abundance, affordability, security, and reliability as well as power economic growth and global competitiveness. Golden, Colorado, hosts the main NREL facility - the South Table Mountain Campus - and the U.S. Department of Energy (DOE) responsible site office - the Golden Field Office; the Flatirons Campus is located 25 miles north. Additional NREL facilities include NREL's Alaska Campus in Fairbanks and the Washington, D.C., office.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Summary Report of the Carbon-Negative Hydrogen Workshop

This report summarizes the outcomes of the Carbon-Negative Hydrogen Workshop held at the National Renewable Energy Laboratory in Golden, Colorado on June 22-23, 2023. The workshop was co-sponsored by Lawrence Livermore National Laboratory and the National Energy Technology Laboratory and focused on developing a shared understanding of the importance of and opportunities for generation and use of carbon-negative hydrogen in industrial decarbonization. For the purposes of this workshop, carbon-negative hydrogen was defined as hydrogen (H 2 ) produced in a manner that leads to net carbon dioxide removal from the atmosphere thus giving rise to a life cycle cradle-to-grave carbon intensity that is below zero.

08 HYDROGEN↗