Data Processing for Short-Term Solar Irradiance Forecasting using Ground-Based Infrared Images. (arXiv:2101.08694v1 [astro-ph.IM])

Data Processing for Short-Term Solar Irradiance Forecasting using Ground-Based Infrared Images. (arXiv:2101.08694v1 [astro-ph.IM])
<a href="http://arxiv.org/find/astro-ph/1/au:+Terren_Serrano_G/0/1/0/all/0/1">Guillermo Terr&#xe9;n-Serrano</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Martinez_Ramon_M/0/1/0/all/0/1">Manel Mart&#xed;nez-Ram&#xf3;n</a>

The generation of energy in a power grid which uses Photovoltaic (PV) systems
depends on the projection of shadows from moving clouds in the Troposphere.
This investigation proposes an efficient method of data processing for the
statistical quantification of cloud features using long-wave infrared (IR)
images and Global Solar Irradiance (GSI) measurements. The IR images are
obtained using a data acquisition system (DAQ) mounted on a solar tracker. We
explain how to remove cyclostationary biases in GSI measurements. Seasonal
trends are removed from the GSI time series, using the theoretical GSI to
obtain the Clear-Sky Index (CSI) time series. We introduce an atmospheric model
to remove from IR images both the effect of atmosphere scatter irradiance and
the effect of the Sun’s direct irradiance. Scattering is produced by water
spots and dust particles on the germanium lens of the enclosure. We explain how
to remove the scattering effect produced by the germanium lens attached to the
DAQ enclosure window of the IR camera. An atmospheric condition model
classifies the sky-conditions in four different categories: clear-sky, cumulus,
stratus and nimbus. When an IR image is classified in the category of
clear-sky, it is used to model the scattering effect of the germanium lens.

The generation of energy in a power grid which uses Photovoltaic (PV) systems
depends on the projection of shadows from moving clouds in the Troposphere.
This investigation proposes an efficient method of data processing for the
statistical quantification of cloud features using long-wave infrared (IR)
images and Global Solar Irradiance (GSI) measurements. The IR images are
obtained using a data acquisition system (DAQ) mounted on a solar tracker. We
explain how to remove cyclostationary biases in GSI measurements. Seasonal
trends are removed from the GSI time series, using the theoretical GSI to
obtain the Clear-Sky Index (CSI) time series. We introduce an atmospheric model
to remove from IR images both the effect of atmosphere scatter irradiance and
the effect of the Sun’s direct irradiance. Scattering is produced by water
spots and dust particles on the germanium lens of the enclosure. We explain how
to remove the scattering effect produced by the germanium lens attached to the
DAQ enclosure window of the IR camera. An atmospheric condition model
classifies the sky-conditions in four different categories: clear-sky, cumulus,
stratus and nimbus. When an IR image is classified in the category of
clear-sky, it is used to model the scattering effect of the germanium lens.

http://arxiv.org/icons/sfx.gif

Comments are closed.