@article {HAMED202214979,
	title = {Techno-economic analysis for optimal configurations of PV systems with back reflectors},
	journal = {Energy Reports},
	volume = {8},
	year = {2022},
	note = {n/a},
	pages = {14979-14996},
	abstract = {<p>With the growth in the solar photovoltaic (PV) market, there is a renewed interest in increasing the system{\textquoteright}s annual produced energy. Most of the proposed solutions in the literature require special additional equipment, which might adversely affect the cost of the produced energy. This paper proposes an integrated PV-reflector system that augments the solar irradiance on already installed PV modules. A new mathematical model has been developed in MATLAB R2020a to simulate and techno-economically assess the proposed integrated PV system during the entire year using real meteorological data. A genetic algorithm has been employed in MATLAB R2020a to obtain the optimal geometric and optical parameters that maximize the annual produced energy and minimize the Levelized Cost of Electricity (LCOE) at two selected locations (Cairo in Egypt and Ma{\textquoteright}an in Jordan) and for three module technologies (monocrystalline, polycrystalline, and thin film) and different commercial reflectors. The optimal system configurations increased the annual energy production by up to 6.05, 5.14, and 8.34\% for the three PV technologies, respectively. For both locations, the optimal tilt angles of the PV module and reflector range between 24{\textdegree} and 34{\textdegree} for Cairo, and between 19{\textdegree} and 36{\textdegree} for Ma{\textquoteright}an, depending on the PV technology. Finally, all the system configurations have favorable and low payback periods (\~{}3 and 6.5 years for Ma{\textquoteright}an and Cairo, respectively), as well as attractive LCOE, which varies between 0.0369 and 0.044 USD/kWh in Ma{\textquoteright}an and between 0.0543 and 0.065 USD/kWh in Cairo.</p>
},
	keywords = {Back reflector, Desert Climate, Genetic optimization, Photovoltaic, Solar power generation, Techno-economic assessment},
	issn = {2352-4847},
	doi = {https://doi.org/10.1016/j.egyr.2022.11.053},
	url = {https://www.sciencedirect.com/science/article/pii/S2352484722024386},
	author = {Hamed, Ahmed and Al-Ghussain, Loiy and Muhammed A. Hassan and Annuk, Andres}
}
