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The Ultra-Short-Term Forecasting of Global Horizonal Irradiance Based on Total Sky Images
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Intra-day solar irradiation forecast using RLS filters and satellite images
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Automatic hourly solar forecasting using machine learning models
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Comparison of eight clear sky broadband models against 16 independent data banks
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Prediction of global solar irradiance based on time series analysis: Application to solar thermal power plants energy production planning
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Evaluation of numerical weather prediction for intra-day solar forecasting in the continental United States
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Intra-hour forecasting with a total sky imager at the UC San Diego solar energy testbed
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Intra-hour DNI forecasting based on cloud tracking image analysis
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Hybrid solar forecasting method uses satellite imaging and ground telemetry as inputs to ANNs
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Comparison of numerical weather prediction solar irradiance forecasts in the US, Canada and Europe
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Hybrid intra-hour DNI forecasts with sky image processing enhanced by stochastic learning
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Cloud-tracking methodology for intra-hour DNI forecasting
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Solar irradiance forecasting using a ground-based sky imager developed at UC San Diego
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Review of photovoltaic power forecasting
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Optics of the atmosphere--Scattering by molecules and particles
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Irradiance Forecasting for the Power Prediction of Grid-Connected Photovoltaic Systems
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Forecasting of Global Horizontal Irradiance Using Sky Cover Indices
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Terawatt-scale photovoltaics: Trajectories and challenges
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Enhanced solar global irradiance during cloudy sky conditions
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Cloud Coverage Based on All-Sky Imaging and Its Impact on Surface Solar Irradiance
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Feature Extraction from Whole-Sky Ground-Based Images for Cloud-Type Recognition
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The Progress in Variation of Surface Solar Radiation, Factors and Probable Climatic Effects
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Short-Term Solar Irradiance Forecasts Using Sky Images and Radiative Transfer Model
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Short-Term Solar Irradiance Forecasting Using Regression Trees: A Case Study at Canberra and Northern Queensland, Australia
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