Parameter Extraction of Photovoltaic Module Using Tunicate Swarm Algorithm

Electronics

Abhinav Sharma¹  Vibhu Jately²  Brian Azzopardi²  Ankit Dasgotra³  Abhishek Sharma³  SunilKumar Tiwari³ 

[1] Department of Electrical and Electronics Engineering, School of Engineering, University of Petroleum and Energy Studies, Dehradun 248007, India;MCAST Energy Research Group, Institute of Engineering and Transport, Malta College of Arts, Science and Technology, PLA9032 Paola, Malta;Research and Development Department, University of Petroleum and Energy Studies, Dehradun 248007, India;

关键词: photovoltaic;    TSA;    parameter extraction;    single-diode model;    double-diode model;    swarm intelligence;   

DOI  :  10.3390/electronics10080878

来源: DOAJ

【 摘 要 】

In the renewable energy sector, the extraction of parameters for solar photovoltaic (PV) cells is a widely studied area of research. Parameter extraction is a non-linear complex optimization problem for solar PV cells. In this research work, the authors have implemented the Tunicate swarm algorithm (TSA) to estimate the optimized value of the unknown parameters of a PV cell/module under standard temperature conditions. The simulation results have been compared with four different, pre-existing optimization algorithms: gravitational search algorithm (GSA), a hybrid of particle swarm optimization and gravitational search algorithm (PSOGSA), sine cosine (SCA), and whale optimization (WOA). The comparison of results broadly demonstrates that the TSA algorithm outperforms the existing optimization algorithms in terms of root mean square error (RMSE) and convergence rate. Furthermore, the statistical results confirm that the TSA algorithm is a better algorithm in terms of average robustness and precision. The Friedman ranking test is also carried out to demonstrate the competency and reliability of the implemented approach.

【 授权许可】

Unknown