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Geologic Characterization of the South Georgia Rift Basin for Source Proximal CO2 Storage

The project Geologic Characterization of the South Georgia Rift Basin for Source Proximal CO2 Storage is one of 9 site characterization projects that were implemented as part of ARRA (American Recovery and Reinvestment Act). Data from this project was used to improve resolution of data in NATCARB in the area of study. Data related to this study has already been incorporated in NATCARB Atlas. The South Carolina Research Foundation and partners evaluated the feasibility of CCS in the Jurassic/ Triassic (J / TR) saline formations of the buried Mesozoic South Georgia Rift (SGR) Basin that extends from South Carolina into Georgia. The J / TR sequence, based on preliminary assessment of limited geologic and geophysical data, appears to have both the appropriate areal extent and multiple horizons to permanently and safely store CO2 The presence of several igneous rock layers within the sequence may potentially provide adequate seals to prevent upward CO2 migration into the Coastal Plain aquifer systems. Approximately 81 kilometers of 2-D seismic reflection data were collected by Bay Geophysical, Inc. to explore a portion of the SGR located in southern Georgia. The 81 kilometers were divided into two lines approximately 40.5 kilometers each, with Line 1 intersecting Georgia well GGS 3457. Line 2 intersects Line 1 at the southern portion of Line 1 to maximize the extent of coverage away from GGS-3457 (a deep well drilled in the 1980s for oil and gas exploration). This well had a set of usable logs, including gamma and neutron logs that provided promising results related to CO2 storage. Results showed sandstone with porosity values greater than 10 percent and a thickness of 120 meters. The design of the seismic shot was to extrapolate information away from the well and to better define the extent of the SGR and the necessary reservoir and caprock for a successful CO2 injection. A numerical simulation model of CO2 Injection and migration was developed based on the geology log for the GGS-3457 well. The simulation model was used to investigate the feasibility of injecting 30 million metric tons of CO2 into SGR J / TA sediments and integrity of the diabase layers as seals to prevent CO2 migration.

2-D seismic↗

Characterization of Most Promising Sequestration Formations in the Rocky Mountain Region

The project Characterization of Most Promising Sequestration Formations in the Rocky Mountain Region is one of 9 site characterization projects that were implemented as part of ARRA (American Recovery and Reinvestment Act). Data from this project was used to improve resolution of data in NATCARB in the area of study. Data related to this study has already been incorporated in NATCARB Atlas. The Rocky Mountain Carbon Capture and Storage (RMCCS) project investigated multiple geologic formations and characterized a local site on the Colorado Plateau for future CCS opportunities. The RMCCS project focused on the Cretaceous Dakota, Jurassic Entrada, and Pennsylvanian Weber Sandstones, the three largest regional formations. All formations in this project are potential CO2 storage resources for future power plants, natural gas processing plants, cement plants, and oil shale development projects. The area adjacent to Craig, Colorado, (Sand Wash Basin) was the area selected for detailed geologic characterization on the RMCCS project. The basin was selected in part because the geology can be extrapolated to other sites on the Colorado Plateau. Field mapping and seismic surveys were conducted to identify and evaluate the basin's structural configuration. A 9,745-foot deep characterization well was drilled to collect 131 feet of core and a suite of geophysical well log data. Petrophysical tests on samples of core were used to calibrate geophysical log data, which can be used to obtain storage resource estimates and evaluate associated uncertainty as well as simulate the hydrologic behavior of injected CO2. A detailed analysis of the primary formations (Dakota, Entrada and Weber sandstones) yielded a more accurate CO2 storage resource assessment for these formations within the Colorado Plateau; RMCCS estimates indicate a total CO2 storage resource of more than 38,000 million metric tons. The characterization of the Sand Wash Basin (2-D seismic surveys, multiple well logs and lithological, petrophysical and geochemical analyses) allowed for a detailed 3-D model to be constructed. The model served as the framework for analyses ranging from CO2 storage resource, injectivity, and subsurface flow to uncertainty estimates to evaluation of risk.

2-D seismic↗

Site Characterization of the Highest-Priority Geologic Formations for CO2 Storage in Wyoming

The project Site Characterization of the Highest-Priority Geologic Formations for CO2 Storage in Wyoming is one of 9 site characterization projects that were implemented as part of ARRA (American Recovery and Reinvestment Act). Data from this project was used to improve resolution of data in NATCARB in the area of study. Data related to this study has already been incorporated in NATCARB Atlas. The Wyoming Carbon Underground Storage Project (WY-CUSP) consisted of CO2 storage site characterization and evaluation, focusing on Wyoming’s most promising CO2 storage reservoirs (the Pennsylvanian Weber/Tensleep Sandstone and Mississippian Madison Limestone) and premier CO2 storage site (Rock Springs Uplift). Results from the WY-CUSP project suggest the two reservoirs could store up to 17,000 million tons of CO2. The WY-CUSP team drilled a stratigraphic test well and acquired a 3-D seismic survey covering 25 square miles of the Rock Springs Uplift site. The team retrieved 916 feet of core from the 12,810-foot-deep well, along with a complete log suite, borehole images, fluid samples, and other data. Project partners (1) provided continuous visual documentation of the core, including grain size, mineralogy, facies distribution, and porosity; (2) performed continuous permeability and velocity scans of selected reservoir intervals; and (3) chemically analyzed the fluid samples. WY-CUSP scientists integrated seismic attributes with observations from log suites, a VSP survey, core, fluid samples, and laboratory analyses, including continuous permeability scans. From these integrations, researchers constructed 3-D spatial distribution volumes of reservoir and seal properties that represent geological heterogeneity at the targeted CO2 storage site. The WY-CUSP team used this data to perform new CO2 plume migration simulations. Baker Hughes, Inc., completed a series of small-scale, in-situ water injectivity measurements. A database was formed when observations, analyses, and experiments from the stratigraphic test well were integrated. Correlation of these data allowed petrophysical parameters to be extrapolated from the test well out into the storage domain (5x5 mile 3-D seismic survey volume). This resulted in an improved, realistic understanding of performance assessments for potential CO2 storage scenarios. The WY-CUSP team worked on (1) improving CO2 storage resource estimates, (2) establishing long-term integrity and permanence of confining layers, (3) designing a profitable strategy for pressure management, and (4) evaluating the utilization of stored CO2 at the Rock Spring Uplift. Finally, Baker Hughes developed a microseismic baseline for the test site using in-bore geophones to complete field operations.

3-D seismic↗

Permanent Magnet Resiliency in Jefferson Lab’s Radiation Environment: LDRD Grant Status and Plans

As the FFA@CEBAF energy upgrade study progresses, it is important to investigate the impact of radiation exposure on the permanent magnet materials to be used in the upgraded fixed field alternating gradient (FFA) arcs. To address this, Jefferson Lab has awarded a Laboratory Directed Research and Development (LDRD) grant to study the resiliency of several permanent magnet materials placed in a radiation environment similar to that in which they are expected to operate. Samples of NeFeB and SmCo are to be placed alongside appropriate dosimetry in a variety of radiation environments in the beam enclosure and experimental halls at CEBAF. The magnet degradation will be measured, and extrapolated to the higher energies expected during operations after the energy upgrade. This document will describe the current status of the LDRD study, as well as describe the upcoming plans. It will also direct the readers to other proceedings which further detail the work thus far.

Bodenstein, R.↗

Current status of permanent magnet radiation resiliency studies at CEBAF

One possible future for Jefferson Lab’s Continuous Electron Beam Accelerator Facility (CEBAF) lies in upgrading its maximum nominal energy using Fixed-Field Alternating-gradient (FFA) technology for its recirculating arcs. The current proposal aims to use permanent magnets to supply the fixed fields. One concern among reviewers is the degradation of these permanent magnets during operation due to the radiation environment in which they will be present. This work, funded by a Laboratory Directed R&D grant, aims to measure the magnet degradation in the CEBAF tunnel enclosure, and extrapolate to the energies expected from the upgrade. We present the latest results of this study, as well as plans moving forward.

Accelerator Physics↗

GLUE Code: A framework handling communication and interfaces between scales

Many scientific applications are inherently multiscale in nature. Such complex physical phenomena often require simultaneous execution and coordination of simulations spanning multiple time and length scales. This is possible by combining expensive small-scale simulations (such as molecular dynamics simulations) with larger scale simulations (such continuum limit/hydro solvers) to allow for considerably larger systems using task and data parallelism. However, the granularity of the tasks can be very large and often leads to load imbalance. Traditionally, we use approximations to streamline the computation of the more costly interactions and this introduces trade-offs between simulation cost and accuracy. In recent years, the available computational power and the advances in machine learning have made computing these scale-bridging interactions and multiscale simulations more feasible. One driving application has been plasma modeling in inertial confinement fusion (ICF), which is fundamentally multiscale in nature. This requires deep understanding of how to extrapolate microscopic information into macroscopically relevant scales. For example, in ICF one needs an accurate understanding of the connection between experimental observables and the underlying microphysics. The properties of the larger scales are often affected by the microscale behavior incorporated usually into the equations of state and ionic and electronic transport coefficients (Liboff, 1959; Rinderknecht et al., 2014; Rosenberg et al., 2015; Ross et al., 2017). Instead of incorporating this information using reliable molecular dynamics (MD) simulations, one often needs to use theoretical models, due to the inability of MD to reach engineering scales (Glosli et al., 2007; Marinak et al., 1998). One approach to resolve this issue is by coupling two MD simulations of different scales via force interpolation, e.g., the AdResS method (Krekeler et al., 2018; Nagarajan et al., 2013). Another approach, which we will pursue in the scope of this work, is by enabling scale bridging between MD simulations and meso/macro-scale models through the development and support of application programming interfaces that these different applications can interact through.

54 ENVIRONMENTAL SCIENCES↗

ANALYSIS OF SUITABLE METHODOLOGIES FOR COMPRESSOR MASS FLOW RATE CORRECTION TO OTHER SUPERHEAT LEVELS AND REFRIGERANTS

This paper investigates the impact of suction conditions and refrigerant on scroll compressor mass flow rate by using calorimeter tests from AHRI-11 and AHRI-21 reports, published by AHRI's Low-GWP Alternative Refrigerants Evaluation program. Two Copeland scroll compressors (20 and 51 cm3) have been analyzed including different suction conditions (SH = 11K, SH = 22K, Ti = 18ºC) and several refrigerants (R134a, R32, R410A, R404A, etc.). Previous studies have explored response surfaces for energy consumption and mass flow rate variables. This study aims to expand the analysis by identifying the optimal approach to extrapolate mass flow rate from specific suction conditions to others SH or suction temperature levels and refrigerants. The current compressor characterization standard relies on the 1981 Dabiri correlation to correct compressor mass flow rate with suction conditions. Thus, this study aims to assess the adequacy of this correction and explore alternative correction methods for improved results.

Marchante Avellaneda, Javier↗

Paying it Forward: How an Emerging Unconventional Play can Hit the Ground Running

While every tight oil play is unique, there are lessons that can be transferred from one play to another to improve the efficiency and pace of production operations and development. These improvements may not fit precisely in every basin or play but generally hold to themes that can be tested against and built upon. Themes such as the quantity of proppant, longer lateral length, or the number of stages can be directly tied to increased productivity. However, there are diminishing returns on these investment activities for which each operator, within a given play, will be required to identify and mitigate against. This is especially true as the industry steps in and begins developing new tight oil plays. In their nascent stages, these plays may have limited well penetrations and, as a result, limited geological and performance data from which to extrapolate. Pulling together an understanding of where the industry currently resides in terms of how to exploit these resources can provide a boost in terms of working towards greatly improved well completions. In 2019, the US EIA estimated that nearly 8 million barrels of oil per day were produced from tight oil reservoirs in the United States (US EIA, 2020). This represents over 60% of the domestic crude production, originating from multiple reservoirs in the Permian Basin (TX) as well as the Bakken (MT, ND), Eagle Ford (TX), Niobrara (CO, WY), and Anadarko Basin (OK) formations, among others. As such, there are 1,000s of wells across these numerous tight oil plays that can relate an informative story. To build this story, the interplay of geology, well spacing, lateral length, and stimulation, all critical to economic success, will be explored. This paper proposes to look back at these mature tight oil (and gas) basins and bring forth an understanding of what lessons can be applied to the emerging Powder River Basin tight oil reservoirs (Mowry and the Turner/Frontier). The authors will delve into the four broad topics of geology, well spacing, lateral length, and stimulation, highlighting case studies to demonstrate those lessons from established tight oil plays that will underpin planned activities at a Field Laboratory Test Site in the southern Powder River Basin.

02 PETROLEUM↗

Proton Spin Structure from Simultaneous Monte Carlo Global QCD Analysis

Despite the great effort and achievements made towards understanding proton spin structure in the past few decades, a complete picture is still elusive. Parton distribution functions (PDFs), which in quantum chromodynamics (QCD) encode the momentum and helicity distributions of quarks and gluons inside a proton, provide the means by which to quantify the proton structure information. Being inherently nonperturbative, PDFs have to be extracted from unpolarized and polarized lepton-hadron and hadron-hadron scattering data. In particular, experiments that measure unpolarized and polarized jet observables can provide insight into the momentum and helicity distributions of gluons, which have generally been more difficult to determine reliably than those of quarks. In the past, extraction of the spin-averaged and spin-dependent (or helicity) PDFs has been performed in separate analyses. In this thesis, we perform the first simultaneous extraction of both types of quantities from deep-inelastic scattering (DIS), Drell-Yan and single jet observables, within the Monte Carlo global QCD analysis framework developed by the Jefferson Lab Angular Momentum (JAM) Collaboration. The results from this work indicate that the gluon helicity distributions depend rather strongly on the theory assumptions on which the global analysis is based, which calls for the need of measurements with higher precision. As an application of the new simultaneous JAM analysis, we perform an impact study for future Electron-Ion Collider (EIC) data with parity-conserving and parity-violating polarization asymmetries on quark and gluon helicity distributions in the proton. The extrapolation of structure functions from the current data is studied for the first time in the context of the impact study. Theory assumptions, such as SU(2) and SU(3) flavor symmetries, are also studied to give a more thorough understanding of the impact of EIC pseudodata on proton spin structure.

Zhou, Yiyu↗

Oxygen diffusion in garnet: Experimental calibration and implications for timescales of metamorphic processes and retention of primary O isotopic signatures

Knowledge of oxygen diffusion in garnet is crucial for a correct interpretation of oxygen isotope signatures in natural samples. A series of experiments was undertaken to determine the diffusivity of oxygen in garnet, which remains poorly constrained. The first suite included high-pressure (HP), nominally dry experiments performed in piston-cylinder apparatus at: (1) T = 1050–1600 °C and P = 1.5 GPa and (2) T = 1500 °C and P = 2.5 GPa using yttrium aluminum garnet (YAG; Y3Al5O12) cubes. Second, HP H2O-saturated experiments were conducted at T = 900 °C and P = 1.0–1.5 GPa, wherein YAG crystals were packed into a YAG + Corundum powder, along with 18O-enriched H2O. Third, 1 atm experiments with YAG cubes were performed in a gas-mixing furnace at T = 1500–1600 °C under Ar flux. Finally, an experiment at T = 900 °C and P = 1.0 GPa was done using a pyrope cube embedded into pyrope powder and 18O-enriched H2O. Experiments using grossular were not successful. Profiles of 18O/(18O+16O) in the experimental charges were analyzed with three different secondary ion mass spectrometers (SIMS): sensitive high-resolution ion microprobe (SHRIMP II and SI), CAMECA IMS-1280, and NanoSIMS. Considering only the measured length of 18O diffusion profiles, similar results were obtained for YAG and pyrope annealed at 900 °C, suggesting limited effects of chemical composition on oxygen diffusivity. However, in both garnet types, several profiles deviate from the error function geometry, suggesting that the behavior of O in garnet cannot be fully described as simple concentration-independent diffusion, certainly in YAG and likely in natural pyrope as well. The experimental results are better described by invoking O diffusion via two distinct pathways with an inter-site reaction allowing O to move between these pathways. Modeling this process yields two diffusion coefficients (D values) for O, one of which is approximately two orders of magnitude higher than the other. Taken together, Arrhenius relationships are:logDm2s-1=-7.2(±1.3)+(-321(±32)kJmol-12.303RT) for the slow pathway, andlogDm2s-1=-5.4(±0.7)+(-321(±20)kJmol-12.303RT) for the fast pathway. We interpret the two pathways as representing diffusion following vacancy and inter-stitial mechanisms, respectively. Regardless, our new data suggest that the slow mechanism is prevalent in garnet with natural compositions, and thus is likely to control the retentivity of oxygen isotopic signatures in natural samples. The diffusivity of oxygen is similar to Fe-Mn diffusivity in garnet at 1000–1100 °C and Ca diffusivity at 850 °C. However, the activation energy for O diffusion is larger, leading to lower diffusivities at P-T conditions characterizing crustal metamorphism. Therefore, original O isotopic signatures can be retained in garnets showing major element zoning partially re-equilibrated by diffusion, with the uncertainty caveat of extrapolating the experimental data to lower temperature conditions.

Geochemistry & Geophysics↗

A simple method for obtaining heat capacity coefficients of minerals

Abstract Heat capacity data are unavailable or incomplete for many minerals at geologically relevant temperatures. Despite the availability of entropy and enthalpy values in numerous thermodynamic tables (even sometimes at elevated temperatures), there remains need for extrapolation beyond, or interpolation between, temperatures. This approach inevitably results in estimates for entropy and enthalpy values because the heat capacity coefficients required for optimal thermodynamic treatment are less frequently available. Here we propose a simple method for obtaining heat capacity coefficients of minerals. This method requires only the empirically measured temperature-specific heat capacity for calculation via a matrix algorithm. The system of equations solver is written in the Python computing language and has been made accessible in an online repository. Thermodynamically, the solution to a system of equations represents the heat capacity coefficients that satisfy the mineral-specific polynomial. Direct coefficient calculation will result in more robust thermodynamic data, which are not subject to fitting uncertainties. Using hematite as an example, this method provides results that are comparable to conventional means and is applicable to any solid material. Coefficients vary within the traditional large 950 K temperature interval, indicating that best results should instead utilize a smaller 400 K temperature interval. Examples of large-scale implications include the refinement of geothermal gradient estimation in rapidly subsiding sedimentary basins or metamorphic and hydrothermal evolution.

Geochemistry & Geophysics↗

Optimal mass variables for semivisible jets

Strongly coupled hidden sector theories predict collider production of invisible, composite dark matter candidates mixed with standard model hadrons in the form of semivisible jets. Classical mass reconstruction techniques may not be optimal for these unusual topologies, in which the missing transverse momentum comes from massive particles and has a nontrivial relationship to the visible jet momentum. We apply the artificial event variable network, a semisupervised, interpretable machine learning technique that uses an information bottleneck, to derive superior mass reconstruction functions for several cases of resonant semivisible jet production. We demonstrate that the technique can extrapolate to unknown signal model parameter values. We further demonstrate the viability of conducting an actual search for new physics using this method, by applying the learned functions to standard model background events from quantum chromodynamics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

A model for $F_L$ structure function at low values of $Q^2$ and $x$ - revisited

A reanalysis of the model for the longitudinal structure function F_L (x,Q^2) F L ( x , Q 2 ) at low x x and low Q^2 Q 2 was undertaken, in view of the advent of the EIC. The model includes the kinematic constraint F_L\sim Q^4 F L ∼ Q 4 as Q^2\rightarrow Q 2 → 0. It is based on the photon-gluon fusion mechanism suitably extrapolated to the region of low Q^2 Q 2 . Revised model was critically updated, extended to the EIC kinematic region, and e.g. contains new parameterisations of the parton distribution functions.

Badelek, Barbara↗

Deciphering the PMI Surface Chemistry of Lithium-Based PFCs and its Effects on High Performance Plasmas in NSTX

The primary aims or objectives of the proposed work here focus on the dynamic measurement (Illinois PI Allain) and atomistic-based multi-scale computational atomistic simulations (UTK PI: Wirth) of: 1) lithium coatings with re-deposited hydrogenated carbon surfaces and high-Z substrates, 2) lithium coatings on boronized ATJ graphite surfaces and high-Z substrates and 3) lithium coatings on ATJ graphite and high-Z substrates with variation in temperature. Three main primary tasks are proposed to address each of the primary objectives listed above: 1) dynamic in-situ irradiation with D+, He+ species of lithium coatings with variation in interface substrate morphology (e.g. smooth vs rough, fuzz vs nanostructured); 2) validation and coupling with multi-scale computational simulations connecting the irradiated surface to the plasma edge; 3) extrapolation to long-pulse conditions (e.g. function of flux vs fluence studies). In primary objective #3, temperature-based effects will be studied to evaluate three primary mechanisms: a) D uptake and recycling, b) erosion, and c) surface melting and evaporation as a function of substrate morphology and chemistry.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

A Guideline for the Assessment of Uniaxial Creep and Creep-Fatigue Data and Models

Of primary concern to FE practitioners is a determination of which constitutive models are the “best”, capable of reproducing the mechanisms expected in an intended design accurately; as well as what experimental datasets are proper or “best” to use for fitting the constitutive parameters needed for the model(s) of interest. In addition, the inherent uncertainty in experiments and the repeatability and stability of extrapolations (for long-lived FE components) is a major concern. The goal of this project is to develop a guideline for the assessment of uniaxial creep and creep-fatigue data and models. The research objectives are RO1) develop an aggregated database of creep and creep-fatigue data for P91 steel and 316 stainless steel and perform a systematic assessment of the uncertainty and integrity of the datasets. RO2) employ the database to benchmark existing creep and creep-fatigue models to evaluate the model’s ability to predict standard and nonstandard boundary conditions.

20 FOSSIL-FUELED POWER PLANTS↗

2019 Results for Avian Monitoring at the Technical Area 36 Minie Site, Technical Area 39 Point 6, and Technical Area 16 Burn Ground at the Los Alamos National Laboratory

Los Alamos National Laboratory biologists in the Environmental Compliance and Protection Division at Los Alamos National Laboratory (LANL) initiated a multi-year program in 2013 to monitor avifauna (birds) at two open detonation sites and one open burn site on LANL property. Monitoring results from these efforts were compared among years to monitor trends. The objectives of this study were to 1) determine whether LANL operations impact bird species richness, diversity, or abundance 2) evaluate trends in species abundance by feeding guild, and 3) examine occupancy and nest success of secondary-cavity nesting birds using nestboxes. LANL biologists completed the seventh year of this effort in 2019. Three bird point count surveys were completed at each of the treatment sites at the Technical Area (TA) 36 Minie site, the TA-39 point 6, and the TA-16 burn ground between May and July 2019. A total of 853 birds representing 53 species were recorded at the three treatment sites and compared to their associated controls. Occupancy and nest success data from nestboxes at treatment sites were compared with the overall avian nestbox monitoring network. In 2019 the species richness and diversity at the treatment sites were not statistically different from their associated controls. Rarefaction and extrapolation plots for all years through 2018 suggest that over time the species diversity was statistically different between treatments and controls, although the diversity was higher at the treatment sites than the control sites. Avian abundance showed more variability but treatment and controls were trending together year to year. The mean number of granivores, insectivores, and omnivores varies from year to year, but there is not a significant trend at any of the treatment sites. The dominant feeding guild at the treatment sites continues to be insectivores. The overall results from 2019 continue to indicate that operations at the three treatment sites are not negatively affecting bird populations. This long-term monitoring will continue to monitor for any changes over time.

54 ENVIRONMENTAL SCIENCES↗

Automated Discovery for Emulytics

Sandia has an extensive background in cybersecurity research and is currently extending its state-of-the-art modeling via emulation capability. However, a key part of Sandia's modeling methodology is the discovery and specification of the information-system under study, and the ability to recreate that specification with the highest fidelity possible in order to extrapolate meaningful results. This work details a method to conduct information system discovery and develop tools to enable the creation of high-fidelity emulation models that can be used to enable assessment of our infrastructure information system security posture and potential system impacts that could result from cyber threats. The outcome are a set of tools and techniques to go from network discovery of operational systems to emulating complex systems. As a concrete usecase, we have applied these tools and techniques at Supercomputing 2016 to model SCinet, the world's largest research network. This model includes five routers and nearly 10,000 endpoints which we have launched in our emulation platform.

97 MATHEMATICS AND COMPUTING↗

From IEC 61853 power measurements to PV system simulations.

The IEC 61853 PV module energy rating standard requires measuring module power (and hence efficiency) over a matrix of irradiance and temperature conditions. These matrix points represent nearly the full range of operating conditions encountered in the field in all but the most extreme locations, and create an opportunity to develop alternative approaches to existing modelssuch as the single-diode models and the Sandia Array Performance Modelfor calculating system performance. This report begins by discussing the bilinear interpolation and extrapolation method from IEC 61853-3, and then describes four existing model-based methods that could be used with matrix measurements. Then a new model is developed and all options are compared according to seven objective criteria using the matrix measurements of four PV modules of different technologies. The results show that the new model is an excellent candidate for launching power matrix-based PV system simulations.

14 SOLAR ENERGY↗