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Data-Driven Model for Photovoltaic Generation: Comparison with Physical Models Using a Microgrid in Puerto Rico
Photovoltaic (PV) generation is a critical component of microgrids, but its accurate modeling is challenging due to the complex and dynamic interactions between solar irradiance, temperature, and PV system installation. This paper develops a multilayer perceptron (MLP) model that inputs solar irradiance and temperature to estimate the PV generation, and it compares the proposed data-driven model’s performance to two well-known physical models: the single-diode model and the inverter model. The results demonstrate that all the models can reach high levels of accuracy. However, the MLP model outperforms the physical models on average by 4.5 to 6.6 percent in R squared scores and 220 to 290 Watts in RMSE scores, and it does not require physical system parameters. Moreover, the data-driven model can overcome the limitations of the lack of real-time PV generation data.
Cathode Modeling and Diode Performance in a Planar Geometry using Space-charge-limited Emission
Space-charge-limited (SCL) emission parameters are varied to study the performance effects in a planar diode using an electromagnetic particle-in-cell simulation software suite, EMPIRE. Oscillations in the simulations are found and linked to the emission parameters, namely the breakdown threshold, the emission delay time, and the current density ramp time. The oscillations are suggested to be a transverse oscillator due to the perfect magnetic conductor boundary condition in steady-state operation and the formation of a virtual cathode in the diode driven by the SCL boundary condition.
PV Performance Modeling and Stakeholder Engagement (Final Technical Report)
This core capability project’s objective is to increase the value of photovoltaic (PV) performance models by improving their functionality, demonstrating, and quantifying their validity, and offering a wide range of stakeholder engagement opportunities. In FY22-24, we developed new and improved modeling algorithms and functions to represent PV performance more accurately in a variety of environments and conditions. The “Model parameter toolkit” was developed and includes functions to translate between different module temperature models, incidence angle modifier models, and single-diode models. A new modeling capability named “PV Atlas” was also developed leveraging Sandia’s High Performance Computing resources. This capability allows us to investigate several questions and provide climate-specific best practices and geographic data files; all these are hosted on an interactive website on Sandia’s GitHub and can be used for training, system optimization, or to provide best practices for uncertainty reduction. For model validation, we published high-quality PV performance, and weather data; these data are well documented, filtered, and processed for quality and include examples on how to run PV simulations. We also developed well documented, standardized methods for validating PV models and ran independent model validation and 2 blind modeling intercomparisons engaging with 49 organizations from 17 countries. We co-led and contributed to a growing, well documented and maintained suite of open-source functions for PV modeling (i.e., the pvlib-python) and we outreached to the PV modeling stakeholders via the PVPMC workshops and web resources. In addition, this project supported US representation and leadership for the International Energy Agency (IEA) PVPS Task 13; specifically, members of our team led and supported 3 subtasks on: 1) Best practices for the optimization of bifacial photovoltaic tracking, 2) Extreme weather events and their multiple impact on PV power plants: Risks, failure mechanisms and mitigation strategies, and 3) Best practice guidelines for the use of economic and technical Key Performance Indicators (KPIs). This project resulted in the publications of 14 peer reviewed journal papers, 37 conference presentations, 6 SAND reports, 5 public datasets and 6 new webpages on the PVPMC website. It supported the release of 13 pvlib-python versions where 28 enhancements were from this PV Performance Modeling project. We co-organized 5 PVPMC workshops in FY22-24 with the participation of 214 unique institutions and around 700 participants. The PVPMC website was redesigned, and its reliability was improved; it receives over 50,000 visitors/year from 202 unique countries.
Cathode Modeling and Diode Performance in Planar Geometry using SCL Emission.
Abstract not provided.
Determining circuit model parameters from operation data for PV system degradation analysis: $\mathrm{PVPRO}$
Physics-based circuit parameters like series and shunt resistance are essential to provide insights into the degradation status of photovoltaic (PV) arrays. However, calculating these parameters typically requires a full current-voltage characteristic (I-V curve), the acquisition of which involves specific measurement devices and costly methods. Thus, I-V curves of the PV system level are often not available. Here this paper proposes a methodology (PVPRO) to estimate these I-V curve parameters using only operation (string-level DC voltage and current) and weather data (irradiance and temperature). PVPRO first performs multi-stage data pre-processing to remove noisy data. Next, the time-series DC data are used to fit an equivalent circuit single-diode model (SDM) to estimate the circuit parameters by minimizing the differences between the measured and estimated values. In this way, the time evolutions of the SDM parameters are obtained. We evaluate PVPRO on synthetic datasets and find an excellent estimation of both SDM and the key I-V parameters (e.g., open-circuit voltage, short-circuit current, maximum power, etc.) with an average relative error of 0.55%. The performance, especially the extracted degradation rate of parameters, is robust to various measurement noises and the presence of faults. In addition, PVPRO is applied to a 271 kW PV field system. The relative error between the real and estimated operation voltage and current is less than 1%, suggesting that degradation trends are well captured. PVPRO represents a promising open-source tool to extract the time-series degradation trends of key PV parameters from routine operation data.
Understanding the Effects of Inhomogeneities at the Back Interface of CdTe‐Based Solar Cells Using 2D Modeling
One-dimensional modeling cannot capture lateral inhomogeneities in CdTe-based devices. Here, we use 2D modeling to investigate the role of varying energetics at the back interface. We consider improvements in the back interface layer (BIL) through either reducing back surface recombination velocity (BSRV) or decreasing the downward band bending near the back interface. We show that when the BSRV is reduced, but strong downward band bending remains, there is no change in the device performance until the BSRV of 90% of the back interface is improved by the BIL. On the other hand, any coverage with a BIL that improves band bending results in device improvements. We use band bending, back interface recombination current densities, and voltage dependent current flow through the device to understand these improvements. The modeling shows that lateral flow of carriers greatly affects device performance, which is not captured in parallel diode modeling, and demonstrates improved understanding with 2D modeling.
Dynamics of laser-generated magnetic fields using long laser pulses
In this work, we report on the experimental investigation of magnetic field generation with a half-loop gold sheet coil driven by long-duration (10 ns) and high-power (0.5 TW) laser pulses. The amplitude of the magnetic field was characterized experimentally using proton deflectometry. The field rises rapidly in the first 1 ns of laser irradiation, and then increases slowly and continuously up to 10 ns during further laser irradiation. The transient dynamics of current shape were investigated with a two-dimensional (2D) numerical simulation that included Ohmic heating of the coil and the resultant change of electrical resistivity determined by the coil material temperature. The numerical simulations show rapid heating at the coil edges by current initially localized at the edges. This current density then diffuses to the central part of the sheet coil in a way that depends both on normal current diffusion as well as temporal changes of the coil resistance induced by the Ohmic heating. The measured temporal evolution of the magnetic field is compared with a model that determines a solution to the coil current and voltage that is consistent with a plasma diode model of the drive region and a 2D simulation of current diffusion and dynamic resistance due to Ohmic heating in the laser coil.
Compact Bremsstrahlung Diode Development on HERMES-III
Testing of a compact Bremsstrahlung diode at the High Energy Radiation Megavolt Electron Source III (HERMES-III) was performed at Sandia National Laboratories in November, 2023. The compact diode described here is the first prototype diode in a campaign to optimize a Bremsstrahlung diode in terms of size and dose production. The goal was to test the diode at 13MV, and the experiment realized between 10-12MV at the diode. Modeling and simulation of this geometry was performed after the test, shedding insight into several phenomena seen by experimental diagnostics. Modifications to the diode and experiment are proposed for future experiments to help explain the phenomena and approach a better final design.
Charge carrier extraction and recombination effects in GaInAs/GaAsP multi-quantum well solar cells
The carrier extraction and transport mechanisms as well as the relative contributions of radiative and non-radiative recombination processes are investigated in high-quality strain-balanced GaInAs/GaAsP multi-quantum well solar cells recently implemented in record efficiency multijunction solar cells. A comprehensive suite of complementary characterization techniques including temperature- and suns-dependent photoluminescence and photovoltaic measurements are employed to analyze thermal escape and tunneling rates, which demonstrate the need to move beyond simple drift-diffusion models of p–n junctions. This study examines the processes that best characterize the operation of these devices across varying temperatures using a simple two-diode model, incorporating multiple transport protocols, and provides insights into the performance-limiting processes and pathways for their optimization.
Fluoride-Cooled High-Temperature Pebble-Bed Reactor Reference Plant Model
In this report we present work performed in Fiscal Year 2022 that demonstrates the modeling and simulation of a fully coupled neutronics thermal hydraulics reference plant model for a fluoride-cooled high-temperature pebble-bed reactor. The multiphysics model is developed on the Nuclear Regulatory Commission’s Comprehensive Reactor Analysis Bundle (BlueCRAB) available on the Idaho National Laboratory’s high-performance computer, which natively and seamlessly couples Griffin, Pronghorn, and the BISON Multiphysics Object-Oriented Simulation Environment based applications. Griffin provides reactor physics capabilities, including depletion to the equilibrium core, k-eigenvalue, adjoint, and transient. The unique direct equilibrium core capability in Griffin is based on a streamline methodology to spatially deplete the pebbles into burnup groups. Pronghorn solves the porous medium equations for the fluid regions and conduction in the solid regions and incorporates a fluidic diode model to simulate the transition from forced to natural convection during accident scenarios. MOOSE modules solves thermal conduction problems for the pebbles and tristructural isotropic in the pebble-bed core, thus providing the fuel and moderator spatial fields for each pebble burnup group. The neutronics feedback relies primarily on fuel, moderator, and reflector temperatures as as well as the FLiBe salt density. Here, we present results for the uncoupled equilibrium core and perform comparisons to equivalent Monte Carlo models. The power distributions and kinetic parameters obtained with Griffin are consistent with those computed with Griffin. We demonstrate a noticeable improvement with the use of discrete ordinates method (SN) transport. The coupled steady-state equilibrium core provides the initial condition for two time-dependent problems: a control rod withdrawal event and an unprotected loss of flow event. In both cases, the reactor design is self-stabilizing and the solutions are consistent with the expected physics. Although this model is prototypical regarding BlueCRAB’s capabilities, its results are consistent with published work by Kairos Power and other research entities. Significant improvements to the model are planned in future work.
Advanced Photovoltaic Module Characterization: Using Image Transformers for Current–Voltage Curve Prediction From Electroluminescence Images
Individual photovoltaic (PV) module health monitoring can be a daunting task for operation and maintenance of solar farms. Modules can be inspected through luminescence, thermal imaging, and current–voltage (I–V) curve analyzes for identification of damage and power loss. I–V curves provide easily interpretable data to determine module health as they directly provide electrical performance metrics. However, in order to obtain these curves, modules must be disconnected from the array and either removed to a solar simulator or characterized in situ with corrections for module temperature, the incident solar spectrum, and intensity. Luminescence or thermal images of a module are relatively easy to acquire in situ. Electroluminescence (EL) images highlight physical defects in the modules but do not provide easily interpretable features to correlate with electrical performance. This work presents a SWin transformer network to predict I–V curves for PV modules from their corresponding EL images. The predicted I–V curves allow the accurate prediction of the maximum power point (MPP), short-circuit current I sc , and open-circuit voltage V oc with a mean error less of than 1%. Comparing single diode model (SDM) parameters extracted from the predicted curves to those extracted from the true curves, the series resistance R s demonstrates a mean error of 5.19%, and the photocurrent I a mean error of 0.197%. The shunt resistance R sh and dark current Io parameters are predicted with larger errors because of their sensitivity to small changes in the I–V curve.
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.
Novel Poly-Si:Ga/SiOx Passivating Contacts through Non-Equilibrium Doping
Poly-Si/SiOx passivating contacts are one of the key enablers for high-efficiency, low-cost c-Si solar cells. In recent years, record devices have reached efficiencies of 26% in the laboratory and 25% in the industry. The current cell structure utilizing a tunneling oxide passivating contact structure with a back phosphorus-doped poly- Si/SiOx passivating contact and a front boron diffused emitter suffers from large emitter recombination. Thus, replacing the front B diffused emitter with a p-type passivating contact is a route to overcome this deficiency. This gives rise to front/back poly-Si based passivating contacts. To address the low passivation performance of the B-doped poly-Si passivating contacts, we replace B with Ga as a novel p-type dopant to avoid dopant accumulation in the tunneling oxide, which is known to lead to large degradation loss in passivation quality. Here, we introduce a non-equilibrium method via pulsed laser melting to thermally melt and recrystallize the poly-Si and redistribute the dopants, achieving doping concentrations above the solid solubility limit (~4E19 cm-3). We demonstrate a good passivation quality with an iVoc of 721 mV with an active Ga doping concentration in poly-Si >1020 cm-3. Furthermore, we show a low contact resistivity of 33.2 +/- 9.3 mO cm2 using a diode model calculation. Finally, cross-section scanning spreading resistance microscopy was performed to determine the resistance profile across the non-homogeneously doped poly-Si layer.
Understanding the Breakdown Behavior of Ultrawide-Bandgap Boron Nitride Power Diodes Using Device Modeling
Herein, a device study using technology computer-aided design simulation to theoretically analyze the electrical performance of ultrawide-bandgap boron nitride (BN)-based vertical junction devices is performed, including h-BN Schottky diode, h-BN pn diode, and h-BN/AlN pn diode; this is also the first demonstration of the BN power devices in simulation. The material properties of BN are defined with recently reported data, and the physical mechanisms of the device performance are systematically investigated. Additionally, the h-BN junctions in this simulation shows excellent performance, especially for breakdown behaviors. Schottky diode shows a turn-on voltage of 0.6 V for Pt Schottky contact and breakdown voltages over 450 V for 5 μm, 6 × 10 15 cm –3 p-type-doped drift layer; The h-BN pn diode shows a turn-on voltage of 6 V and breakdown voltages over 3 kV with a critical electric field of 13.6 MV cm –1 for 2.5 μm, 2 × 10 16 cm –3 p-type-doped drift layer. The h-BN/AlN heterojunction pn diode shows a turn-on voltage of 5.8 V and breakdown voltage over 2 kV for 2.5 μm, 2 × 10 16 cm –3 n-type-doped AlN drift layer. Herein, an understanding of the device principles of vertical BN junctions is provided, which can serve as a reference for the future development of robust BN power electronics.
Correlative Electron Energy-Loss Spectroscopy Bandgap Mapping and DFT Modeling in AlGaN Diodes .
Abstract not provided.
Carrier capture and emission by substitutional carbon impurities in GaN vertical diodes
A model was developed for the operation of a GaN pn junction vertical diode which includes rate equations for carrier capture and thermally activated emission by substitutional carbon impurities and carrier generation by ionizing radiation. The model was used to simulate the effect of ionizing radiation on the charge state of carbon. These simulations predict that with no applied bias, carbon is negatively charged in the n-doped layer, thereby compensating n-doping as experimentally observed in diodes grown by metal-organic chemical vapor deposition. With reverse bias, carbon remains negative in the depletion region, i.e., compensation persists in the absence of ionization but is neutralized by exposure to ionizing radiation. This increases charge density in the depletion region, decreases the depletion width, and increases the capacitance. The predicted increase in capacitance was experimentally observed using a pulsed 70 keV electron beam as the source of ionization. In additional confirming experiments, the carbon charge-state conversion was accomplished by photoionization using sub-bandgap light or by the capture of holes under forward bias.