Search NASA⌕ Search

Engineering topics

Xie, Yu

Publications and source records attributed to Xie, Yu.

At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Surface albedo and reflectance: Review of definitions, angular and spectral effects, and intercomparison of major data sources in support of advanced solar irradiance modeling over the Americas

This study defines albedo and reflectance in the context of solar applications. It examines the main sources of surface albedo data that can be used to help solar irradiance modeling efforts, such as undertaken by the National Renewable Energy Laboratory (NREL) over the Americas, for instance, per the National Solar Radiation Database (NSRDB). The MODIS-based albedo database, as used as input to derive historical time series of solar irradiance in the current version of the NSRDB, is compared to other sources of global gridded data over the Americas in general and some specific areas in particular. The particular role of snow cover is analyzed. It is found that, in the current MODIS-based NSRDB implementation, snow-impacted areas have been assigned a too high albedo in general because of the lack of consideration for the antagonistic effect of surface roughness, among other factors. Other albedo databases, such as CMSAF, MINES-ParisTech or the ERA5 reanalysis, do not display such high albedos at latitudes above ~40 degrees N. The gap-free and snow-free MODIS MCD43GF product is found affected by a long-term downward trend over some areas and out-of-phase seasonal effects over other areas, in comparison with MERRA-2 reanalysis data in particular. Comparisons with actual albedo measurements at the arid Desert Rock site in Nevada also show that albedo data derived from land surface models are affected by systematic bias. Five albedo databases are intercompared for the area around Ivanpah Playa, California, which has great importance in both remote sensing and solar applications. Various aspects of the proper usage of albedo data in solar radiation modeling are discussed, regarding calculations of both the backscattering process and reflections on a tilted surface: spatial resolution, temporal resolution, angular effects, and spectral effects. An important distinction is made between the use of albedo data at ~4 km resolution for backscattering calculations and at ~10 m resolution for transposition calculations to tilted planes, which might additionally require spectral information for monofacial or bifacial PV applications. It is shown that the tilted calculations usually performed in solar resource assessments are far from realistic in the case of most large-scale PV applications, for which a more suitable methodological approach is described. For such needs, the limitations of the current sources of high-resolution reflectance data are discussed. The impact of surface albedo estimation errors on the estimation of backscattered irradiance over snowy areas is evaluated. It is found non-negligible, and even large under cloudy conditions.

14 SOLAR ENERGY↗
DOE OSTI2019

Edge Segregated Polymorphism in 2D Molybdenum Carbide

Molybdenum carbide (Mo 2 C), a class of unterminated MXene, is endowed with rich polymorph chemistry, but the growth conditions of the various polymorphs are not understood. Other than the most commonly observed T-phase Mo 2 C, little is known about other phases. Here, Mo 2 C crystals are successfully grown consisting of mixed polymorphs and polytypes via a diffusion-mediated mechanism, using liquid copper as the diffusion barrier between the elemental precursors of Mo and C. By controlling the thickness of the copper diffusion barrier layer, the crystal growth can be controlled between a highly uniform AA-stacked T-phase Mo 2 C and a “wedding cake” like Mo 2 C crystal with spatially delineated zone in which the Bernal -stacked Mo 2 C predominate. The atomic structures, as well as the transformations between distinct stackings, are simulated and analyzed using density functional theory (DFT)-based calculations. Bernal -stacked Mo 2 C has a d band closer to the Fermi energy, leading to a promising performance in catalysis as verified in hydrogen evolution reaction (HER).

36 MATERIALS SCIENCE↗
DOE OSTI2019

The National Solar Radiation Database (NSRDB) for CSP Applications: Preprint

This study examines the differences in direct normal irradiance (DNI) in the two versions of the National Solar Radiation Database (NSRDB) produced by the National Renewable Energy Laboratory. Version 3 of the NSRDB includes significant changes in various parts of the radiative transfer model and inputs to the model from Version 2. The changes in Version 3 resulted in less uncertainty than Version 2. The study quantified the uncertainty and the spatial and temporal variability under clear-sky conditions. The uncertainty estimation was performed using a standardized method, A Guide to the Expression of Uncertainty in Measurement (GUM). The method includes high-quality ground-measured data for seven of the National Oceanic and Atmospheric Administration's Surface Radiation Budget Network (SURFRAD) stations for 1998-2015.

14 SOLAR ENERGY↗
DOE OSTI2018

Developing a Framework for Reference Cell Standards for PV Resource Applications

Quantifying and predicting electricity production from photovoltaic (PV) systems is based on measured or modeled irradiance data. These solar resource data consist of global horizontal irradiance, global tilted irradiance, direct normal irradiance, and diffuse horizontal irradiance, which are either derived from satellite observations validated against ground-based measurements or directly obtained from ground-based measurements. The ground-based measurements are made using thermopile or photodiode radiometers. For a PV plant, the efficiency of the energy production is verified by comparing measured output with the modeled production, which is computed using either modeled or measured irradiance data. Thus, plant performance assessments typically include the uncertainty of the transposition and, in some cases, decomposition of a given irradiance to convert to the appropriate plane-of-array (POA) irradiance corresponding to the orientation of the PV installation. Additionally, the various types of uncertainty in radiometric measurements or the modeled irradiance and the PV module specifications influence the model results and thereby further increase the uncertainty. An alternative method of assessing the PV system performance has been to use reference cells to measure the "PV resource." When used to calculate PV performance ratios, there are inherent systematic differences between radiometers and reference cells, such as spectral, directional, temperature, time responses, nonstability, and nonlinearity differences. Reference cells tend to mimic the performance and characteristics of a PV module more closely. In this report, a framework is proposed to develop standards that will better quantify and characterize the use of reference cells for PV resource measurements. The measurement from an appropriate reference cell in the POA correlates closely with the plant performance, reduces the number of modeling steps needed to simulate PV performance, and hence reduces the uncertainties of the comparisons. Because technologically matched reference cells and PV modules respond similarly to each wavelength of light that composes the incident solar radiation, the uncertainty associated with the changing spectral distribution of incident radiation during the day and year can be greatly reduced. This will reduce the overall uncertainty in estimated PV performance. The same can be said for the angle-of-incidence effects because the reference cells are deployed in the same POA as the PV module. At that point, the main sources of uncertainty are in modeling the temperature effect differences between the reference cells and the PV module and accounting for the difference between the short-circuit current monitored by the reference cells and max power point current and voltage at which the PV module operates. These sources of uncertainty are also associated with typical irradiance measurements made by pyranometers and pyrheliometers; however, typical irradiance measurements also include uncertainties associated with the spectral mismatch between thermopile or photodiode pyranometers and the PV module, which are minimized with the use of reference cells. To enhance the use of reference cells for resource assessment, we identify the necessary data, characteristics, and calibration methodologies of reference cells and how to standardize the use of these data and methods. Further, as we develop this framework, the classification of reference cells will be essential to provide guidance for selecting PV reference cells appropriate for a specific application. As we address the calibration and sources of uncertainties of reference cells, classification schemes and expected limits of performance with respect to certain parameters become important.

14 SOLAR ENERGY↗
DOE OSTI2018

Assessment of the National Solar Radiation Database (NSRDB 1998-2016)

Applying traceable and standardized uncertainty characterization for solar resource data provides confidence in the dataset for use by financiers, developers and site operators of solar energy conversion systems, and ultimately reduces deployment cost. Performance guarantees of solar energy conversion systems are based on the available solar resource from measurement stations or modeled dataset such as the National Solar Radiation Database (NSRDB). In this study we implemented a comprehensive uncertainty determination approach [1]. The study also analyzed how the NSRDB (19982016) - Version 3 compares with the previous NSRDB (19982015) - Version 2. The study also attempted to estimate the uncertainty differences derived by comparing theNSRDB data to the seven measurement stations from the National Oceanic and Atmospheric Administration's Surface Radiation Budget Network (SURFRAD) and University of Oregon Solar Radiation Monitoring Laboratory (SRML). The evaluation was conducted for hourly values, daily totals, monthly mean daily totals, and annual mean monthly mean daily totals and demonstrate the qualityof the new datasets currently available from the NSRDB.

14 SOLAR ENERGY↗
DOE OSTI2018

A Physics-based Smart Persistence model for Intra-hour forecasting of solar radiation (PSPI) using GHI measurements and a cloud retrieval technique

Short-term solar forecasting models based solely on global horizontal irradiance (GHI) measurements are often unable to discriminate the forecasting of the factors affecting GHI from those that can be precisely computed by atmospheric models. Here, we introduce a Physics-based Smart Persistence model for Intra-hour forecasting of solar radiation (PSPI) that decomposes the forecasting of GHI into the computation of extraterrestrial solar radiation and solar zenith angle and the forecasting of cloud albedo and cloud fraction. The extraterrestrial solar radiation and solar zenith angle are accurately computed by the Solar Position Algorithm (SPA) developed at the National Renewable Energy Laboratory (NREL). A cloud retrieval technique is used to estimate cloud albedo and cloud fraction from surface-based observations of GHI. With the assumption of persistent cloud structures, the cloud albedo and cloud fraction are predicted for future time steps using a two-stream approximation and a 5-min exponential weighted moving average, respectively. Our model evaluation using the long-term observations of GHI at NREL's Solar Radiation Research Laboratory (SRRL) shows that the PSPI has a better performance than the persistence and smart persistence models in all forecast time horizons between 5 and 60 min, which is more significant in cloudy-sky conditions. Finally, compared to the persistence and smart persistence models, the PSPI does not require additional observations of various atmospheric parameters but is customizable in that additional observations, if available, can be ingested to further improve the GHI forecast. An advanced technology of cloud forecast is also expected to improve the future performance of the PSPI.

14 SOLAR ENERGY↗
DOE OSTI2018

Recent Advancements in the Numerical Simulation of Surface Irradiance for Solar Energy Applications

This paper briefly reviews the National Renewable Energy Laboratory's recent efforts to develop all-sky solar irradiance models for solar energy applications. The Fast All-sky Radiation Model for Solar applications (FARMS) uses the simulation of clear-sky transmittance and reflectance and a parameterization of cloud transmittance and reflectance to rapidly compute broadband irradiances on horizontal surfaces. The accuracy of FARMS is comparable to that of two-stream approximation, but it is approximately 1,000 times faster. A FARMS for Narrowband Irradiance over Tilted surfaces (FARMS-NIT) has been developed to compute spectral irradiances on photovoltaic (PV) panels in 2,002 wavelength bands. FARMS-NIT has been extended to bifacial PV panels by accounting for solar radiation reaching the backside of a PV panel.

14 SOLAR ENERGY↗
DOE OSTI2018

Fabrication and properties of biodegradable ZnO nano-rods/porous Zn scaffolds

Highlights: • ZnO nano-rods/porous Zn scaffolds were fabricated successfully. • Compressive property of ZnO nano-rods/porous Zn scaffolds is not decrease obviously. • The ZnO nano-rods/porous Zn scaffolds have a good corrosion resistance in SBF. • The ZnO nano-rods/porous Zn scaffolds can efficiently induce Ca-P precipitation. • The ZnO nano-rods/porous Zn scaffolds have an excellent antibacterial activity. - Abstract: Biodegradable ZnO nano-rods/porous Zn scaffolds were successfully fabricated by treating the porous Zn scaffolds in NaCl solution at 80 °C. X-ray diffraction (XRD) analysis shows that the nano-rods in situ fabricated on the porous Zn scaffolds in NaCl solution are hexagonal ZnO phase. This result is also confirmed by the image of high resolution transmission electron microscope (HRTEM) and the analysis of X-ray photoelectron spectroscopy (XPS). Compressive tests suggest that the compressive mechanical properties of the ZnO nano-rods/porous zinc scaffolds do not decrease significantly compared with that of the porous Zn scaffolds without treating in NaCl solution. Immersion tests in simulated body fluid (SBF) show that the ZnO nano-rods/porous zinc scaffolds slightly gain in weight after 16 days of immersion. Moreover, these ZnO nano-rods/porous zinc scaffolds can efficiently induce Ca-P precipitation during immersion tests and show a good bioactivity. In addition, antibacterial tests imply that the ZnO nano-rods/porous zinc scaffolds have an excellent antibacterial ability against Escherichia coli and Staphylococcus aureus. However, the results of cytotoxicity tests of ZnO nano-rods/porous Zn scaffolds are not satisfactory.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2018

A New Approach for Short-Term Solar Radiation Forecasting Using the Estimation of Cloud Fraction and Cloud Albedo

Solar generation is an increasing part of the energy portfolio in the United States. An accurate forecast of the available solar resource and power is essential to managing the electric grid, market operations, and reducing the cost of solar energy. High-frequency forecasts of solar radiation in intra-hour horizons is important for real-time electric power system energy management, especially at the distribution level. Conventional Numerical Weather Prediction models perform poorly in intra-hour, high-frequency forecasts because of the limits on real-time computing, spatial resolution, and infrequent availability of observations. Although a number of alternative technologies, e.g., time-series analysis and machine learning, have been used to fill this gap, the smart persistence model is among the top-performing models in short-term forecasting and therefore often serves as the baseline to evaluate other forecasting models. Although the smart persistence model often serves as the baseline model in these intra-hour forecasts, obvious uncertainties exist in the current smart persistence model: (1) clear-sky index does not respond to the variation of the solar incident angle when cloud conditions are persistent within the forecast horizon, and (2) cloud coverage is inherently persistent though it is constrained by cloud advection. In this study, we developed a Physics-Based Smart Persistence Model for Intra-Hour Solar Forecasting (PSPI) that integrates cloudy property estimation, a radiative transfer model, and cloud fraction forecasts to improve the performance of the smart persistence model. Compared to the smart persistence model, PSPI does not require additional observations of various atmospheric parameters past global horizontal irradiance, but it is customizable because additional observations, if available, can be ingested to further improve the forecast. Our results show that the PSPI outperforms the persistence and smart persistence model on 5-minute, 15-minute, and 30-minute forecast horizons. The software package of PSPI is flexible to users' needs and provides low computational time to run at site-specific locations across the continental United States.

14 SOLAR ENERGY↗
DOE OSTI2018

National Solar Radiation Database (NSRDB)

The National Solar Radiation Database (NSRDB) is a serially complete collection of meteorological and solar irradiance data sets for the United States and a growing list of international locations for 1998-2023. The NSRDB is updated annually and provides foundational information to support U.S. Department of Energy programs, research, industry and the general public. The NSRDB provides time-series data at 30-minute resolution of resource averaged over surface cells of 0.038 degrees in both latitude and longitude, or nominally 4 km in size. Additionally time series data at 5 minutes for the US and 10 minutes for North, Central and South America at 2 km resolution are produced from the next generation of GOES satellites and made available from 2019. The solar radiation values represent the resource available to solar energy systems. The data was created using cloud properties which are generated using the AVHRR Pathfinder Atmospheres-Extended (PATMOS-x) algorithms developed by the University of Wisconsin. Fast all-sky radiation model for solar applications (FARMS) in conjunction with the cloud properties, and aerosol optical depth (AOD) and precipitable water vapor (PWV) from ancillary source are used to estimate solar irradiance (GHI, DNI, and DHI). The Global Horizontal Irradiance (GHI) is computed for clear skies using the REST2 model. For cloud scenes identified by the cloud mask, FARMS is used to compute GHI and FARMS DNI is used to compute the Direct Normal Irradiance (DNI). The PATMOS-X model uses radiance images in visible and infrared channels from the Geostationary Operational Environmental Satellite (GOES) series of geostationary weather satellites. Ancillary variables needed to run REST2 and FARMS (e.g., aerosol optical depth, precipitable water vapor, and albedo) are derived from NASA's Modern Era-Retrospective Analysis (MERRA-2) dataset. Temperature and wind speed data are also derived from MERRA-2 and provided for use in NREL's System Advisor Model (SAM) to compute PV generation.

aerosol↗
DOE OSTI2018

Assessment of Error Sources in the Modeling of POA Irradiance Under Clear-Sky Conditions: Preprint

A new physics-based model, the Fast All-sky Radiation Model for Solar applications with Narrowband Irradiances on Tilted surfaces (FARMS-NIT), accurately computes plane-of-array (POA) irradiances in both narrow- and broad wavelength bands within the solar region. The evaluation studies suggest that the new model provides increased accuracy than a model assuming isotropic diffuse solar radiation and an empirical model linking the POA irradiances with long-term surface observations at selected locations. This study anlyzes the surface observations used by FARMS-NIT and is intended to understand the error sources under clear-sky conditions as well as their impact to the performance of FARMS-NIT.

14 SOLAR ENERGY↗
DOE OSTI2018

A Fast All-sky Radiation Model for Solar applications with Narrowband Irradiances on Tilted surfaces (FARMS-NIT): Part I. The clear-sky model

The solar energy industry often uses individual steps to empirically compute plane-of-array (POA) irradiance from horizontal irradiance and decompose it to narrow-wavelength bands. Conventional radiative transfer models designed for meteorological applications requires significant computing efforts in practice; however, they provide a physics-based solution of radiance and therefore are capable of computing spectral POA irradiances in a single step. In this study, we integrate the advantages of the current models and develop an innovative radiative transfer model, the Fast All-sky Radiation Model for Solar applications with Narrowband Irradiances on Tilted surfaces (FARMS-NIT), to efficiently compute irradiances on inclined photovoltaics (PV) panels for 2002 narrow-wavelength bands from 0.28 to 4.0 um. This study is reported in two parts. Part I presents the methodology and performance evaluation of the new model under clear-sky conditions. The Simple Model of the Atmospheric Radiative Transfer of Sunshine (SMARTS), which was designed to compute clear-sky irradiances, is employed to rapidly provide the optical properties of a given clear-sky atmosphere. The clear-sky radiances in the narrow-wavelength bands are computed by considering three paths of photon transmission and solving the radiative transfer equation with the single-scattering approximation. The Bi-directional Transmittance Distribution Function (BTDF) of aerosols is given by their single-scattering phase function with a correction using a two-stream approximation. The validation analysis confirms that FARMS-NIT has improved accuracy compared to TMYSPEC as evaluated by both surface observations and a state-of-the-art radiative transfer model. This model substantially improves computational efficiency compared to other radiative transfer models though it uses slightly more computing time than TMYSPEC. Part II of this study addresses the model in cloud-sky conditions and will be published as a companion paper.

14 SOLAR ENERGY↗
DOE OSTI2018

NREL Renewable Energy Resource Data

This data is derived from the Wind Integration National Dataset (WIND) Toolkit and the Solar Integration National Dataset (SIND). The WIND Toolkit provides meteorological conditions and turbine power for more than 126,000 land-based and offshore wind sites across the continental United States, and the SIND Toolkit provides subhourly solar power data designed to assist researchers and utilities in solar generation integration studies This data set includes meteorological variables, including wind speed, direction, temperature, pressure, air density, irradiance, and surface temperature. Parameters such as wind profiles, atmospheric stability, and solar radiation data are also included.

P↗
DOE OSTI2018

NREL Renewable Energy Resource Data

This data is derived from the Wind Integration National Dataset (WIND) Toolkit and the Solar Integration National Dataset (SIND). The WIND Toolkit provides meteorological conditions and turbine power for more than 126,000 land-based and offshore wind sites across the continental United States, and the SIND Toolkit provides subhourly solar power data designed to assist researchers and utilities in solar generation integration studies This data set includes meteorological variables, including wind speed, direction, temperature, pressure, air density, irradiance, and surface temperature. Parameters such as wind profiles, atmospheric stability, and solar radiation data are also included.

Rossol, Michael↗
DOE OSTI2018

Assessment of the National Solar Radiation Database (NSRDB 1998-2016): Preprint

Applying traceable and standardized uncertainty characterization for solar resource data provides confidence in the data set for use by financiers, developers, and site operators of solar energy conversion systems, and ultimately this reduces deployment cost. Performance guarantees of solar energy conversion systems are based on the available solar resource from measurement stations or modeled data sets, such as the National Solar Radiation Database (NSRDB). In this study, we implemented a comprehensive uncertainty determination approach (1). The study also analyzed how the NSRDB (1998-2016): Version 3 compares with the previous NSRDB (1998-2015): Version 2. The study also attempted to estimate the uncertainty differences derived by comparing the NSRDB data to the seven measurement stations from the National Oceanic and Atmospheric Administration's Surface Radiation Budget Network (SURFRAD) and University of Oregon Solar Radiation Monitoring Laboratory (SRML). The evaluation was conducted for hourly values, daily totals, monthly mean daily totals, and annual mean monthly mean daily totals, and it demonstrates the quality of the new data sets currently available from the NSRDB.

14 SOLAR ENERGY↗
DOE OSTI2018

In situ atomistic insight into the growth mechanisms of single layer 2D transition metal carbides

Developing strategies for atomic-scale controlled synthesis of new two-dimensional (2D) functional materials will directly impact their applications. Here, using in situ aberration-corrected scanning transmission electron microscopy, we obtain direct insight into the homoepitaxial Frank–van der Merwe atomic layer growth mechanism of TiC single adlayers synthesized on surfaces of Ti 3 C 2 MXene substrates with the substrate being the source material. Activated by thermal exposure and electron-beam irradiation, hexagonal TiC single adlayers form on defunctionalized surfaces of Ti 3 C 2 MXene at temperatures above 500 °C, generating new 2D materials Ti 4 C 3 and Ti 5 C 4 . The growth mechanism for a single TiC adlayer and the energies that govern atom migration and diffusion are elucidated by comprehensive density functional theory and force-bias Monte Carlo/molecular dynamics simulations. This work could lead to the development of bottom-up synthesis methods using substrates terminated with similar hexagonal-metal surfaces, for controllable synthesis of larger-scale and higher quality single-layer transition metal carbides.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Double transition metal MXenes with wide band gaps and novel magnetic properties

Novel wide band gaps and magnetism in ordered titanium–vanadium, titanium–chromium, and titanium–manganese carbide and nitride based MXenes are predicted using density functional theory. Based on the recent synthesis of Ti centred double transition metal MXenes, we study MXenes with a central Ti layer and different surface early 3d metals, and various terminations, TiM 2 X 2 T (M = V, Cr, Mn; X = C, N; T = H, F, O, OH). While previously studied MXenes are strongly metallic, we predict surface metal and termination dependent metal–insulator transitions in the Cr–N and Mn–N series. A uniquely wide band gap over 1 eV is predicted for TiMn 2 N 2 F 2 using the HSE06 density functional while the unterminated TiMn 2 N 2 remains metallic. The entire TiCr 2 C 2 T series is predicted to be semiconducting. Distinct from the more common Ti–C MXenes, not all combinations of metals and terminations are predicted to be stable. Within the examined sets of materials, anti-ferromagnetic orders are generally most favorable. In conclusion, the new MXenes further extend the range of properties accessible in this family of two-dimensional nanomaterials.

36 MATERIALS SCIENCE↗