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International Journal of Mathematical, Engineering and Management Sciences

ISSN: 2455-7749 . Open Access


An Effective Method for Parameter Estimation of Solar PV Cell Using Grey-Wolf Optimization Technique

An Effective Method for Parameter Estimation of Solar PV Cell Using Grey-Wolf Optimization Technique

Abhishek Sharma
Research and Development Department, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India.

Abhinav Sharma
Department of Electrical and Electronics Engineering, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India.

Averbukh Moshe
Department of Electrical and Electronics Engineering, Ariel University, Ariel, Israel.

Nikhil Raj
Research and Development Department, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India.

Rupendra Kumar Pachauri
Department of Electrical and Electronics Engineering, University of Petroleum and Energy Studies, Dehradun, Uttarakhand, India.

DOI https://doi.org/10.33889/IJMEMS.2021.6.3.054

Received on November 21, 2020
  ;
Accepted on February 07, 2021

Abstract

In the field of renewable energy, the extraction of parameters for solar photovoltaic (PV) cells is a widely studied area of research. Parameter extraction of solar PV cell is a highly non-linear complex optimization problem. In this research work, the authors have explored grey wolf optimization (GWO) algorithm to estimate the optimized value of the unknown parameters of a PV cell. The simulation results have been compared with five different pre-existing optimization algorithms: gravitational search algorithm (GSA), a hybrid of particle swarm optimization and gravitational search algorithm (PSOGSA), sine cosine (SCA), chicken swarm optimization (CSO) and cultural algorithm (CA). Furthermore, a comparison with the algorithms existing in the literature is also carried out. The comparative results comprehensively demonstrate that GWO outperforms the existing optimization algorithms in terms of root mean square error (RMSE) and the rate of convergence. Furthermore, the statistical results validate and indicate that GWO algorithm is better than other algorithms in terms of average accuracy and robustness. An extensive comparison of electrical performance parameters: maximum current, voltage, power, and fill factor (FF) has been carried out for both PV model.

Keywords- Photovoltaic, GWO, Parameter extraction, Single-diode model, Double-diode model.

Citation

Sharma, A., Sharma, A., Moshe, A., Raj, N., & Pachauri, R. K. (2021). An Effective Method for Parameter Estimation of Solar PV Cell Using Grey-Wolf Optimization Technique. International Journal of Mathematical, Engineering and Management Sciences, 6(3), 911-931. https://doi.org/10.33889/IJMEMS.2021.6.3.054.