Article,
Discourses on solar radiation modeling
Renewable and Sustainable Energy Reviews, (2007)
Abstract
All solar energy applications require readily available, site-oriented
and long-term solar radiation data. A typical database comprises
of global, direct and diffuse solar irradiance, duration of sunshine
and complementary data like cloud cover, atmospheric turbidity, humidity,
temperature, etc. However, most of these stations do not provide
complete if any information on solar data, chiefly due to the capital
and maintenance costs that measuring instruments incur. For instance,
global radiation is the most frequently measured parameter, its two
components, i.e. diffuse and direct irradiance are often not measured.
Improvements have been made to the meteorological radiation model
MRM which, had been developed by Muneer et al. as a simple broadband
irradiance estimation model based on synoptic information, by incorporating
the sunshine information in the modelâs regressions. The result
of the improvement of the model is a considerable reduction in biases
and scatter in the comparison between estimated and measured data.
The improved meteorological radiation model, IMRM is more accurate,
by up to 70% in some cases, than its predecessor in estimating, global
and diffuse horizontal irradiance. When sunshine, atmospheric pressure
and temperature are not measured by a nearby station, yet cloud information
is recorded, radiation estimation models based on cloud cover, CRM,
can be used. Three CRMs have been compared to newly proposed models.
It was found that models with locally fitted coefficients gave a
more accurate estimation of the solar radiation than CRMs with generalized
coefficients. The newly proposed model performed better that the
older generation models. The third section of the article deals with
estimation of diffuse radiation and possible improvements in its
modeling. In this section, apart from clearness index (kt), influence
of the synoptic parameters of sunshine fraction (SF), cloud cover
(CC) and air mass (m) on diffuse fraction of global radiation (k)
is studied both qualitatively and quantitatively. It is found that,
SF shows a strong bearing on the kâkt relationship followed by
CC and then m. As a next step, a series of models are developed for
k as a polynomial function of kt, SF, CC and m. After an extensive
evaluation procedure, a regression model is selected such that the
diffuse radiation can be estimated with reasonable accuracy without
making the model overtly complex. It was found that among all the
models, the composite model involving all parameters provides the
most accurate estimation of diffuse radiation. The site-specific
models are further investigated for any appreciable correlations
between different locations and their possible attributions. It was
also found that a single model could more than adequately estimate
the diffuse radiation for the locations within a given region. Three
optimum models are also recommended for each region, in view of the
fact that information on all parameters is not necessarily available
for all sites. This study reveals a significant improvement from
the conventional kâkt regression models to the presently proposed
models, therefore, leading to more accurate estimation of diffuse
radiation by approximately 50%.
