Estimation of monthly Global Horizontal irradiation pan India using
spatial interpolation and comparing its deviations from standard dataset
Abstract
In the current scenario of increasing demand for solar photovoltaic (PV)
systems, the need to predict their feasibility and performance is more
than ever. Irradiance of a geographical location almost exclusively
determines the generation possible via solar. Hence, accurate irradiance
data is required to assess the value of solar PV systems. Emphasizing
such need, this paper presents a method of estimating global horizontal
irradiance (GHI) using the two dimensional (2-D) spatial interpolation
technique. The proposed model is geo-agnostic and can estimate
irradiance depending on the geographical range of the input data. This
paper also compares the model predictions with a standard irradiation
dataset in the industry. This comparison helps in getting insights
regarding the spatio-temporal trends in recent times. As part of our
asset management, solar PV plants spread all over India have irradiation
sensors whose measures are sent to our servers on a real-time basis.
This is incorporated into our in-house analytics portal which is
developed for operations and monitoring. Thus, the data is organized for
each plant with its geographical parameters (latitude and longitude)
along with Global Tilted Irradiation (GTI) measured by on ground
sensors. T-factors (calculated as function of tilt, azimuth of the site)
corresponding to each sensor orientation are also known which are used
to obtain Global Horizontal Irradiation (GHI) values. As part of our
study, the increasing predominance of solar PV as a renewable source of
energy is discussed. This has focused the attention on the need to have
quality irradiation data. The above research has been as an endeavour to
use a data-driven approach to solve the issue at hand. Hopefully, this
work can showcase the power of using data-intensive techniques such as
the one shown to solve the many challenges in the energy industry
especially those in solar. The model is built using irradiation sensor
data pan India and used an effective spatial interpolation technique,
kriging, to produce the gap-filled estimates. The statistical measures
of estimate error are also mentioned which show impressive accuracy.
Heat maps for respective months have also been produced for better
visualization of GHI trends. An independent dataset of industrial
benchmarking standards is also compared with the estimates to better
understand the temporal GHI trends with respect to long-term averaged
values. The assessment of this work’s potential is for the industrial
community to ascertain as this can have various use cases of immense
business value.