New correlations for photovoltaic panel’s efficiency and surface temperature with different operating parameters

ABSTRACT

Solar photovoltaic (PV) panels and solar thermal collectors are two major technologies used to extract electrical and thermal energy, respectively, from solar irradiation. PV panels convert only 15–20% of incident solar radiation into electricity. The remaining radiation elevates the panel’s surface temperature, which badly affects the conversion efficiency and reduces the overall lifespan of the panel. Hence, in this paper, we investigate three cooling techniques developed in-house to maintain the PV panel’s surface temperature: passive cooling, active cooling, and combined cooling. A novel PV/T-PCM system was designed and fabricated to conduct a detailed experimental analysis of each of the cooling methods used on the performance of PV panel in the form of temperature and electrical efficiency of the panel. The temperature of the panel surface got reduced by a maximum of 36% at 1,050 W/m², and as an effect of that, the electrical efficiency was also improved by around 42% in the case of a combined cooling technique. Finally, empirical correlations were also developed to predict the electrical efficiency and PV panel surface temperature using the experimental data of present investigation considering investigated system and operating parameters. Based on the experimental results, the coefficient of determination (R²), for the correlation of electrical efficiency, was found to be 0.90 and 0.9188 for surface temperature that indicate good confidence level for both the correlations. As a result, the correlations and results are more important from an application standpoint for the design and development of the PV/T system.

KEYWORDS:

• Solar PV/T system
• solar energy
• phase change materials
• electrical efficiency
• correlation

Nomenclature

η	=	Electrical efficiency of PV panel
P	=	Power produced by the PV panel
V	=	Voltage
I	=	Current
Is	=	Value of solar irradiation
Apanel	=	PV panel surface area
T	=	PV panel surface temperature (°C)
t	=	Time in seconds
wt%	=	Weight percent

Abbreviations

PCM	=	Phase Change Material
PV/T	=	Photovoltaic/Thermal
AMF	=	Aluminum Metal Foam
SWCNT	=	Single-Walled Carbon Nano Tube
NOCT	=	Nominal Operating Cell Temperature
ANFIS	=	Adaptive Neuro-Fuzzy Inference Systems
AARD	=	Absolute Average Relative Deviation
MSE	=	Mean Squared Error
LPM	=	Liter Per Minute

Acknowledgements

The authors are very grateful to Department of Hydro and Renewable Energy of Indian Institute of Technology (IIT) Roorkee and Department of Mechanical & Industrial Engineering, IIT Roorkee for providing the essential support for the experimental work.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

The experimental work was performed at Renewable Energy System laboratory at Department of Hydro and Renewable Energy of IIT Roorkee. The experimental work was not funded by any of the agency.

Notes on contributors

Ankit Dev

Ankit Dev is working as an assistant professor in the department of mechanical engineering, SR University, Warangal, India and has extensive working experience in the field of solar pv thermal energy systems.

Ravi Kumar

Ravi Kumar is currently working as a professor in the mechanical & industrial engineering department, IIT Roorkee.

Aditya Kumar

Aditya Kumar is working as an assistant professor in the department of energy & environment, NIT Tiruchirappalli, India and has extensive working experience in the field of nanofluids and solar pv thermal energy systems.