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Estimating spectral plane-of-array (POA) solar irradiance on inclined surfaces is an important step in the design and performance evaluation of both photovoltaic and concentrated solar plants. This work introduces a fast, line-by-line spectral, Monte Carlo (MC) radiative transfer model approach to simulate anisotropic distributions of shortwave radiation through the atmosphere as photon bundles impinge on inclined surfaces. This fast Monte Carlo approach reproduces the angular distribution of solar irradiance without the undesirable effects of spatial discretization and thus computes detailed POA irradiance values on surfaces at any orientation and also when surfaces are subjected to the anisotropic ground and atmospheric scattering. Polarization effects are also easily incorporated into this approach that can be considered as direct numerical simulation of the physics involved. Here, we compare our Monte Carlo radiative transfer model with the most widely used empirical transposition model, Perez4, under various conditions. The results show that the Perez4 model reproduces the more detailed Monte Carlo simulations with less than 10% deviation under clear skies for all relevant surface tilt and azimuth angles. When optically thin clouds are present, observed deviations are larger, especially when the receiving surface is strongly tilted. Deviations are also observed for large azimuth angle differences between the receiving surface and the solar position. When optically thick clouds are present, the two models agree within 15% deviation for nearly all surface orientation and tilt angles. The overall deviations are smaller when compared with cases for optically thin clouds. The Perez4 model performs very well (∼6.0% deviation) in comparison with the detailed MC simulations for all cases, thus validating its widespread use for practical solar applications. When detailed atmospheric profiles and cloud optical properties are available, the proposed fast Monte Carlo radiative model reproduces accurate spectral and angular POA irradiance levels for various atmospheric and cloud cover conditions, surface orientations, and different surface and ground properties.

The output of ground-based, solar power generation systems is strongly dependent on cloud cover, which is the main contributor to solar power variability and uncertainty. Cloud optical properties are typically over-simplified in forecasting applications due to the lack of real-time, accurate estimates. In this work, we introduce a method, the Spectral Cloud Optical Property Estimation (SCOPE), for estimating cloud optical properties directly from high-resolution (5-min, 2 km) imagery from Geostationary Operational Environmental Satellite (GOES)-R, which is the newest generation of the GOES system. The SCOPE method couples a two-stream, spectrally resolved radiative model with the longwave GOES-R sensor output to simultaneously estimate the cloud optical depth, cloud top height, and cloud thickness during both day and night at 5-min intervals. The accuracy of SCOPE is evaluated using one year (2018) of downwelling longwave (DLW) radiation measurements from the Surface Radiation Budget Network, which consists of seven sites spread across climatically diverse regions of the contiguous United States. During daytime clear-sky periods, SCOPE predicts DLW within instrument uncertainty (10 W m−2) for four of the seven locations, with the remaining locations yielding errors of the order of 11.2, 17.7, and 20.2 W m−2. For daytime cloudy-sky, daytime all-sky (clear or cloudy), and nighttime all-sky periods, SCOPE achieves root mean square error values of 23.0–34.5 W m−2 for all seven locations. These results, together with the low-latency of the method (∼1 s per sample), show that SCOPE provides a viable solution to real-time, accurate estimation of cloud optical properties for both day and night.

We propose a framework for modeling the temperature-dependent infrared optical and radiative properties of metals exhibiting nonideal free-carrier dynamics. In order to do so, we derive a parsimonious model that possesses both multivariate (in temperature and wavelength) and single variate (in wavelength) components. The model is realized as the complex-valued relative permittivity and is applicable to optically smooth media. A procedure is outlined for regressing both components of the model under an appropriate set of physical constraints that preclude superfluous degrees of freedom. The procedure is demonstrated by applying the model to nickel, a transition metal of technical significance that possesses nontrivial valency. The resulting model yields practically accurate results for eight data sets spanning four separate studies, representing the approximate wavelength ( λ) bandwidth between 1 and 16 μ m and the approximate temperature ( T) range between 0 and 1400 K. The proposed model framework retains phase information and can, therefore, be directly interfaced with more complex Fresnel frameworks, such as those commonly used for modeling systematically or randomly roughened surfaces.We propose a framework for modeling the temperature-dependent infrared optical and radiative properties of metals exhibiting nonideal free-carrier dynamics. In order to do so, we derive a parsimonious model that possesses both multivariate (in temperature and wavelength) and single variate (in wavelength) components. The model is realized as the complex-valued relative permittivity and is applicable to optically smooth media. A procedure is outlined for regressing both components of the model under an appropriate set of physical constraints that preclude superfluous degrees of freedom. The procedure is demonstrated by applying the model to nickel, a transition metal of technical significance that possesses nontrivial valency. The resulting model yields practically accurate results for eight data sets spanning four separate studies, representing the approximate wavelength ( λ) bandwidth between 1 and 16 μ m and the approximate temperature ( T) range between 0 and 1400 K. The proposed model framework ...

Passive cooling devices take advantage of the partially transparent properties of the atmosphere in the longwave spectral band from 8 to 13 μm (the so-called “atmospheric window”) to reject radiation to outer space. Spectrally designed thermophotonic devices have raised substantial attention recently for their potential to provide passive and carbon-free alternatives to air conditioning. However, the level of transparency of the atmospheric window depends on the local content of water vapor in the atmosphere and on the optical depth of clouds in the local sky. Thus, the radiative cooling capacity of solar reflectors not only depends on the optical properties of their surfaces but also on local meteorological conditions. In this work, detailed radiative cooling resource maps for the contiguous United States are presented with the goal of determining the best climates for large-scale deployment of passive radiative cooling technologies. The passive cooling potential is estimated based on ideal optical properties, i.e., zero shortwave absorptance (maximum reflectance) and blackbody longwave emittance. Both annual and season-averaged maps are presented. Daytime and nighttime cooling potential are also computed and compared. The annual average cooling potential over the contiguous United States is 50.5 m−2. The southwestern United States has the highest annual averaged cooling potential, over 70 W m−2, due to its dry and mostly clear sky meteorological conditions. The southeastern United States has the lowest potential, around 30 W m−2, due to frequent humid and/or overcast weather conditions. In the spring and fall months, the Arizona and New Mexico climates provide the highest passive cooling potential, while in the summer months, Nevada and Utah exhibit higher potentials. Passive radiative cooling is primarily effective in the western United States, while it is mostly ineffective in humid and overcast climates elsewhere.Passive cooling devices take advantage of the partially transparent properties of the atmosphere in the longwave spectral band from 8 to 13 μm (the so-called “atmospheric window”) to reject radiation to outer space. Spectrally designed thermophotonic devices have raised substantial attention recently for their potential to provide passive and carbon-free alternatives to air conditioning. However, the level of transparency of the atmospheric window depends on the local content of water vapor in the atmosphere and on the optical depth of clouds in the local sky. Thus, the radiative cooling capacity of solar reflectors not only depends on the optical properties of their surfaces but also on local meteorological conditions. In this work, detailed radiative cooling resource maps for the contiguous United States are presented with the goal of determining the best climates for large-scale deployment of passive rad...

We describe and release a comprehensive solar irradiance, imaging, and forecasting dataset. Our goal with this release is to provide standardized solar and meteorological datasets to the research community for the accelerated development and benchmarking of forecasting methods. The data consist of three years (2014–2016) of quality-controlled, 1-min resolution global horizontal irradiance and direct normal irradiance ground measurements in California. In addition, we provide overlapping data from commonly used exogenous variables, including sky images, satellite imagery, and Numerical Weather Prediction forecasts. We also include sample codes of baseline models for benchmarking of more elaborated models.We describe and release a comprehensive solar irradiance, imaging, and forecasting dataset. Our goal with this release is to provide standardized solar and meteorological datasets to the research community for the accelerated development and benchmarking of forecasting methods. The data consist of three years (2014–2016) of quality-controlled, 1-min resolution global horizontal irradiance and direct normal irradiance ground measurements in California. In addition, we provide overlapping data from commonly used exogenous variables, including sky images, satellite imagery, and Numerical Weather Prediction forecasts. We also include sample codes of baseline models for benchmarking of more elaborated models.

We examine memory viscous effects on the motion of a particle in the vicinity of nodal points. The Basset history force has a fractional derivative dependence of order 3∕2 on the particle displacement, and its contribution to the dynamics of acoustically forced particles is demonstrated for typical conditions occurring in acoustic separation devices. The inclusion of the Basset history force in the formulation has the net effect of changing the eigenfunctions of the problem from exponential to Mittag-Leffler functions, thus affecting the overall balance of forces considered.

In this work, we address the stability of equilibrium points for particle motion in an important class of flows for which a consistent Lagrangian equation of motion for the particle can be derived and solved exactly. This class of flows includes all nonuniform, steady solenoidal flows that are characterized by constant vorticity and constant strain rate. We demonstrate that equilibrium points for particle motion exist for such flow fields and that, under some specific conditions, these equilibrium points are stable and therefore represent the observable steady-state solution of the Lagrangian equation of motion for the particle. We show that there exists an exact solution procedure for the Maxey-Riley equation of motion in all linear solenoidal flows. We also show that for two-dimensional linear solenoidal velocity fields characterized by closed streamlines, the stability of the equilibrium point for the particle motion is determined by the relative density of the particle with respect to the fluid: heavy...