Enhanced Vibrating Particles System Algorithm for Parameters Estimation of Photovoltaic System

Autor: René Wamkeue, Patrick Juvet Gnetchejo, Daniel Eutyche Mbadjoun Wapet, Salomé Ndjakomo Essiane, Pierre Ele, Steve Perabi Ngoffe
Rok vydání: 2019
Předmět:
Zdroj: Journal of Power and Energy Engineering. :1-26
ISSN: 2327-5901
2327-588X
DOI: 10.4236/jpee.2019.78001
Popis: To evaluate the performance of a photovoltaic panel, several parameters must be extracted from the photovoltaic. These parameters are very important for the evaluation, monitoring and optimization of photovoltaic. Among the methods developed to extract photovoltaic parameters from current-voltage (I-V) characteristic curve, metaheuristic algorithms are the most used nowadays. A new metaheuristic algorithm namely enhanced vibrating particles system algorithm is presented here to extract the best values of parameters of a photovoltaic cell. Five recent algorithms (grey wolf optimization (GWO), moth-flame optimization algorithm (MFOA), multi-verse optimizer (MVO), whale optimization algorithm (WAO), salp swarm-inspired algorithm (SSA)) are also implemented on the same computer. Enhanced vibrating particles system is inspired by the free vibration of the single degree of freedom systems with viscous damping. To extract the photovoltaic parameters using enhanced vibrating particles system algorithm, the problem can be set as an optimization problem with the objective to minimize the difference between measured and estimated current. Four case studies have been implemented here. The results and comparison with other methods exhibit high accuracy and validity of the proposed enhanced vibrating particles system algorithm to extract parameters of a photovoltaic cell and module.
Databáze: OpenAIRE