Citation: Fajuke, I.D.; Raji, A.K.
Firefly Algorithm-Based
Optimization of the Additional
Energy Yield of Bifacial PV Modules.
Energies 2022, 15, 2651. https://
doi.org/10.3390/en15072651
Academic Editor: Luis
Hernández-Callejo
Received: 17 January 2022
Accepted: 15 February 2022
Published: 5 April 2022
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Article
Firefly Algorithm-Based Optimization of the Additional Energy
Yield of Bifacial PV Modules
Ibukun Damilola Fajuke * and Atanda K. Raji *
Department of Electrical, Electronic and Computer Engineering, Faculty of Engineering and the Built
Environment, Cape Peninsula University of Technology, Bellville 7535, South Africa
* Correspondence: 221598057@mycput.ac.za (I.D.F.); rajia@cput.ac.za (A.K.R.)
Abstract:
A solar bifacial photovoltaic (PV) module is designed so that it permits the addition of
the back electrode to the prevailing silicon PV on the front side. Hence, it has the ability to harvest
energy using its front and back faces. This study presents an optimization model for calculating
the extra energy yield (EY) that can be harvested from the backside of a bifacial PV module using
the Firefly Algorithm (FA). Mathematical modelling of the various parameters that influence the
extra EY of the backside of a bifacial module was carried out using SIMULINK. Moreover, the
mathematical model of the EY of the module was also carried out and then optimized using FA.
The optimization model was confined to two orientation states namely the vertical south–north and
vertical east–west at Ogbomosho (8.1227
◦
N, 4.2436
◦
E), Nigeria, with different values of albedo
and mounting heights. The simulation result shows that the vertical east–west oriented modules
outperform the vertical south–north oriented modules in terms of the EY generated. The result
also showed that the maximum value of the EY is harvested at a mounting height of 1 m above the
ground with row spacing of 2.5 m and a tilt angle of 25 degrees. Therefore, an optimal selection of the
mounting surface (albedo) and mounting elevation values can harvest an extra EY of 5 to 45 per cent
and help minimize the cost of energy generated using bifacial PV modules for electricity generation.
Keywords: bifacial PV module; Firefly Algorithm; additional energy yield; renewable energy
1. Introduction
The continuous rise in energy demand witnessed during the last few decades is a
result of overpopulation and technological advancements. In addition, the ever-increasing
price of fossil fuels, the depletion of the ozone layer which is caused by the burning of fossil
fuels and the need to prevent the looming global warming has justified the need for an
alternate source of energy generation [
1
]. With the attention of the world shifting towards
renewable energy sources, exciting advancements in solar power specifically, photovoltaic
(PV) technologies have emerged. Solar PV systems have become one of the most promising
technologies for global energy production. It is estimated that about 650 GWp of PV
systems have been installed worldwide as of 2021. The most recent of these technologies is
the bifacial PV solar module [2,3].
Bifacial solar modules are designed to collect sunlight from both the front and back
sides for energy production. Since their inception, studies have shown that these modules
have a higher energy output potential compared to their monoracial PV modules counter-
parts. This is because of their ability to collect solar irradiation using the front and back
sides. In recent times, the interest in bifacial PV modules continues to rise as a result of
their ability to lower the price of the energy-generated PV systems [1].
One of the main advantages of a solar bifacial PV module is its ability to generate
power using the incidence irradiance from both sides of the module. However, various
setbacks exist when accurately predicting and measuring the extra EY of the back side
of bifacial PV modules [
4
]. Therefore, optimization of system design should be treated
Energies 2022, 15, 2651. https://doi.org/10.3390/en15072651 https://www.mdpi.com/journal/energies
