posted on 2015-11-24, 11:45authored byFoteini Plyta
This thesis presents the simulated optical design of a fully LED-based solar simulator.
The work focuses on the spectral mismatch, the spatial uniformity acquired
with direct light and the spectral uniformity. The proposed LED solar simulator has
an illuminated area of 32cm x 32cm and can characterise medium size photovoltaic
devices under variable light intensities and variable output spectra. The spectral
range covered is between 350nm and 1300nm which offers the capability of characterising
various different PV technologies. The spectral match classification is A+
for the 400nm-1100nm spectral range and B for the 350nm-1300nm spectral range.
The spatial non-uniformity of irradiance is also A+ across the illuminated area. The
temporal stability of LEDs can easily reach class A as proven by previous work in
the group and is not examined here.
An automated LED selection methodology that optimises the spectral mismatch
was developed to replace the trial and error method usually employed. The algorithm
created accommodates a more accurate selection of the most appropriate LED
wavelengths in order to represent the solar spectrum even more closely than before
and improve the uncertainties caused by the spectral mismatch. A genetic algorithm
and the chi-squared error criterion were used to create the automated methodology
applying a minimisation technique. This technique helps the user choose from a
wide variety of LEDs available on the market, determine the wavelengths and the
number of LEDs per wavelength needed to accurately represent the AM1.5G solar
spectrum and other spectra and provides a cost-effective and straightforward solution.
The solution chosen for this project involves 24 different wavelengths.
A direct beam approach was followed regarding the collimation of light to account
for the measurement errors introduced by the frequent overestimation of the
current due to the unpredicted reflections caused by diffuse light. Extended simulations
of different optics were performed to determine the best layout that offers
good directionality and satisfactory non-uniformity of irradiance and light collection
efficiency. Total internal reflectors of 13.5mm diameter proved to be the most
appropriate primary optics with the highest collection efficiency. An imaging homogeniser
was chosen as secondary optics for its capability to mix the light and
achieve low levels of non-uniformity of irradiance. The spatial non-uniformity of
irradiance achieved with 612 LEDs is 0.29% across the 32cm x 32cm illuminated
area and the irradiance is equal to 1316 W/m2 assuming 1W LEDs.
The hexagonal placement set-up was used for the placement of the LEDs since
it results in the lowest non-uniformity and it is the best option for keeping the lamp
size compact. An optical engineering software called FRED was used for ray-tracing
individual optics. Due to the time and computational demands of the simulations a
different approach needed to be found for overlaying the irradiance profiles of hundreds
or even thousands optical elements. An algorithm was developed in Matlab
that takes into consideration the geometry of each case and calculates the final irradiance
profile.
A placement methodology that accounts for the spectral uniformity on the illuminated
target was also developed. It was shown that placing the LEDs randomly
does not offer enough spectral mixing and is therefore problematic as it introduces
an unexpected source of measurement uncertainty. The influence of spectral non-uniformity
varies for different photovoltaic technologies due to their variable spectral
responses. Thus, a placement methodology using a genetic algorithm was developed
to optimise the positioning of the LEDs. As a result the highest spectral non-uniformity
drops from almost 5% to 1.46% and the measurement uncertainty is
reduced significantly since an improvement of up to 1.8% is noted in the current
density non-uniformity.
Funding
Industrially funded (do not wish to be mentioned)
History
School
Mechanical, Electrical and Manufacturing Engineering
This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/
Publication date
2015
Notes
A Doctoral Thesis. Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University.