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New Challenges in Solar Radiation, Modeling and Remote Sensing
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This reprint gathers several works focused on recent and novel research in solar radiation modeling and forecasting where remote sensing techniques and retrieval information is employed as a part of the methodology. The use of machine learning algorithms in solar irradiance modeling and solar power forecasting is included in some of the works here presented. This is a topic with high interest nowadays because of the impact in solar energy deployment and in atmospheric studies as well. The recent improved remote sensing information and available data and the advances in machine learning algorithms have a relevant presence in this reprint indicating the current ad near future path of the contributions in solar radiation modeling.
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Keywords
- aerosol and cloud impact
- all sky imagers (ASI)
- biomass burning
- black ice
- cloud cover
- complete ensemble empirical mode decomposition with adaptive noise
- daily average downward surface shortwave radiation
- DEM
- digital surface model
- direct normal irradiance
- Economics, finance, business & management
- energy losses
- financial losses
- Forest fires
- geographic information system
- GK2A/AMI
- global horizontal irradiation
- Himawari-8
- Industry & industrial studies
- Information technology industries
- local weather
- Machine learning
- machine learning models blending
- Media, information & communication industries
- meteorological observation
- MSG satellite images
- n/a
- perceived temperature
- PV energy production
- radiation flux
- radiation observation
- Renewable energy sources
- road worker PT
- Sentinel-2
- shadow pattern
- short-term forecast
- sky view factor
- Smart grid
- solar cadaster
- solar energy
- solar irradiance nowcasting
- solar potential in rooftops
- solar radiation forecasting
- solar resource mapping
- SOWEIG model
- spatial downscaling
- surface solar irradiance (SSI)
- temporal extrapolation
- topography
- Visible All-Sky image
- wavelet transform
- δ-Eddington approximation
Links
DOI: 10.3390/books978-3-0365-7871-2Editions