Research Papers

Prediction of Solar Photovoltaic/Thermal Collector Power Output Using Fuzzy Logic

[+] Author and Article Information
M. Sridharan

Saranathan College of Engineering,
Tiruchirappalli 620012, Tamil Nadu, India
e-mail: sridhudhiya@gmail.com

G. Jayaprakash

Saranathan College of Engineering,
Tiruchirappalli 620012, Tamil Nadu, India
e-mail: jayaprakashcad@gmail.com

M. Chandrasekar

Anna University of Technology,
Tiruchirappalli 620024, Tamil Nadu, India
e-mail: shekarpunchu@yahoo.com

P. Vigneshwar

Saranathan College of Engineering,
Tiruchirappalli 620012, Tamil Nadu, India
e-mail: Vigneshwar-mech@saranathan.ac.in

S. Paramaguru

Saranathan College of Engineering,
Tiruchirappalli 620012, Tamil Nadu, India
e-mail: paramaguru-mech@saranathan.ac.in

K. Amarnath

Saranathan College of Engineering,
Tiruchirappalli 620012, Tamil Nadu, India
e-mail: amar-mech@saranathan.ac.in

1Corresponding author.

Contributed by the Solar Energy Division of ASME for publication in the JOURNAL OF SOLAR ENERGY ENGINEERING: INCLUDING WIND ENERGY AND BUILDING ENERGY CONSERVATION. Manuscript received November 29, 2017; final manuscript received June 25, 2018; published online July 24, 2018. Assoc. Editor: Gerardo Diaz.

J. Sol. Energy Eng 140(6), 061013 (Jul 24, 2018) (6 pages) Paper No: SOL-17-1473; doi: 10.1115/1.4040757 History: Received November 29, 2017; Revised June 25, 2018

In recent years, solar PV/T water collectors have been identified as one of the most promising hybrid devices. It is a combination of solar photovoltaic (PV) and solar flat plate collector (FPC) systems capable of generating electrical and thermal power simultaneously. This study presents a model which predicts solar PV/T collector power output using fuzzy logic techniques. A fuzzy logic model was established to predict power output of PV/T with respect to changes in input process and FPC output power. Membership functions were allocated in connection with each model input. Experimental tests conducted during the month of December 2016 are compared with the developed fuzzy model to verify predicted results. The results indicate an agreement between fuzzy model and experimental results with an accuracy of 94.38% and error of 5.62%.

Copyright © 2018 by ASME
Your Session has timed out. Please sign back in to continue.


Sivakumar, P. , Christraj, W. , Sridharan, M. , and Jayamalathi, N. , “ Performance Improvement Study of Solar Water Heating System,” ARPN J. Eng. Appl. Sci., 7(1), pp. 45–49. http://www.arpnjournals.com/jeas/research_papers/rp_2012/jeas_0112_621.pdf
Hamid, S. A. , Othman, M. Y. , Sopian, K. , and Zaidi, S. H. , 2014, “ An Overview of Photovoltaic Thermal Combination (PV/T Combi) Technology,” Renewable Sustainable Energy Rev., 38, pp. 212–222. [CrossRef]
Shyam, G. N. , Tiwari, O. F. , Mishra, R. K. , and Al-Helal, I. M. , 2016, “ Performance Evaluation of N-Photovoltaic Thermal (PVT) Water Collectors Partially Covered by Photovoltaic Module Connected in Series: An Experimental Study,” Sol. Energy, 134, pp. 302–313. [CrossRef]
Bahaidarah, H. M. S. , Baloch, A. A. B. , and Gandhidasan, P. , 2016, “ Uniform Cooling of Photovoltaic Panels: A Review,” Renewable Sustainable Energy Rev., 57, pp. 1520–1544. [CrossRef]
Nizetic, S. , Coko, D. , Yadav, A. , and Grubisic-Cabo, F. , 2016, “ Water Spray Cooling Technique Applied on a Photovoltaic Panel: The Performance Response,” Energy Convers. Manage., 108, pp. 287–296.
Michael, J. J. , Iniyan, S. , and Goic, R. , 2015, “ Flat Plate Solar Photovoltaic–Thermal (PV/T) Systems: A Reference Guide,” Renewable Sustainable Energy Rev., 51, pp. 62–88. [CrossRef]
Rizwan, M. , Jamil, M. , Kirmani, S. , and Kothari, D. P. , 2014, “ Fuzzy Logic Based Modeling and Estimation of Global Solar Energy Using Meteorological Parameters,” Energy, 70, pp. 685–691. [CrossRef]
Teo, H. G. , Lee, P. S. , and Hawlader, M. N. A. , 2012, “ An Active Cooling System for Photovoltaic Modules,” Appl. Energy, 90(1), pp. 309–315. [CrossRef]
Chandrasekar, M. , Suresh, S. , Senthilkumar, T. , and Ganesh Karthikeyan, M. , 2013, “ Passive Cooling of Standalone Flat PV Module With Cotton Wick Structures,” Energy Convers. Manage., 71, pp. 43–50. [CrossRef]
Singhai R. , 2013, Introduction to Fuzzy Logic, 1st ed., PHI Learning Publishers, New Delhi, India.
Gilat, A. , 2004, MATLAB: An introduction with Applications, 4th ed., John Wiley and Sons, Hoboken, NJ.
Zalnezhad, E. , “ Surface Hardness Prediction of CrN Thin Film Coating on AL7075-T6 Alloy Using Fuzzy Logic System,” Int. J. Precis. Eng. Manuf., 14(3), pp. 467–473. [CrossRef]


Grahic Jump Location
Fig. 2

Standalone partially covered solar PV/T collectors

Grahic Jump Location
Fig. 1

Architecture of fuzzy logic based PV/T predictive model

Grahic Jump Location
Fig. 5

Variation in thermal and electrical efficiency with respect to time

Grahic Jump Location
Fig. 6

Comparison of fuzzy logic model prediction with the measured PV/T power output

Grahic Jump Location
Fig. 4

PV/T power output in relations to change in PV and FPC power output

Grahic Jump Location
Fig. 3

(a) Input variable-1 PV output power, (b) input variable-2 FPC output power, and (c) output variable-PV/T output power



Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In