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  • IrradianceNet: Spatiotemporal deep learning model for satellite-derived . . .
    Solar irradiance forecasting can be traced all the way back to the late 19th century when numerical weather prediction models (NWP) were first developed (Yang et al , 2018) Since then, numerous methods have been developed to improve forecast horizons spanning from very short-term forecasts to multiple days ahead (Lorenz et al , 2009)
  • Direct normal irradiance related definitions and applications: The . . .
    Historically, the interest in accurate measurement of DNI started decades ago Early studies (e g , Linke, 1931, Linke and Ulmitz, 1940) identified the difficulty of separating the measurement of DNI from that of the diffuse irradiance in the immediate vicinity of the sun, hereafter referred to as circumsolar irradiance
  • Benchmark of estimated solar irradiance data at high latitude locations
    As irradiance estimates are more uncertain in cloudy conditions, the low clearness indices and high latitudes illustrates the challenges with estimating irradiance in Norway Challenges related to snow and horizon shading is also discussed, where the latter is especially pronounced in the rugged fjord terrain of Western Norway
  • Clear sky solar irradiance models: A review of seventy models
    Clear sky models can be broadly classified into empirical and physical models [13] Empirical or parametric models are simplified parameterizations of the atmospheric attenuation processes that provide analyitical expressions to estimate clear sky irradiance using some atmospheric components as inputs
  • Solar Irradiance - an overview | ScienceDirect Topics
    The irradiance at earth's surface is lower than that at the top of atmosphere due to light scattering and absorption by certain gas molecules (N 2, O 2, H 2 O, CO 2, etc ) It is estimated that the globally averaged solar irradiance is approximately 1 365 kW per square meter in a 24-h day throughout a whole year [39]
  • Global and direct solar irradiance estimation using deep learning and . . .
    The irradiance estimation results at SURFRAD stations are presented in Table 3 (for GHI) and Table 4 (for DNI) It is shown in Table 3 that deep learning models for GHI estimations using 16 satellite bands (DNN16) and 8 selected bands (DNN8) have comparable overall performance DNN16 generates GHI estimations at all the SURFRAD stations with
  • Irradiance-to-power conversion based on physical model chain: An . . .
    Here, effective irradiance refers to the POA irradiance after accounting for spectral and incidence losses; cell temperature has been discussed in Section 4 5; and PV module specifications are stored in the Sandia module database, which can be automatically retrieved by the program once the name of the module is given
  • Modeling daylight availability and irradiance components from direct . . .
    Modeling daylight availability and irradiance components from direct and global irradiance 281 3 2 Diffuse irradiance and illuminance on tilted "~ r surJaces modeling These models estimate the total (integrated) sky diffuse irradiance illuminance received by a surface ~~ = tilted from the horizontal (e g , a window)
  • Spectral irradiance, ground and crop dynamic reflectance: Key . . .
    The irradiance on the front side of the bifacial PV module G front can be calculated by [41]: (3) G front = G b R b + G d, t i l t + R Â · G H I 1-c o s β 2 where G b represents the beam irradiance on a horizontal surface; R b is the ratio of the beam irradiance on the tilted surface to that on a horizontal surface; G d, t i l t is the total





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