Some new GWO variants for PV systems modelling

Authors

  • Simran Srivastava Department of Electrical & Instrumentation Engineering, Thapar Institute of Engineering and Technology, Patiala-147004, Punjab, India Author
  • Saumyadip Hazra Department of Electrical & Instrumentation Engineering, Thapar Institute of Engineering and Technology, Patiala-147004, Punjab, India Author
  • Shini Agarwal Department of Electrical & Instrumentation Engineering, Thapar Institute of Engineering and Technology, Patiala-147004, Punjab, India Author
  • Sauhardh Sethi Department of Electrical & Instrumentation Engineering, Thapar Institute of Engineering and Technology, Patiala-147004, Punjab, India Author
  • Souvik Ganguli Department of Electrical & Instrumentation Engineering, Thapar Institute of Engineering and Technology, Patiala-147004, Punjab, India, Author

DOI:

https://doi.org/10.61841/7bk70r53

Keywords:

Single double model (SDM, Grey wolf optimizer (GWO), parameter estimation.

Abstract

Single Diode Model (SDM) is a popularly model used for the modelling of PV cells where five parameters are to be determined. This work accurately determines the five parameters of the SDM using meta-heuristic algorithm. Three equations have been considered for parameter extraction. The parameters of three widely used panels (KC200GT multi-crystal, MSX-60 poly-crystalline, and CS6K-280 M mono-crystalline) are extracted. The summation of the square of errors is used to define the error function. The Grey Wolf optimization (GWO) and its variants are being used. The values of the parameters and the error for all the three panels are compared for each algorithm. The results obtained are very promising and the error in the results is very less with EGWO proving out to be the best.

 

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Published

31.10.2020

Issue

Vol. 24 No. 8 (2020): 24 (8) 2020

Section

Articles

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How to Cite

Srivastava, S., Hazra, S., Agarwal, S., Sethi, S., & Ganguli, S. (2020). Some new GWO variants for PV systems modelling. International Journal of Psychosocial Rehabilitation, 24(8), 7120-7129. https://doi.org/10.61841/7bk70r53